A computational dynamic trust model for user authorizationKamal Spring
Development of authorization mechanisms for secure information access by a large community of users in an open environment is an important problem in the ever-growing Internet world. In this paper we propose a computational dynamic trust model for user authorization, rooted in findings from social science. Unlike most existing computational trust models, this model distinguishes trusting belief in integrity from that in competence in different contexts and accounts for subjectivity in the evaluation of a particular trustee by different trusters. Simulation studies were conducted to compare the performance of the proposed integrity belief model with other trust models from the literature for different user behavior patterns. Experiments show that the proposed model achieves higher performance than other models especially in predicting the behavior of unstable users.
RISK ASSESSMENT ALGORITHM IN WIRELESS SENSOR NETWORKS USING BETA DISTRIBUTIONIJCNCJournal
This paper introduces the Beta distribution as a novel technique to weight direct and indirect trust and
assessing the risk in wireless sensor networks. This paper also reviews the trust factors, which play a major
role in building trust in wireless sensor networks and explains the dynamic aspects of trust. This is an
extension of a previous work done by the authors using a new approach to assess risk. Simulation results
related to the previous work and to the new approach introduced in this paper are also presented for easy
comparison
An exaustive survey of trust models in p2 p networkijwscjournal
Most of the peers accessing the services are under the assumption that the service accessed in a P2P
network is utmost secured. By means of prevailing hard security mechanisms, security goals like
authentication, authorization, privacy, non repudiation of services and other hard security issues are
resolved. But these mechanisms fail to provide soft security. An exhaustive survey of existing trust and
reputation models in P2P network regarding service provisioning is presented and challenges are listed.
Trust issues like trust bootstrapping, trust evidence procurement, trust assessment, trust interaction
outcome evaluation and other trust based classification of peer’s behavior into trusted,, inconsistent, un
trusted, malicious, betraying, redemptive are discussed,
NS2 Projects for M. Tech, NS2 Projects in Vijayanagar, NS2 Projects in Bangalore, M. Tech Projects in Vijayanagar, M. Tech Projects in Bangalore, NS2 IEEE projects in Bangalore, IEEE 2015 NS2 Projects, WSN and MANET Projects, WSN and MANET Projects in Bangalore, WSN and MANET Projects in Vijayangar
TRUST METRICS IN RECOMMENDER SYSTEMS: A SURVEYaciijournal
Information overload is a new challenge in e-commerce sites. The problem refers to the fast growing of
information that lead following the information flow in real world be impossible. Recommender systems, as
the most successful application of information filtering, help users to find items of their interest from huge
datasets. Collaborative filtering, as the most successful technique for recommendation, utilises social
behaviours of users to detect their interests. Traditional challenges of Collaborative filtering, such as cold
start, sparcity problem, accuracy and malicious attacks, derived researchers to use new metadata to
improve accuracy of recommenders and solve the traditional problems. Trust based recommender systems
focus on trustworthy value on relation among users to make more reliable and accurate recommends. In
this paper our focus is on trust based approach and discuss about the process of making recommendation
in these method. Furthermore, we review different proposed trust metrics, as the most important step in this
process.
A computational dynamic trust model for user authorizationKamal Spring
Development of authorization mechanisms for secure information access by a large community of users in an open environment is an important problem in the ever-growing Internet world. In this paper we propose a computational dynamic trust model for user authorization, rooted in findings from social science. Unlike most existing computational trust models, this model distinguishes trusting belief in integrity from that in competence in different contexts and accounts for subjectivity in the evaluation of a particular trustee by different trusters. Simulation studies were conducted to compare the performance of the proposed integrity belief model with other trust models from the literature for different user behavior patterns. Experiments show that the proposed model achieves higher performance than other models especially in predicting the behavior of unstable users.
