VULHUNTER: Toward Discovering Vulnerabilities In Android Applications

VULHUNTER: Toward Discovering Vulnerabilities In Android Applications

VULHUNTER: Toward Discovering Vulnerabilities In Android Applications

ABSTRACT:

With the prosperity of the Android app economy, many apps have been published and sold in various markets. However, short development cycles and insufficient security development guidelines have led to many vulnerable apps. Although some systems have been developed for automatically discovering specific vulnerabilities in apps, their effectiveness and efficiency are usually restricted because of the exponential growth of paths to examine and simplified assumptions. In this article, the authors propose a new static-analysis framework for facilitating security analysts to detect vulnerable apps from three aspects. First, they propose an app property graph (APG), a new data structure containing detailed and precise information from apps. Second, by modeling app-related vulnerabilities as graph traversals, the authors conduct graph traversals over APGs to identify vulnerable apps for easing the identification process. Third, they reduce the workload of manual verification by removing infeasible paths and generating attack inputs whenever possible. They have implemented the framework in a system named VulHunter with 9,145 lines of Java code and modeled five types of vulnerabilities. Checking 557 popular apps that are randomly collected from Google Play and have at least 1 million installations, the authors found that 375 apps (67.3 percent) have at least one vulnerability.

PROJECT OUTPUT VIDEO: (Click the below link to see the project output video):

EXISTING SYSTEM:

  • Existing research on automatic vulnerability discovery for applications (“apps”) usually focuses on several specific types of vulnerabilities because of the undecidability of the generic problem of spotting program vulnerabilities.
  • 1, For example, ComDroid aims at Intentrelated issues (that is, unauthorized Intent receipt and Intent spoofing).
  • 2, SMV-Hunter detects SSL and Transport Layer Security (TLS) man-in-the-middle vulnerabilities.
  • 3, ContentScope examines the vulnerabilities of an unprotected content provider.
  • 4, AndroidLeaks uncovers potential private information leakage.
  • 5, Woodpecker targets capability leak vulnerabilities.
  • 6, CHEX discovers component hijacking vulnerabilities.
  • 7, However, these systems’ effectiveness and efficiency are usually restricted in practice due to the exponential growth of paths to examine, simplified assumptions, and the limited number of vulnerability patterns.1,8 Moreover, it is not easy to extend these systems to capture new vulnerabilities, although they share some common,components (such as constructing control-flow graphs and dataflow graphs).

DISADVANTAGES OF EXISTING SYSTEM:

  • It is not easy to extend these systems to capture new vulnerabilities, although they share some common, components (such as constructing control-flow graphs and dataflow graphs).
  • They did not discover vulnerable apps, and it is not clear how SCA processes those apps.

PROPOSED SYSTEM:

  • We propose a new static-analysis framework to facilitate vulnerability discovery for apps by extracting detailed and precise information from apps and easing the identification process.
  • Moreover, the framework can reduce the manual-verification workload by performing slicing and filtering out infeasible paths. To our knowledge, existing approaches cannot achieve these goals simultaneously. Moreover, defining app property graphs (APGs) and employing graph databases can scale up the vulnerability discovery process.
  • Researchers are exploring an alternative vulnerability-discovery approach of facilitating security analysts by providing detailed and precise information and expert knowledge. The work closest to our approach is the code property graph (CPG),1 which combines an abstract syntax tree (AST), control-flow graph (CFG), and program dependency graph (PDG) to represent C source codes and model common vulnerabilities as graph traversals. Therefore, finding potential vulnerabilities is turned into performing graph traversals over CPGs with much better performance in terms of accuracy and flexibility.
  • Although we also model vulnerabilities as graph traversals and conduct graph traversals to find vulnerable apps, significant differences exist between the two approaches.

ADVANTAGES OF PROPOSED SYSTEM:

  • Capturing vulnerabilities is made easy and also modeling vulnerabilities become easy as per graph traversals.
  • It reduces false positives and optimizes queries according to vulnerabilities pattern.

SYSTEM ARCHITECTURE:

vul

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

  • System :         Pentium IV 2.4 GHz.
  • Hard Disk :         40 GB.
  • Floppy Drive : 44 Mb.
  • Monitor : 15 VGA Colour.
  • Mouse :
  • Ram : 512 Mb.
  • MOBILE : ANDROID

SOFTWARE REQUIREMENTS:

  • Operating system : Windows 7.
  • Coding Language : Java 1.7
  • Tool Kit : Android 2.3 ABOVE
  • IDE : Eclipse

REFERENCE:

Chenxiong Qian Xiapu Luo Yu Le, Hong Kong Polytechnic University, Guofei Gu Texas, A&M University, “VULHUNTER: TOWARD DISCOVERING VULNERABILITIES IN ANDROID APPLICATIONS”, IEEE Computer Society 2015.

User-Defined Privacy Grid System for Continuous Location-Based Services

User-Defined Privacy Grid System for Continuous Location-Based Services

User-Defined Privacy Grid System for Continuous Location-Based Services

ABSTRACT:

Location-based services (LBS) require users to continuously report their location to a potentially untrusted server to obtain services based on their location, which can expose them to privacy risks. Unfortunately, existing privacy-preserving techniques for LBS have several limitations, such as requiring a fully-trusted third party, offering limited privacy guarantees and incurring high communication overhead. In this paper, we propose a user-defined privacy grid system called dynamic grid system (DGS); the first holistic system that fulfills four essential requirements for privacy-preserving snapshot and continuous LBS. (1) The system only requires a semi-trusted third party, responsible for carrying out simple matching operations correctly. This semi-trusted third party does not have any information about a user’s location. (2) Secure snapshot and continuous location privacy is guaranteed under our defined adversary models. (3) The communication cost for the user does not depend on the user’s desired privacy level, it only depends on the number of relevant points of interest in the vicinity of the user. (4) Although we only focus on range and k-nearest-neighbor queries in this work, our system can be easily extended to support other spatial queries without changing the algorithms run by the semi-trusted third party and the database server, provided the required search area of a spatial query can be abstracted into spatial regions. Experimental results show that our DGS is more efficient than the state-of-the-art privacy-preserving technique for continuous LBS.

PROJECT OUTPUT VIDEO: (Click the below link to see the project output video):

EXISTING SYSTEM:

  • Spatial cloaking techniques have been widely used to preserve user location privacy in LBS. Most of the existing spatial cloaking techniques rely on a fully-trusted third party (TTP), usually termed location anonymizer that is required between the user and the service provider.
  • When a user subscribes to LBS, the location anonymizer will blur the user’s exact location into a cloaked area such that the cloaked area includes at least k – 1 other users to satisfy k-anonymity.
  • In a system with such regional location privacy it is difficult for the user to specify personalized privacy requirements. The feeling based approach alleviates this issue by finding a cloaked area based on the number of its visitors that is at least as popular as the user’s specified public region. Although some spatial clocking techniques can be applied to peer-to-peer environments, these techniques still rely on the k-anonymity privacy requirement and can only achieve regional location privacy.
  • Furthermore, these techniques require users to trust each other, as they have to reveal their locations to other peers and rely on other peers’ locations to blur their locations, another distributed method was proposed that does not require users to trust each other, but it still uses multiple TTPs.
  • Another family of algorithms uses incremental nearest neighbor queries, where a query starts at an “anchor” location which is different from the real location of a user and iteratively retrieves more points of interest until the query is satisfied. While it does not require a trusted third party, the approximate location of a user can still be learned; hence only regional location privacy is achieved.

DISADVANTAGES OF EXISTING SYSTEM:

  • The TTP model has four major drawbacks.
  • It is difficult to find a third party that can be fully trusted.
  • All users need to continuously update their locations with the location anonymizer, even when they are not subscribed to any LBS, so that the location anonymizer has enough information to compute cloaked areas.
  • Because the location anonymizer stores the exact location information of all users, compromising the location anonymizer exposes their locations.
  • k-anonymity typically reveals the approximate location of a user and the location privacy depends on the user distribution.

PROPOSED SYSTEM:

  • In this paper, we propose a user-defined privacy grid system called dynamic grid system (DGS) to provide privacy-preserving snapshot and continuous
  • The main idea is to place a semi trusted third party, termed query server (QS), between the user and the service provider (SP). QS only needs to be semi-trusted because it will not collect/store or even have access to any user location information.
  • Semi-trusted in this context means that while QS will try to determine the location of a user, it still correctly carries out the simple matching operations required in the protocol, i.e., it does not modify or drop messages or create new messages. An untrusted QS would arbitrarily modify and drop messages as well as inject fake messages, which is why our system depends on a semi-trusted
  • The main idea of our DGS. In DGS, a querying user first determines a query area, where the user is comfortable to reveal the fact that she is somewhere within this query area. The query area is divided into equal-sized grid cells based on the dynamic grid structure specified by the user. Then, the user encrypts a query that includes the information of the query area and the dynamic grid structure, and encrypts the identity of each grid cell intersecting the required search area of the spatial query to produce a set of encrypted identifiers.
  • Next, the user sends a request including (1) the encrypted query and (2) the encrypted identifiers to QS, which is a semi-trusted party located between the user and SP. QS stores the encrypted identifiers and forwards he encrypted query to SP specified by the user. SP decrypts the query and selects the POIs within the query area from its database.

ADVANTAGES OF PROPOSED SYSTEM:

  • For each selected POI, SP encrypts its information, using the dynamic grid structure specified by the user to find a grid cell covering the POI, and encrypts the cell identity to produce the encrypted identifier for that POI.
  • The encrypted POIs with their corresponding encrypted identifiers are returned to QS. QS stores the set of encrypted POIs and only returns to the user a subset of encrypted POIs whose corresponding identifiers match any one of the encrypted identifiers initially sent by the user.
  • After the user receives the encrypted POIs, she decrypts them to get their exact locations and computes a query answer.

SYSTEM ARCHITECTURE:

user d

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

  • System :         Pentium IV 2.4 GHz.
  • Hard Disk :         40 GB.
  • Floppy Drive : 44 Mb.
  • Monitor : 15 VGA Colour.
  • Mouse :
  • Ram : 512 Mb.
  • MOBILE : ANDROID

SOFTWARE REQUIREMENTS:

  • Operating system : Windows 7.
  • Coding Language : Java 1.7
  • Tool Kit : Android 2.3 ABOVE
  • IDE : Eclipse

REFERENCE:

Roman Schlegel, Member, IEEE, Chi-Yin Chow, Member, IEEE, Qiong Huang, Member, IEEE, and Duncan S. Wong, Member, IEEE, “User-Defined Privacy Grid System for Continuous Location-Based Services”, IEEE Transactions on Mobile Computing 2015.

User Privacy and Data Trustworthiness in Mobile Crowd Sensing

User Privacy and Data Trustworthiness in Mobile Crowd Sensing

User Privacy and Data Trustworthiness in Mobile Crowd Sensing

ABSTRACT:

Smartphones and other trendy mobile wearable devices are rapidly becoming the dominant sensing, computing and communication devices in peoples’ daily lives. Mobile crowd sensing is an emerging technology based on the sensing and networking capabilities of such mobile wearable devices. MCS has shown great potential in improving peoples’ quality of life, including healthcare and transportation, and thus has found a wide range of novel applications. However, user privacy and data trustworthiness are two critical challenges faced by MCS. In this article, we introduce the architecture of MCS and discuss its unique characteristics and advantages over traditional wireless sensor networks, which result in inapplicability of most existing WSN security solutions. Furthermore, we summarize recent advances in these areas and suggest some future research directions.

PROJECT OUTPUT VIDEO: (Click the below link to see the project output video):

EXISTING SYSTEM:

  • When searching for a place and nearest location, a user sends queries in the form of keyword.
  • Nowadays Smartphones are used for query searching in the internet servers. Also users use Smartphones for posting or uploading some important reports into the server.
  • Once the reports are uploaded, all other users get those results with the sensible information like location and time of the participant who uploads the reports. Participant may also upload some photos in social websites which may contain some information about his/her location.
  • This leads to the leakage of participant’s information to the queerer, one who performs search.

DISADVANTAGES OF EXISTING SYSTEM:

  • The leakage of sensible information to the querier, leads to misusing to participants.
  • Without proper registration of any users can upload and view reports.

PROPOSED SYSTEM:

  • In this paper, we present a novel approach to user privacy and data trustworthiness when they use mobile sensors to sense and share information to the server.
  • In MCS, privacy concerns arise due to the disclosure of private information such as participants’ identities, IP addresses, locations, trajectories, and lifestyle-related information.
  • MCS applications even aggravate the privacy problem because they make large volumes of information easily available through remote access. Thus, adversaries need not be physically present to maintain surveillance. They can gather information in a low-risk and anonymous manner.
  • Remote access also allows a single adversary to monitor multiple users simultaneously. We consider users’ location information as an example. Since MCS allows any voluntary participant to contribute data, the application server is exposed to erroneous or even malicious data. For example, participants may inadvertently put their wearable devices in an undesirable position while collecting sensor readings (e.g., Galaxy Gear kept in a pocket while sampling street-level noise). Moreover, malicious participants may deliberately contribute bad data. Both behaviors result in erroneous contributions, which need to be identified and eliminated to ensure the reliability of the computed summaries.