RISK ASSESSMENT ALGORITHM IN WIRELESS SENSOR NETWORKS USING BETA DISTRIBUTIONIJCNCJournal
This paper introduces the Beta distribution as a novel technique to weight direct and indirect trust and
assessing the risk in wireless sensor networks. This paper also reviews the trust factors, which play a major
role in building trust in wireless sensor networks and explains the dynamic aspects of trust. This is an
extension of a previous work done by the authors using a new approach to assess risk. Simulation results
related to the previous work and to the new approach introduced in this paper are also presented for easy
comparison
An exaustive survey of trust models in p2 p networkijwscjournal
Most of the peers accessing the services are under the assumption that the service accessed in a P2P
network is utmost secured. By means of prevailing hard security mechanisms, security goals like
authentication, authorization, privacy, non repudiation of services and other hard security issues are
resolved. But these mechanisms fail to provide soft security. An exhaustive survey of existing trust and
reputation models in P2P network regarding service provisioning is presented and challenges are listed.
Trust issues like trust bootstrapping, trust evidence procurement, trust assessment, trust interaction
outcome evaluation and other trust based classification of peer’s behavior into trusted,, inconsistent, un
trusted, malicious, betraying, redemptive are discussed,
NS2 Projects for M. Tech, NS2 Projects in Vijayanagar, NS2 Projects in Bangalore, M. Tech Projects in Vijayanagar, M. Tech Projects in Bangalore, NS2 IEEE projects in Bangalore, IEEE 2015 NS2 Projects, WSN and MANET Projects, WSN and MANET Projects in Bangalore, WSN and MANET Projects in Vijayangar
TRUST METRICS IN RECOMMENDER SYSTEMS: A SURVEYaciijournal
Information overload is a new challenge in e-commerce sites. The problem refers to the fast growing of
information that lead following the information flow in real world be impossible. Recommender systems, as
the most successful application of information filtering, help users to find items of their interest from huge
datasets. Collaborative filtering, as the most successful technique for recommendation, utilises social
behaviours of users to detect their interests. Traditional challenges of Collaborative filtering, such as cold
start, sparcity problem, accuracy and malicious attacks, derived researchers to use new metadata to
improve accuracy of recommenders and solve the traditional problems. Trust based recommender systems
focus on trustworthy value on relation among users to make more reliable and accurate recommends. In
this paper our focus is on trust based approach and discuss about the process of making recommendation
in these method. Furthermore, we review different proposed trust metrics, as the most important step in this
process.
AN INDEPENDENT TRUST MODEL FOR MANET BASED ON FUZZY LOGIC RULESIAEME Publication
A mobile ad hoc network (MANET) is a self-organized system comprised by multiple mobile wireless nodes. Due to the openness in network topology and the absence of centralized administration in management, MANET is vulnerable to attacks from malicious nodes. In order to reduce the hazards from these malicious nodes, we incorporate the concept of trust into the MANET, and build a subjective trust management model with multiple decision factors based on the analytic hierarchy process (AHP) theory and the fuzzy logic rules prediction method ˉ AFStrust. We consider multiple decision factors, including direct trust, recommendation trust, incentive function and active degree, in our model to reflect trust relationship’s complexity and uncertainty from various aspects. It overcomes the shortage of traditional method, where the decision factors are incomplete. Moreover, the weight of classification is set up by AHP for these decision factors, which makes the model has a better rationality and a higher practicability. Compared to the existing trust management models, comprehensive experiments have been conducted to evaluate the efficiency of our trust management model in the improvement of network interaction quality, trust dynamic adaptability, malicious node identification, attack resistance and enhancements of system’s security
The reliability of delivering packets through multi-hop intermediate nodes is a significant issue in the mobile ad hoc networks (MANETs). The distributed mobile nodes establish connections to form the MANET, which may include selfish and misbehaving nodes. Recommendation based trust management has been proposed in the literature as a mechanism to filter out the misbehaving nodes while searching for a packet delivery route. However, building a trust model that relies on the recommendations from other nodes in the network is vulnerable to the possible dishonest behaviour, such as bad-mouthing, ballot-stuffing, and collusion, of the recommending nodes. This paper investigates the problems of attacks posed by misbehaving nodes while propagating recommendations in the existing trust models. We propose a recommendation-based trust model with a defence scheme that utilises clustering technique to dynamically filter attacks related to dishonest recommendations within certain time based on number of interactions, compatibility of information and node closeness. The model is empirically tested in several mobile and disconnected topologies in which nodes experience changes in their neighbourhoods and consequently face frequent route changes. The empirical analysis demonstrates robustness and accuracy of the trust model in a dynamic MANET environment
Modelling of A Trust and Reputation Model in Wireless Networksijeei-iaes
Security is the major challenge for Wireless Sensor Networks (WSNs). The sensor nodes are deployed in non controlled environment, facing the danger of information leakage, adversary attacks and other threats. Trust and Reputation models are solutions for this problem and to identify malicious, selfish and compromised nodes. This paper aims to evaluate varying collusion effect with respect to static (SW), dynamic (DW), static with collusion (SWC), dynamic with collusion (DWC) and oscillating wireless sensor networks to derive the joint resultant of Eigen Trust Model. An attempt has been made for the same by comparing aforementioned networks that are purely dedicated to protect the WSNs from adversary attacks and maintain the security issues. The comparison has been made with respect to accuracy and path length and founded that, collusion for wireless sensor networks seems intractable with the static and dynamic WSNs when varied with specified number of fraudulent nodes in the scenario. Additionally, it consumes more energy and resources in oscillating and collusive environments.
Towards Purposeful Reuse of Semantic Datasets Through Goal-Driven SummarizationPanos Alexopoulos
The emergence in the last years of initiatives like the Linked Open Data (LOD) has led to a significant increase of the amount of structured semantic data on the Web. Nevertheless, the wider reuse of such public semantic data is inhibited by the difficulty for users to decide whether a given dataset is actually suitable for their needs. This is because semantic datasets typically cover diverse domains, do not follow a unified way of organizing the knowledge and may differ in a number of dimensions. With that in mind, in this paper, we report our work in progress on a goal-driven dataset summarization approach that may facilitate better understanding and reuse-oriented evaluation of available semantic data.
SelCSP: A Framework to Facilitate Selection of Cloud Service Providers1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Research Inventy : International Journal of Engineering and Scienceinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
PROBABILISTIC CREDIT SCORING FOR COHORTS OF BORROWERSAndresz26
Este Working Paper relata sobre el nivel del riesgo crediticio, se debe reconocer que el riesgo de un grupo proviene de la diversidad de sus miembros, este libro propone una metodología para la aplicación de la medición del riesgo crediticio, y permite hacer un ranking de la población por su nivel de riesgo. La misma que realiza una distinción en los diferentes rankings de la población por su nivel de riesgo, y considerando en el ranking los riesgos de sus preferencias en sus decisiones realizadas.