ADVANTAGES OF PROPOSED SYSTEM:

  • USER PRIVACY – Protecting query privacy with respect to the registration authority. Protecting node privacy with respect to the network
  • With the current technology, users’ locations and identities are not allowed to be hidden from the network operator. Based on the commodity mobile phones, our system obviates the need for special hardware or extra vehicle devices.
  • DATA TRUSTWORTHINESSData trustworthiness and user privacy preservation are two conflicting objectives in an MCS application. Strong mechanisms for protecting privacy might influence data trustworthiness. On the other hand, protecting the data trustworthiness counteracts the mechanisms for preserving privacy.

SYSTEM ARCHITECTURE:

user

MODULES:

  1. Participant or mobile node:
  2. Properly register with registration authority.
  3. Uploads sensor reports like location of places
  4. Service provider:
  5. Holds reports from mobile node.
  6. Provides anonymity for mobile node location details.

           iii. Provides reports for querier

  1. Querier:
  2. Searches for query
  3. Get reports according to proper query.

MODULE DESCRIPTION:

  • Participant or Mobile Node:

Participants or mobile nodes register properly with the application servers managed by MCS operator. Once the registration is confirmed by authority, he/she can upload reports with the help of mobile sensors in their smart phones.

  • Service providers:

The service providers on the other hand handle the mobile phone sensing information to the system. After getting all the user registration of participant and querier the confirmation for the mobile nodes are given, only when they have given valid details. Then the collected reports from mobile nodes are verified. When the querier queries, the reports for their query is transmitted to the querier with the encrypted details of participant.

  • Querier:

Querier are mobile users, who queries for their needs. They too have a valid registration with the registration authority. They get the reports according to their queries with encrypted details of participants. Also the location is shown in Google maps.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

  • System :         Pentium IV 2.4 GHz.
  • Hard Disk :         40 GB.
  • Floppy Drive : 44 Mb.
  • Monitor : 15 VGA Colour.
  • Mouse :
  • Ram : 512 Mb.
  • MOBILE : ANDROID

SOFTWARE REQUIREMENTS:

  • Operating system : Windows 7.
  • Coding Language : Java 1.7
  • Tool Kit : Android 2.3 ABOVE
  • IDE : Eclipse

REFERENCE:

DAOJING HE, SAMMY CHAN, AND MOHSEN GUIZANI, “USER PRIVACY AND DATA TRUSTWORTHINESS IN MOBILE CROWD SENSING”, IEEE Wireless Communications, February 2015.

Time-and-Energy-Aware Computation Offloading in Handheld Devices to Coprocessors and Clouds

Time-and-Energy-Aware Computation Offloading in Handheld Devices to Coprocessors and Clouds

Time-and-Energy-Aware Computation Offloading in Handheld Devices to Coprocessors and Clouds

ABSTRACT:

Running sophisticated software on smart phones could result in poor performance and shortened battery lifetime because of their limited resources. Recently, offloading computation workload to the cloud has become a promising solution to enhance both performance and battery life of smart phones. However, it also consumes both time and energy to upload data or programs to the cloud and retrieve the results from the cloud. In this paper, we develop an offloading framework, named Ternary Decision Maker (TDM), which aims to shorten response time and reduce energy consumption at the same time. Unlike previous works, our targets of execution include an on-board CPU, an on-board GPU, and a cloud, all of which combined provide a more flexible execution environment for mobile applications. We conducted a real-world application, i.e., matrix multiplication, in order to evaluate the performance of TDM. According to our experimental results, TDM has less false offloading decision rate than existing methods. In addition, by offloading modules, our method can achieve, at most, 75% savings in execution time and 56% in battery usage.

PROJECT OUTPUT VIDEO: (Click the below link to see the project output video):

EXISTING SYSTEM:

  • There have been many research efforts dedicated to offload data- or computation-intensive programs from a resourcepoor mobile device. Gu et al., Li et al., and Chen et al. partitioned source codes into client/server parts and then saved energy consumption by running the server parts at remote servers.
  • All these methods perform well for smallsize applications but may induce a significant overhead when partitioning large-size applications.
  • Advanced location-based services such as mobile advertisement services may use not only users’ locations but also users’ attributes. However, the existing location anonymization methods do not consider attribute information and may result in low-quality privacy protection.

DISADVANTAGES OF EXISTING SYSTEM:

  • User attributes do not have any privacy in use location based services.
  • Anonymization methods do not consider attribute information and may result in low-quality privacy protection.

PROPOSED SYSTEM:

  • In this paper, we have designed and implemented a decision framework for computation offloading. The decision is based on estimated execution time and energy consumption.
  • We aim to save both execution time and energy consumption at the same time. Unlike previous works, which consider only binary decisions, our ternary decision is suitable for multiple offloading targets. In our experiment, we presented a case study to validate the applicability in different situations.
  • Based on our decision framework, the matrix multiplication module tends to be offloaded to more powerful processors, such as local GPU or cloud. By offloading modules, we can achieve, at most, 75% savings in execution time and 56% in battery usage.
  • Our results also demonstrate high accuracy and low false decision rates of the proposed decision framework. Generally speaking, the false decision rate is less than 15% in most cases. Our future work includes three aspects.
  • First, we will implement a lightweight ping function in order to further reduce the overhead in collecting the parameter of bandwidth.
  • Second, we plan to investigate effects of different smart phones, mobile applications, and network environment on the accuracy of TDM. Finally, we will extend this work by considering different wireless technologies, such as LTE and WiMAX, and security issues.

ADVANTAGES OF PROPOSED SYSTEM:

  • The decision is based on estimated execution time and energy consumption also saves both execution time and energy consumption at the same time.
  • Ternary decision is suitable for multiple offloading targets.

SYSTEM ARCHITECTURE:

time

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

  • System :         Pentium IV 2.4 GHz.
  • Hard Disk :         40 GB.
  • Floppy Drive : 44 Mb.
  • Monitor : 15 VGA Colour.
  • Mouse :
  • Ram : 512 Mb.
  • MOBILE : ANDROID

SOFTWARE REQUIREMENTS:

  • Operating system : Windows 7.
  • Coding Language : Java 1.7
  • Tool Kit : Android 2.3 ABOVE
  • IDE : Eclipse

REFERENCE:

Ying-Dar Lin, Fellow, IEEE, Edward T.-H. Chu, Member, IEEE, Yuan-Cheng Lai, and Ting-Jun Huang, “Time-and-Energy-Aware Computation Offloading in Handheld Devices to Coprocessors and Clouds”, IEEE SYSTEMS JOURNAL, VOL. 9, NO. 2, JUNE 2015.