http://www.udla.edu.ec/
Trust Management for Secure Routing Forwarding Data Using Delay Tolerant Netw...rahulmonikasharma
Delay Tolerant Networks (DTNs) have established the connection to source and destination. For example this often faces disconnection and unreliable wireless connections. A delay tolerant network (DTNs) provides a network imposes disruption or delay. The delay tolerant networks operate in limited resources such as memory size, central processing unit. Trust management protocol uses a dynamic threshold updating which overcomes the problems .The dynamic threshold update reduces the false detection probability of the malicious nodes. The system proposes a secure routing management schemes to adopt information security principles successfully. It analyzes the basic security principles and operations for trust authentication which is applicable in delay tolerant networks (DTNs).For security the proposed system identifies the store and forward approach in network communications and analyzes the routing in cases like selfish contact and collaboration contact methods. The proposed method identifies ZRP protocol scheme and it enhances the scheme using methods namely distributed operation, mobility, delay analysis, security association and trust modules. This security scheme analyzes the performance analysis and proposed algorithm based on parameter time, authentication, security, and secure routing. From this analysis, this research work identifies the issues in DTNs secure routing and enhances ZRP (Zone Routing Protocol) by suggesting an authentication principle as a noted security principle for extremely information security concepts.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
A Computational Dynamic Trust Model for User Authorization1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
AN EXAUSTIVE SURVEY OF TRUST MODELS IN P2P NETWORKijwscjournal
Most of the peers accessing the services are under the assumption that the service accessed in a P2P network is utmost secured. By means of prevailing hard security mechanisms, security goals like authentication, authorization, privacy, non repudiation of services and other hard security issues are resolved. But these mechanisms fail to provide soft security. An exhaustive survey of existing trust and reputation models in P2P network regarding service provisioning is presented and challenges are listed. Trust issues like trust bootstrapping, trust evidence procurement, trust assessment, trust interaction outcome evaluation and other trust based classification of peer’s behavior into trusted,, inconsistent, un
trusted, malicious, betraying, redemptive are discussed,
AN EXAUSTIVE SURVEY OF TRUST MODELS IN P2P NETWORKijwscjournal
ABSTRACT
Most of the peers accessing the services are under the assumption that the service accessed in a P2P
network is utmost secured. By means of prevailing hard security mechanisms, security goals like
authentication, authorization, privacy, non repudiation of services and other hard security issues are
resolved. But these mechanisms fail to provide soft security. An exhaustive survey of existing trust and
reputation models in P2P network regarding service provisioning is presented and challenges are listed.
Trust issues like trust bootstrapping, trust evidence procurement, trust assessment, trust interaction
outcome evaluation and other trust based classification of peer’s behavior into trusted,, inconsistent, un
trusted, malicious, betraying, redemptive are discussed,
Developing a trust model using graph and ranking trust of social messaging s...IJECEIAES
Trust is an important issue in social interactions, especially in using cyberspace services. In this paper, a trust and evaluation model are proposed based on which the government can provide reliable services to users. The model is a distributed and hierarchical model. First, the number 12 trust criteria and the weight of these criteria were extracted using the analytical hierarchy process (AHP) and analytic network process (ANP) techniques. Second, to obtain the trust in the service examined, for each criterion, a graph of trusted entities is proposed. Then, a weighted graph with the number of trusted entities called trust pathways measure will be obtained. To test the model, the effect of the 12 criteria on three important evaluation factors over seven widely used social services was rated by three experts. The trust of each service was obtained, which was satisfactory as compared to a valid organizational evaluation. Finally, the correlation coefficient of this comparison was 70.37%, indicating that the results from this model were appropriate.
TUX-TMS: Thapar University Extensible-Trust Management SystemCSCJournals
In a Grid Computing scenario, where the market players are dynamic; traditional assumptions for establishing and evaluating trust, do not hold good anymore. There are two different methods for handling access controls to the resources either by using policy based approach where logical rules and verifiable properties are encoded in signed credentials or using reputation based approach where trust values are collected, aggregated and evaluated to disseminate reputation among the market players. There is need for a dynamic and flexible general-purpose trust management system. In this paper TUX-TMS: an extensible reputation based Trust Management System is presented for establishing and evaluating trust in grid systems. TUX is an efficient Reputation based trust management system for establishing secure Grids.
PURGING OF UNTRUSTWORTHY RECOMMENDATIONS FROM A GRIDijngnjournal
In grid computing, trust has massive significance. There is lot of research to propose various models in providing trusted resource sharing mechanisms. The trust is a belief or perception that various researchers have tried to correlate with some computational model. Trust on any entity can be direct or indirect. Direct trust is the impact of either first impression over the entity or acquired during some direct interaction. Indirect trust is the trust may be due to either reputation gained or recommendations received from various recommenders of a particular domain in a grid or any other domain outside that grid or outside that grid itself. Unfortunately, malicious indirect trust leads to the misuse of valuable resources of the grid. This paper proposes the mechanism of identifying and purging the untrustworthy recommendations in the grid environment. Through the obtained results, we show the way of purging of untrustworthy entities.
AN INDEPENDENT TRUST MODEL FOR MANET BASED ON FUZZY LOGIC RULESIAEME Publication
A mobile ad hoc network (MANET) is a self-organized system comprised by multiple mobile wireless nodes. Due to the openness in network topology and the absence of centralized administration in management, MANET is vulnerable to attacks from malicious nodes. In order to reduce the hazards from these malicious nodes, we incorporate the concept of trust into the MANET, and build a subjective trust management model with multiple decision factors based on the analytic hierarchy process (AHP) theory and the fuzzy logic rules prediction method ˉ AFStrust. We consider multiple decision factors, including direct trust, recommendation trust, incentive function and active degree, in our model to reflect trust relationship’s complexity and uncertainty from various aspects. It overcomes the shortage of traditional method, where the decision factors are incomplete. Moreover, the weight of classification is set up by AHP for these decision factors, which makes the model has a better rationality and a higher practicability. Compared to the existing trust management models, comprehensive experiments have been conducted to evaluate the efficiency of our trust management model in the improvement of network interaction quality, trust dynamic adaptability, malicious node identification, attack resistance and enhancements of system’s security
The reliability of delivering packets through multi-hop intermediate nodes is a significant issue in the mobile ad hoc networks (MANETs). The distributed mobile nodes establish connections to form the MANET, which may include selfish and misbehaving nodes. Recommendation based trust management has been proposed in the literature as a mechanism to filter out the misbehaving nodes while searching for a packet delivery route. However, building a trust model that relies on the recommendations from other nodes in the network is vulnerable to the possible dishonest behaviour, such as bad-mouthing, ballot-stuffing, and collusion, of the recommending nodes. This paper investigates the problems of attacks posed by misbehaving nodes while propagating recommendations in the existing trust models. We propose a recommendation-based trust model with a defence scheme that utilises clustering technique to dynamically filter attacks related to dishonest recommendations within certain time based on number of interactions, compatibility of information and node closeness. The model is empirically tested in several mobile and disconnected topologies in which nodes experience changes in their neighbourhoods and consequently face frequent route changes. The empirical analysis demonstrates robustness and accuracy of the trust model in a dynamic MANET environment
Modelling of A Trust and Reputation Model in Wireless Networksijeei-iaes
Security is the major challenge for Wireless Sensor Networks (WSNs). The sensor nodes are deployed in non controlled environment, facing the danger of information leakage, adversary attacks and other threats. Trust and Reputation models are solutions for this problem and to identify malicious, selfish and compromised nodes. This paper aims to evaluate varying collusion effect with respect to static (SW), dynamic (DW), static with collusion (SWC), dynamic with collusion (DWC) and oscillating wireless sensor networks to derive the joint resultant of Eigen Trust Model. An attempt has been made for the same by comparing aforementioned networks that are purely dedicated to protect the WSNs from adversary attacks and maintain the security issues. The comparison has been made with respect to accuracy and path length and founded that, collusion for wireless sensor networks seems intractable with the static and dynamic WSNs when varied with specified number of fraudulent nodes in the scenario. Additionally, it consumes more energy and resources in oscillating and collusive environments.
Towards Purposeful Reuse of Semantic Datasets Through Goal-Driven SummarizationPanos Alexopoulos
The emergence in the last years of initiatives like the Linked Open Data (LOD) has led to a significant increase of the amount of structured semantic data on the Web. Nevertheless, the wider reuse of such public semantic data is inhibited by the difficulty for users to decide whether a given dataset is actually suitable for their needs. This is because semantic datasets typically cover diverse domains, do not follow a unified way of organizing the knowledge and may differ in a number of dimensions. With that in mind, in this paper, we report our work in progress on a goal-driven dataset summarization approach that may facilitate better understanding and reuse-oriented evaluation of available semantic data.