 

The Impact of API Change- and Fault-Proneness on the User Ratings of Android Apps

The Impact of API Change- and Fault-Proneness on the User Ratings of Android Apps

ABSTRACT:

The mobile apps market is one of the fastest growing areas in the information technology. In digging their market share, developers must pay attention to building robust and reliable apps. In fact, users easily get frustrated by repeated failures, crashes, and other bugs; hence, they abandon some apps in favor of their competition. In this paper we investigate how the fault- and change-proneness of APIs used by Android apps relates to their success estimated as the average rating provided by the users to those apps. First, in a study conducted on 5,848 (free) apps, we analyzed how the ratings that an app had received correlated with the fault- and change-proneness of the APIs such app relied upon. After that, we surveyed 45 professional Android developers to assess (i) to what extent developers experienced problems when using APIs, and (ii) how much they felt these problems could be the cause for unfavorable user ratings. The results of our studies indicate that apps having high user ratings use APIs that are less fault- and change-prone than the APIs used by low rated apps. Also, most of the interviewed Android developers observed, in their development experience, a direct relationship between problems experienced with the adopted APIs and the users’ ratings that their apps received.

PROJECT OUTPUT VIDEO: (Click the below link to see the project output video):

EXISTING SYSTEM:

  • The analysis of mobile applications and operating systems has become a hot research topic in the recent years. However, for reasons related to availability of source code and other artifacts (e.g., bugs, change requests, etc.), such studies have been mainly focused on the Android ecosystem.
  • Stability and fault-proneness in the Android API is a sensitive and timely topic, given the frequent releases and the number of applications that use these APIs.
  • The analysis is that extent the APIs fault- and change-proneness affect the user ratings of the Android apps using them, and the investigation to what extent Android developers experience problems when using APIs and how much they feel these problems can be causes of unfavorable user ratings/comments.

DISADVANTAGES OF EXISTING SYSTEM:

  • The impact of breaking changes could be a major factor for the development of Android apps in Java, because Android produced significant releases as rapidly as every one to six months.
  • No evidence is there on the impact of unstable APIs on the client code using those APIs.

PROPOSED SYSTEM:

  • In this paper we investigate how the fault- and change-proneness of APIs used by Android apps relates to their success estimated as the average rating provided by the users to those apps.
  • The goal of this paper is to provide solid empirical evidence and shed some light on the relationship between the success of apps (in terms of user ratings), and the change- and fault-proneness of the underlying APIs (i.e., Android API and third-party libraries). We designed two case studies. First, in a study conducted on 5,848 (free) apps, we analyzed how the ratings that an app had received correlated with the fault- and change-proneness of the APIs such app relied upon. After that, we surveyed 45 professional Android developers to assess (i) to what extent developers experienced problems when using APIs, and (ii) how much they felt these problems could be the cause for unfavorable user ratings.
  • The results of our studies indicate that apps having high user ratings use APIs that are less fault- proneness and change-prone than the APIs used by low rated apps. Also, most of the interviewed Android developers observed, in their development experience, a direct relationship between problems experienced with the adopted APIs and the users’ ratings that their apps received.

ADVANTAGES OF PROPOSED SYSTEM:

  • Implements recommenders to support developers in dealing with APIs updates that can potentially (and inadvertently) impact their apps with breaking changes and bugs.
  • The fault proneness was measured as the total number of bugs fixed in the used API, while to assess the change-proneness we used the number of changes at method level along three categories:
    • Generic changes (including all kinds of changes),
    • Changes applied to method signatures, and
    • Changes applied to the exceptions thrown by methods.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

 

  • System :         Pentium IV 2.4 GHz.
  • Hard Disk :         40 GB.
  • Floppy Drive : 44 Mb.
  • Monitor : 15 VGA Colour.
  • Mouse :
  • Ram : 512 Mb.
  • MOBILE : ANDROID

SOFTWARE REQUIREMENTS:

  • Operating system : Windows 7.
  • Coding Language : Java 1.7
  • Tool Kit : Android 2.3 ABOVE
  • IDE : Eclipse

REFERENCE:

Gabriele Bavota, Mario Linares-Vasquez, Member, IEEE, Carlos Eduardo Bernal-Cardenas, Massimiliano Di Penta, Rocco Oliveto, and Denys Poshyvanyk, Member, IEEE, “The Impact of API Change- and Fault-Proneness on the User Ratings of Android Apps”, IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, VOL. 41, NO. 4, APRIL 2015.

Smartphone-Based Wound Assessment System for Patients With Diabetes

Smartphone-Based Wound Assessment System for Patients With Diabetes

Smartphone-Based Wound Assessment System for Patients With Diabetes

ABSTRACT:

Diabetic foot ulcers represent a significant health issue. Currently, clinicians and nurses mainly base their wound assessment on visual examination of wound size and healing status, while the patients themselves seldom have an opportunity to play an active role. Hence, amore quantitative and cost-effective examination method that enables the patients and their caregivers to take a more active role in daily wound care potentially can accelerate wound healing, save travel cost and reduce healthcare expenses. Considering the prevalence of smartphones with a high-resolution digital camera, assessing wounds by analyzing images of chronic foot ulcers is an attractive option. In this paper, we propose a novel wound image analysis system implemented solely on the Android smartphone. The wound image is captured by the camera on the smartphone with the assistance of an image capture box. After that, the smartphone performs wound segmentation by applying the accelerated mean-shift algorithm. Specifically, the outline of the foot is determined based on skin color, and the wound boundary is found using a simple connected region detection method. Within the wound boundary, the healing status is next assessed based on red–yellow–black color evaluation model. Moreover, the healing status is quantitatively assessed, based on trend analysis of time records for a given patient. Experimental results on wound images collected in UMASS—Memorial Health Center Wound Clinic (Worcester, MA)following an Institutional Review Board approved protocol show that our system can be efficiently used to analyze the wound healing status with promising accuracy.