SelCSP: A Framework to Facilitate Selection of Cloud Service Providers1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
Research Inventy : International Journal of Engineering and Scienceinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
PROBABILISTIC CREDIT SCORING FOR COHORTS OF BORROWERSAndresz26
Este Working Paper relata sobre el nivel del riesgo crediticio, se debe reconocer que el riesgo de un grupo proviene de la diversidad de sus miembros, este libro propone una metodología para la aplicación de la medición del riesgo crediticio, y permite hacer un ranking de la población por su nivel de riesgo. La misma que realiza una distinción en los diferentes rankings de la población por su nivel de riesgo, y considerando en el ranking los riesgos de sus preferencias en sus decisiones realizadas.
http://www.udla.edu.ec/
Trust Management for Secure Routing Forwarding Data Using Delay Tolerant Netw...rahulmonikasharma
Delay Tolerant Networks (DTNs) have established the connection to source and destination. For example this often faces disconnection and unreliable wireless connections. A delay tolerant network (DTNs) provides a network imposes disruption or delay. The delay tolerant networks operate in limited resources such as memory size, central processing unit. Trust management protocol uses a dynamic threshold updating which overcomes the problems .The dynamic threshold update reduces the false detection probability of the malicious nodes. The system proposes a secure routing management schemes to adopt information security principles successfully. It analyzes the basic security principles and operations for trust authentication which is applicable in delay tolerant networks (DTNs).For security the proposed system identifies the store and forward approach in network communications and analyzes the routing in cases like selfish contact and collaboration contact methods. The proposed method identifies ZRP protocol scheme and it enhances the scheme using methods namely distributed operation, mobility, delay analysis, security association and trust modules. This security scheme analyzes the performance analysis and proposed algorithm based on parameter time, authentication, security, and secure routing. From this analysis, this research work identifies the issues in DTNs secure routing and enhances ZRP (Zone Routing Protocol) by suggesting an authentication principle as a noted security principle for extremely information security concepts.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
A Computational Dynamic Trust Model for User Authorization1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
AN EXAUSTIVE SURVEY OF TRUST MODELS IN P2P NETWORKijwscjournal
Most of the peers accessing the services are under the assumption that the service accessed in a P2P network is utmost secured. By means of prevailing hard security mechanisms, security goals like authentication, authorization, privacy, non repudiation of services and other hard security issues are resolved. But these mechanisms fail to provide soft security. An exhaustive survey of existing trust and reputation models in P2P network regarding service provisioning is presented and challenges are listed. Trust issues like trust bootstrapping, trust evidence procurement, trust assessment, trust interaction outcome evaluation and other trust based classification of peer’s behavior into trusted,, inconsistent, un
trusted, malicious, betraying, redemptive are discussed,
AN EXAUSTIVE SURVEY OF TRUST MODELS IN P2P NETWORKijwscjournal
ABSTRACT
Most of the peers accessing the services are under the assumption that the service accessed in a P2P
network is utmost secured. By means of prevailing hard security mechanisms, security goals like
authentication, authorization, privacy, non repudiation of services and other hard security issues are
resolved. But these mechanisms fail to provide soft security. An exhaustive survey of existing trust and
reputation models in P2P network regarding service provisioning is presented and challenges are listed.
Trust issues like trust bootstrapping, trust evidence procurement, trust assessment, trust interaction
outcome evaluation and other trust based classification of peer’s behavior into trusted,, inconsistent, un
trusted, malicious, betraying, redemptive are discussed,
Developing a trust model using graph and ranking trust of social messaging s...IJECEIAES
Trust is an important issue in social interactions, especially in using cyberspace services. In this paper, a trust and evaluation model are proposed based on which the government can provide reliable services to users. The model is a distributed and hierarchical model. First, the number 12 trust criteria and the weight of these criteria were extracted using the analytical hierarchy process (AHP) and analytic network process (ANP) techniques. Second, to obtain the trust in the service examined, for each criterion, a graph of trusted entities is proposed. Then, a weighted graph with the number of trusted entities called trust pathways measure will be obtained. To test the model, the effect of the 12 criteria on three important evaluation factors over seven widely used social services was rated by three experts. The trust of each service was obtained, which was satisfactory as compared to a valid organizational evaluation. Finally, the correlation coefficient of this comparison was 70.37%, indicating that the results from this model were appropriate.