PROJECT OUTPUT VIDEO: (Click the below link to see the project output video):

EXISTING SYSTEM:

  • There are several problems with current practices for treating diabetic foot ulcers.
  • First, patients must go to their wound clinic on a regular basis to have their wounds checked by their clinicians. This need for frequent clinical evaluation is not only inconvenient and time consuming for patients and clinicians, but also represents a significant health care cost because patients may require special transportation, e.g., ambulances.
  • Second, a clinician’s wound assessment process is based on visual examination. He/she describes the wound by its physical dimensions and the color of its tissues, providing important indications of the wound type and the stage of healing. Because the visual assessment does not produce objective measurements and quantifiable parameters of the healing status, tracking a wound’s healing process across consecutive visits is a difficult task for both clinicians and patients.
  • The wound boundary determination was done with a particular implementation of the level set algorithm; specifically the distance regularized level set evolution The principal disadvantage of the level set algorithm is that the iteration of global level set function is too computationally intensive to be implemented on smart phones, even with the narrow band confined implementation based on GPUs.
  • In addition, the level set evolution completely depends on the initial curve which has to be pre-delineated either manually or by a well-designed algorithm. Finally, false edges may interfere with the evolution when the skin color is not uniform enough and when missing boundaries, as frequently occurring in medical images, results in evolution leakage (the level set evolution does not stop properly on the actual wound boundary). Hence, a better method was required to solve these problems.

DISADVANTAGES OF EXISTING SYSTEM:

  • Patient has to travel with foot ulcers to their clinics to report about the ulcers. This may increase the seriousness of the ulcers instead of curing it.
  • Patient travel exposure may cause a serious problem for them.

PROPOSED SYSTEM:

  • In this paper, we replaced the level set algorithms with the efficient mean-shift segmentation algorithm.
  • While it addresses the previous problems, it also creates additional challenges, such as over-segmentation, which we solved using the region adjacency graph (RAG)-based region merge algorithm.
  • In this paper, we present the entire process of recording and analyzing a wound image, using algorithms that are executable on a smart phone, and provide evidence of the efficiency and accuracy of these algorithms for analyzing diabetic foot ulcers.

ADVANTAGES OF PROPOSED SYSTEM:

  • Patient’s travel exposure is considerably reduced. Also it will reduce the patients stress.
  • Doctor can easily analyze the problem through images and its segmentation. So the proper report can be given to the patient on time

SYSTEM ARCHITECTURE:

smart

MODULES:

  1. Wound Image Analysis System overview.
  2. Mean-Shift-Based Segmentation Algorithm.
  3. Wound Boundary Determination and Analysis Algorithms.

MODULE DESCRIPTION:

Wound Image Analysis System overview:

In this module, we carry out a Wound boundary determination based on the foot outline detection result. If the foot detection result is regarded as a binary image with the foot area marked as “white” and rest part marked as “black,” it is easy to locate the wound  boundary within the foot region boundary by detecting the largest connected  black” component within the “white”  part. If the wound is located at the foot region boundary, then the foot boundary is not closed, and hence the problem becomes more complicated, i.e., we might need to first form a closed boundary. When the wound boundary has been successfully determined and the wound area calculated, we next evaluate the healing state of the wound by performing Color segmentation, with the goal of categorizing each pixel in the wound boundary into certain classes labeled as granulation, slough and necrosis. The classical self-organized clustering method called K-mean with high computational efficiency is used. After the color segmentation, a feature vector including the wound area size and dimensions for different types of wound tissues is formed to describe the wound quantitatively. This feature vector, along with both the original and analyzed images, is saved in the result database. The Wound healing trend analysis is performed on a time sequence of images belonging to a given patient to monitor the wound healing status. The current trend is obtained by comparing the wound feature vectors between the current wound record and the one that is just one standard time interval earlier (typically one or two weeks). Alternatively, a longer term healing trend is obtained by comparing the feature vectors between the current wound and the base record which is the earliest record for this patient.

Mean-Shift-Based Segmentation Algorithm:

In this module we implement mean-shift-based segmentation, the mean-shift algorithm belongs to the density estimation based nonparametric clustering methods, in which the feature space can be considered as the empirical probability density function of the represented parameter. This type of algorithms adequately analyzes the image feature space (color space, spatial space or the combination of the two spaces) to cluster and can provide a reliable solution for many vision tasks.

Wound Boundary Determination and Analysis Algorithms:

In this module we implement wound boundary determination, because the mean-shift algorithm only manages to segment the original image into homogeneous regions with similar color features, an object recognition method is needed to interpret the segmentation result into a meaningful wound boundary determination that can be easily understood by the users of the wound analysis system. As noted, a standard recognition method relies on known model information to develop a hypothesis, based on which a decision is made whether a region should be regarded as a candidate object, i.e., a wound. A verification step is also needed for further confirmation. Because our wound determination algorithm is designed for real time implementation on the smart phones with limited computational resources, we simplify the object recognition process while ensuring that recognition accuracy is acceptable.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

  • System :         Pentium IV 2.4 GHz.
  • Hard Disk :         40 GB.
  • Floppy Drive : 44 Mb.
  • Monitor : 15 VGA Colour.
  • Mouse :
  • Ram : 512 Mb.
  • MOBILE : ANDROID

SOFTWARE REQUIREMENTS:

  • Operating system : Windows 7.
  • Coding Language : Java 1.7
  • Tool Kit : Android 2.3 ABOVE
  • IDE : Eclipse

REFERENCE:

Lei Wang, Student Member, IEEE, Peder C. Pedersen, Senior Member, IEEE, Diane M. Strong, Bengisu Tulu, Member, IEEE, Emmanuel Agu, and Ronald Ignotz, “Smartphone-Based Wound Assessment System for Patients With Diabetes”, IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 62, NO. 2, FEBRUARY 2015.

Cooperative Positioning and Tracking in Disruption Tolerant Networks

Cooperative Positioning and Tracking in Disruption Tolerant Networks

Cooperative Positioning and Tracking in Disruption Tolerant Networks

ABSTRACT:

With the increasing number of location-dependent applications, positioning and tracking a mobile device becomes more and more important to enable pervasive and context-aware service. While extensive research has been performed in physical localization and logical localization for satellite, GSM and WiFi communication networks where fixed reference points are densely-deployed, positioning and tracking techniques in a sparse disruption tolerant network (DTN) have not been well addressed. In this paper, we propose a decentralized cooperative method called PulseCounting for DTN localization and a probabilistic tracking method called ProbTracking to confront this challenge. PulseCounting evaluates the user walking steps and movement orientations using accelerometer and electronic compass equipped in cellphones. It estimates user location by accumulating the walking segments, and improves the estimation accuracy by exploiting the encounters of mobile nodes. Several methods to refine the location estimation are discussed, which include the adjustment of trajectory based on reference points and the mutual refinement of location estimation for encountering nodes based on maximum-likelihood. To track user movement, the proposed ProbTracking method uses Markov chain to describe movement patterns and determines the most possible user walking trajectories without full record of user locations. We implemented the positioning and tracking system in Android phones and deployed a testbed in the campus of Nanjing University. Extensive experiments are conducted to evaluate the effectiveness and accuracy of the proposed methods, which show an average deviation of 9m in our system compared to GPS.

PROJECT OUTPUT VIDEO: (Click the below link to see the project output video):

EXISTING SYSTEM:

  • Several recent research focuses on GPS-free localization in wireless networks by incorporating fixed landmarks and surrounding characteristics.
  • Surround Sense identifies logical location using the surrounding information like sounds, lights and colors.
  • CompAcc adopts a distance estimation method using accelerometer and compass and determines location by matching to possible path signatures generated from an electronic map.
  • Escort provides a logical navigation system to help a person navigate to another person in a public place with the aid of context features.

DISADVANTAGES OF EXISTING SYSTEM:

  • Escort provides a logical navigation system for social localization. Its goal is not to identify the physical location, but to help a person navigate to another person in a public place such as a hotel. By periodically learning the walking trails of different individuals, as well as how they encounter each other in space-time, a route is computed between any pair of persons. However, it needs global information of users’ movements and their encounters to construct the navigation graph, which does not apply for DTNs.
  • These methods need continuous communication with a centralized server to process a large amount of surrounding data, which are not suitable for the decentralized structure and the opportunistic communication nature of DTNs.

PROPOSED SYSTEM:

  • In this paper, we propose a decentralized cooperative method called PulseCounting for DTN localization and a probabilistic method called ProbTracking to track the movement of mobile nodes.
  • PulseCounting evaluates the number of user walking steps using the accelerometer data, and decides the orientation of each step using the electronic compass measurements. By accumulating the segments of walking steps, it is able to form an estimation of current location.
  • PulseCounting further takes advantage of the opportunity of encounters in DTNs to refine the location estimation: on the one hand, the encountering APs and phones equipped with GPS could be regarded as reference points; on the other hand, the encounters of two mobile nodes enable the possibility of mutual adjustment to reduce estimation error.
  • ProbTracking detects the movement trajectory based on the partial location information reported by the other mobile nodes. It constructs a Markov chain using the movement his tory data and uses it to determine the most probable user walking route without the need for global location information in DTNs

ADVANTAGES OF PROPOSED SYSTEM:

  • It constructs a Markov chain using the movement history data and uses it to determine the most probable user walking route without the need for global location information in DTNs.
  • Accuracy of direction mapping

SYSTEM ARCHITECTURE:

coop

MODULES:

  1. Bootstrapping
  2. Step counting
  3. Direction mapping
  4. Trajectory generation
  5. Location estimation

MODULES DESCRIPTION:

Bootstrapping:

As the first step, each node needs to know its position initially. Without the initial position, there is no reference point for location estimation. In DTNs, we assume a small number of fixed landmarks (e.g., wireless APs) are deployed in the environment with known locations. We also assume that there are a few GPS-nodes willing to report their locations to other nodes. Thus the common-nodes can obtain a rough initial location when they firstly encounter the land-marks or GPS-nodes. It is unlikely for all common-nodes to obtain their initial locations at the same time, so the initialization process is asynchronous. With the initial location information, a map in this area will be downloaded to the user’s cellphone. We use the Google Map in our implementation since it provides open access to its data and APIs. The map is downloaded opportunistically when the device has a chance to access the Internet (i.e., entering the communication range of an AP).

Step counting:

We introduce the method of using the accelerometer to measure walking steps. The accelerometer records user movement in three dimensions: X (the direction of front and back), Y (the direction of left and right), and Z (the direction of up and down). As we plot the accelerometer data of users with the cellphone putting in three different positions: holding horizontally in hand, sticking vertically in front pocket, and sticking vertically in back pocket. Observation reveals several characteristics: (1) The acceleration is non-uniform. It shows a pattern of “increase-decrease” and fluctuates around some value. (2) The data is noisy. It is influenced by the way people walks and the position of their cellphones. (3) It has obvious periodicity and its shape looks like a wave. The periodical phenomenon is most clear in the direction of Z axis (up and down) of all cellphone positions. During movement, the human’s center of gravity goes up and down, which causes the increasing and decreasing of his accelerations. Thus a period in the accelerometer reading corresponds to two walking steps in reality.

Direction mapping:

The other important aspect of movement is direction, which can be measured by electronic compass. The cellphone compass records the users orientation in the form of an angle with respect to magnetic north. Similar to the accelerometer data, the compass data is densely sampled (about 22 data per seconds) and appears fluctuating and noisy, thus it cannot be used directly. We proposed the direction mapping method to make the compass data discrete. For a rough estimation, we project the compass data to eight discrete directions: North, Northeast, East, Southeast, South, Southwest, West, and Northwest, which are numbered by 0-7 accordingly.

Trajectory generation:

With the results from step counting and direction mapping, we are able to describe user movement trajectories. A movement trajectory is defined as a series of segments with distance and direction. Each tuple < Si, θi >(i = 1, 2,… ,M ) indicates a segment of the movement. Si is the moving distance of two consecutive walking steps (one period of the acceleration); θi is the movement direction (measured by the angle to the north) in the steps, which is obtained by the direction mapping method. M is the total number of segments.

Location estimation:

Given a trajectory T (P0 P1), if the location of departure point P0 is known, we can roughly estimate the location of P1 by accumulating the trajectory segments. However, due to the inaccuracy of step size and orientation measurement, errors may be introduced during the estimation of each segment. With the number of segments increase, the errors are accumulated, thus the estimated location will be far away from the actual location. To overcome this drawback, we use the encounter opportunity of nodes to improve the estimation accuracy, which is introduced in the following subsection.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

 

  • System :         Pentium IV 2.4 GHz.
  • Hard Disk :         40 GB.
  • Floppy Drive : 44 Mb.
  • Monitor : 15 VGA Colour.
  • Mouse :
  • Ram : 512 Mb.
  • MOBILE : ANDROID

SOFTWARE REQUIREMENTS:

  • Operating system : Windows XP/7.
  • Coding Language : Java 1.7
  • Tool Kit : Android 2.3 ABOVE
  • IDE : Eclipse

REFERENCE:

Wenzhong Li, Member, IEEE, Yuefei Hu, Student Member, IEEE, Xiaoming Fu, Senior Member, IEEE, Sanglu Lu, Member, IEEE, and Daoxu Chen, Member, IEEE, “Cooperative Positioning and Tracking in Disruption Tolerant Networks,”. IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 26, NO. 2, FEBRUARY 2015

Context-Based Access Control Systems for Mobile Devices

Context-Based Access Control Systems for Mobile Devices

Context-Based Access Control Systems for Mobile Devices

ABSTRACT:

Mobile Android applications often have access to sensitive data and resources on the user device. Misuse of this data by malicious applications may result in privacy breaches and sensitive data leakage. An example would be a malicious application surreptitiously recording a confidential business conversation. The problem arises from the fact that Android users do not have control over the application capabilities once the applications have been granted the requested privileges upon installation. In many cases, however, whether an application may get a privilege depends on the specific user context and thus we need a context-based access control mechanism by which privileges can be dynamically granted or revoked to applications based on the specific context of the user. In this paper we propose such an access control mechanism. Our implementation of context differentiates between closely located sub-areas within the same location. We have modified the Android operating system so that context-based access control restrictions can be specified and enforced. We have performed several experiments to assess the efficiency of our access control mechanism and the accuracy of context detection.

PROJECT OUTPUT VIDEO: (Click the below link to see the project output video):

EXISTING SYSTEM:

Security for mobile operating systems focuses on restricting applications from accessing sensitive data and resources, but mostly lacks efficient techniques for enforcing those restrictions according to fine-grained contexts that differentiate between closely located subareas. Moreover, most of this work has focused on developing policy systems that do not restrict privileges per application and are only effective system-wide. So User disable all applications from using the camera and any device resources and privileges that employers restrict while at work, while the user device can retain all its original privileges outside the work area.

DISADVANTAGES OF EXISTING SYSTEM:

  • Do not cover all the possible ways in which applications can access user data and device resources.
  • The User leakage of Their privacy.
  • Existing location-based policy systems are not accurate enough to differentiate between nearby locations without extra hardware or location devices.

PROPOSED SYSTEM:

  • In this paper, we propose a context-based access control (CBAC) mechanism for Android systems that allows smartphone users to set configuration policies over their applications’ usage of device resources and services at different contexts.
  • Through the CBAC mechanism, users can, for example, set restricted privileges for device applications when using the device at work, and device applications may re-gain their original privileges when the device is used at home. This change in device privileges is automatically applied as soon as the user device matches a pre-defined context of a user-defined policy.
  • The user can also specify a default set of policies to be applied when the user is located in a non-previously defined location. Configured policy restrictions are defined according to the accessible device resources, services, and permissions that are granted to applications at installation time. Such policies define which services are offered by the device and limit the device and user information accessibility. Policy restrictions are linked to context and are configured by the device user. We define context according to location and time.

ADVANTAGES OF PROPOSED SYSTEM:

  • Applications should not be able to fake the location or time of the device.
  • Can develop securer and more acceptable applications for end users.

SYSTEM ARCHITECTURE:

Capture

MODULES:

  • Context Provider
  • Access Controller
  • Policy Manager
  • Policy Executor

MODULES DESCRIPTION:

Context Provider

The Context Provider (CP) collects the physical location parameters (GPS, Cell IDs, Wi-Fi parameters) through the device sensors and stores them in its own database, linking each physical location to a user-defined logical location. It also verifies and updates those parameters whenever the device is re-located.

Access Controller

The Access Controller (AC) controls the authorizations of applications and prevents unauthorized usage of device resources or services. Even though the Android OS has its own permission control system that checks if an application has privileges to request resources or services, the AC complements this system with more control methods and specific fine-grained control permissions that better reflect the application capabilities and narrow down its accessibility to resources. The AC enhances the security of the device system since the existing Android system has some permissions that, once granted to applications, may give applications more accessibility than they need, which malicious code can take advantage of.

Policy Manager

The Policy Manager (PM) represents the interface used to create policies, mainly assigning application restrictions to contexts. It mainly gives control to the user to configure which resources and services are accessible by applications at the given context provided by the CP. As an example, the user through the PM can create a policy to enable location services only when the user is at work during weekdays between 8 am and 5 pm.

Policy Executor

The Policy Executor (PE) enforces device restrictions by comparing the device’s context with the configured policies. Once an application requests access to a resource or service, the PE checks the user-configured restrictions set at the PM to either grant to deny access to the application request. The PE acts as a policy enforcement by sending the authorization information to the AC to handle application requests, and is also responsible to resolve policy conflicts and apply the most strict restrictions.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

  • System :         Pentium IV 2.4 GHz.
  • Hard Disk :         40 GB.
  • Floppy Drive : 44 Mb.
  • Monitor : 15 VGA Colour.
  • Mouse :
  • Ram : 512 Mb.
  • MOBILE : ANDROID

SOFTWARE REQUIREMENTS

  • Operating system : Windows XP/7.
  • Coding Language : Java 1.7
  • Tool Kit : Android 2.3 ABOVE
  • IDE : Eclipse

REFERENCE:

Bilal Shebaro, Oyindamola Oluwatimi, Elisa Bertino, “Context-based Access Control Systems for Mobile Devices”, IEEE Transactions on Dependable and Secure Computing, VOL. 12, NO. 2, MARCH/APRIL 2015

Secure Data Aggregation Technique for Wireless Sensor Networks in the Presence of Collusion Attacks

Secure Data Aggregation Technique for Wireless Sensor Networks in the Presence of Collusion Attacks

ABSTRACT:

Due to limited computational power and energy resources, aggregation of data from multiple sensor nodes done at the aggregating node is usually accomplished by simple methods such as averaging. However such aggregation is known to be highly vulnerable to node compromising attacks. Since WSN are usually unattended and without tamper resistant hardware, they are highly susceptible to such attacks. Thus, ascertaining trustworthiness of data and reputation of sensor nodes is crucial for WSN. As the performance of very low power processors dramatically improves, future aggregator nodes will be capable of performing more sophisticated data aggregation algorithms, thus making WSN less vulnerable. Iterative filtering algorithms hold great promise for such a purpose. Such algorithms simultaneously aggregate data from multiple sources and provide trust assessment of these sources, usually in a form of corresponding weight factors assigned to data provided by each source. In this paper we demonstrate that several existing iterative filtering algorithms, while significantly more robust against collusion attacks than the simple averaging methods, are nevertheless susceptive to a novel sophisticated collusion attack we introduce. To address this security issue, we propose an improvement for iterative filtering techniques by providing an initial approximation for such algorithms which makes them not only collusion robust, but also more accurate and faster converging.

PROJECT OUTPUT VIDEO: (Click the below link to see the project output video):

EXISTING SYSTEM:

  • In recent years, there has been an increasing amount of literature on IF algorithms for trust and reputation systems. The performance of IF algorithms in the presence of different types of faults and simple false data injection attacks has been studied where it was applied to compressive sensing data in WSNs.
  • In the past literature it was found that these algorithms exhibit better robustness compared to the simple averaging techniques; however, the past research did not take into account more sophisticated collusion attack scenarios. If the attackers have a high level of knowledge about the aggregation algorithm and its parameters, they can conduct sophisticated attacks on WSNs by exploiting false data injection through a number of compromised nodes.

DISADVANTAGES OF EXISTING SYSTEM:

  • Although the existing IF algorithms consider simple cheating behaviour by adversaries, none of them take into account sophisticated malicious scenarios such as collusion attacks.
  • Although the existing IF algorithms consider simple cheating behaviour by adversaries, none of them take into account sophisticated malicious scenarios such as collusion attacks.

PROPOSED SYSTEM:

  • This paper presents a new sophisticated collusion attack scenario against a number of existing IF algorithms based on the false data injection. In such an attack scenario, colluders attempt to skew the aggregate value by forcing such IF algorithms to converge to skewed values provided by one of the attackers.
  • In this paper, we propose a solution for vulnerability by providing an initial trust estimate which is based on a robust estimation of errors of individual sensors.
  • Identification of a new sophisticated collusion attack against IF based reputation systems which reveals a severe vulnerability of IF algorithms.
  • A novel method for estimation of sensors’ errors which is effective in a wide range of sensor faults and not susceptible to the described attack.
  • Design of an efficient and robust aggregation method inspired by the MLE, which utilises an estimate of the noise parameters obtained using contribution above.
  • Enhanced IF schemes able to protect against sophisticated collusion attacks by providing an initial estimate of trustworthiness of sensors using inputs from contributions

ADVANTAGES OF PROPOSED SYSTEM:

  • We provide a thorough empirical evaluation of effectiveness and efficiency of our proposed aggregation method. The results show that our method provides both higher accuracy and better collusion resistance than the existing methods.
  • To the best of our knowledge, no existing work addresses on false data injection for a number of simple attack scenarios, in the case of a collusion attack by compromised nodes in a manner which employs high level knowledge about data aggregation algorithm used.

SYSTEM ARCHITECTURE:

BLOCK DIAGRAM:

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

  • System :         Pentium IV 2.4 GHz.
  • Hard Disk :         40 GB.
  • Floppy Drive : 44 Mb.
  • Monitor : 15 VGA Colour.
  • Mouse :
  • Ram : 512 Mb.

SOFTWARE REQUIREMENTS:

  • Operating system : Windows XP/7/LINUX.
  • Implementation : NS2
  • NS2 Version : 2.28
  • Front End : OTCL (Object Oriented Tool Command Language)
  • Tool : Cygwin (To simulate in Windows OS)

REFERENCE:

Mohsen Rezvani, Student Member, IEEE, Aleksandar Ignjatovic, Elisa Bertino, Fellow, IEEE, and Sanjay Jha, Senior Member, IEEE, “Secure Data Aggregation Technique for Wireless Sensor Networks in the Presence of Collusion Attacks”, IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, VOL. 12, NO. 1, JANUARY/FEBRUARY 2015

Time-Delayed Broadcasting for Defeating Inside Jammers

Time-Delayed Broadcasting for Defeating Inside Jammers

ABSTRACT:

We address the problem of jamming-resistant broadcast communications under an internal threat model. We propose a time-delayed broadcast scheme (TDBS), which implements the broadcast operation as a series of unicast transmissions distributed in frequency and time. TDBS does not rely on commonly shared secrets, or the existence of jamming-immune control channels for coordinating broadcasts. Instead, each node follows a unique pseudo-noise (PN) frequency hopping sequence. Contrary to conventional PN sequences designed for multi-access systems, the PN sequences in TDBS exhibit correlation to enable broadcast. Moreover, they are designed to limit the information leakage due to the exposure of a subset of sequences by compromised nodes. We map the problem of constructing such PN sequences to the 1-factorization problem for complete graphs. We further accommodate dynamic broadcast groups by mapping the problem of updating the assigned PN sequences to the problem of constructing rainbow paths in proper edge-colored graphs.

PROJECT OUTPUT VIDEO: (Click the below link to see the project output video):

EXISTING SYSTEM:

  • Several researchers have studied the broadcasting problem in the presence of inside jammers. Methods eliminate the dependency of SS on shared secrets.
  • Baird et al. proposed the encoding of “indelible marks” at specific locations within each broadcasted message. Assuming that the jammer cannot flip a bit ‘1’ to a bit ‘0’, it was shown that a jammer cannot erase packets from the wireless channel.
  • Popper et al. proposed a method called Uncoordinated DSSS (UDSSS), in which broadcast transmissions are spread according to a PN code, randomly selected from a public codebook. Receivers decode transmitted messages by exhaustively applying every PN code in the public codebook.

DISADVANTAGES OF EXISTING SYSTEM:

  • Dependency on shared secrets
  • In most PHY-layer standards, frame detection is based on the signal cross-correlation between the received signal and the known preamble and does not require preamble decoding.

PROPOSED SYSTEM:

  • We propose the Time-Delayed Broadcast Scheme (TDBS) as an emergency mechanism for temporarily restoring broadcast communications until inside jammers are physically removed from the network. TDBS differs from classical FHSS designs in that two communicating nodes do not follow the same FH sequence, but are assigned unique ones. Unlike the typical broadcast in which all receivers tune to the same channel, TDBS propagates broadcast messages as a series of unicast transmissions, spread both in frequency and time.
  • To ensure resilience to inside jammers, the locations of these unicast transmissions, defined by a frequency band/slot pair, are only partially known to any subset of receivers. Assuming that the jammer can only interfere with a limited number of frequency bands, a subset of the unicast transmissions are interference-free, thus propagating broadcast messages.

ADVANTAGES OF PROPOSED SYSTEM:

  • Prevents the sender(s) from communicating with all, or a subset of the intended receivers.
  • We mapped the problem of minimizing the number of FH sequence changes required for node addition, to the problem of finding rainbow paths in proper edge-colored complete graphs.

SYSTEM ARCHITECTURE:

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

  • System :         Pentium IV 2.4 GHz.
  • Hard Disk :         40 GB.
  • Floppy Drive : 44 Mb.
  • Monitor : 15 VGA Colour.
  • Mouse :
  • Ram : 512 Mb.

SOFTWARE REQUIREMENTS:

  • Operating system : Windows XP/7/LINUX.
  • Implementation : NS2
  • NS2 Version : 2.28
  • Front End : OTCL (Object Oriented Tool Command Language)
  • Tool : Cygwin (To simulate in Windows OS)

REFERENCE:

Sisi Liu, Loukas Lazos, Member, IEEE, and Marwan Krunz, Fellow, IEEE, “Time-Delayed Broadcasting for Defeating Inside Jammer”, IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, VOL. 12, NO. 3, MAY/JUNE 2015.