TUX-TMS: Thapar University Extensible-Trust Management SystemCSCJournals
In a Grid Computing scenario, where the market players are dynamic; traditional assumptions for establishing and evaluating trust, do not hold good anymore. There are two different methods for handling access controls to the resources either by using policy based approach where logical rules and verifiable properties are encoded in signed credentials or using reputation based approach where trust values are collected, aggregated and evaluated to disseminate reputation among the market players. There is need for a dynamic and flexible general-purpose trust management system. In this paper TUX-TMS: an extensible reputation based Trust Management System is presented for establishing and evaluating trust in grid systems. TUX is an efficient Reputation based trust management system for establishing secure Grids.
PURGING OF UNTRUSTWORTHY RECOMMENDATIONS FROM A GRIDijngnjournal
In grid computing, trust has massive significance. There is lot of research to propose various models in providing trusted resource sharing mechanisms. The trust is a belief or perception that various researchers have tried to correlate with some computational model. Trust on any entity can be direct or indirect. Direct trust is the impact of either first impression over the entity or acquired during some direct interaction. Indirect trust is the trust may be due to either reputation gained or recommendations received from various recommenders of a particular domain in a grid or any other domain outside that grid or outside that grid itself. Unfortunately, malicious indirect trust leads to the misuse of valuable resources of the grid. This paper proposes the mechanism of identifying and purging the untrustworthy recommendations in the grid environment. Through the obtained results, we show the way of purging of untrustworthy entities.
How Psychological Factors Shape DeFi TrustworthinessThe Connecter
Trust is a psychological construct that plays a central role in the adoption and success of DeFi. Establishing trust in the decentralized realm requires a multi-faceted approach, considering factors such as transparency, consistency, security, and community engagement.
Social life in digital societies: Trust, Reputation and Privacy EINS summer s...i_scienceEU
Ralph Holz (Technische Universitat Munchen)
Pablo Aragon (Barcelona Media)
Katleen Gabriels (IBBT-SMIT, Vrije Univeriteit Brussel)
Janet Xue (Macquaire University)
Anna Satsiou (Centre for Research and Technology Hellas- Information Technologies Institute)
Sorana Cimpan (Universite De Savoie)
Norbert Blenn (Delft University of Technology)
More information: http://www.internet-science.eu/
The objective of the paper is to propose a
predictable context sensitive trust model for a business system.
A business system can be imagined with four basic entities
between which there is a mutual trust of different nature exists.
A formal model, which encompasses the trust between the
stack-holders is proposed where the context sensitive features
of the multi variate trust issues are addressed. The impact
of both the legal environment and the interoperability factors
on various entities involved in the trust issues are focused in
the work. The key dimensions of the trust i.e. integrity and
loyalty are determined through acceptable uncertainties of
various components in the proposed model the proposed context
sensitive trust model for business systems. The model which
represents the various trusts in a context sensitive business
system is verified using a numerical simulation tool and the
inferences are drawn with a scenario
Buying intangibles requires higher levels of trust than do specification compliant products and therefore demands new approaches to building confidence in the supplier’s value proposition. Trust Enablement™ gives suppliers a strategic approach to building value based on trust into the supply chain.
A Real Dynamic Cyber Trust Model is an application that is proposed in order to distinguish the trust belief among the trustees who have been marketing in today's digital world by authenticated users. Though we are happy with the developing technology, still we are worrying about the security issues in every scenario. In the same way, if we shop online by trusting some products, there are few chances of getting bad products. We can experience these types of scenarios when we shop online in some interfaces like amazon, e bay, flip kart, etc. Of course, there are many existing systems which give a rating to the product, that help the buyer to trust the seller and buy the product. Still, there is an issue of being cheated by some wrong reviews given by unauthenticated users. In order to overcome that type of issues, this Real Dynamic Cyber Trust Model has been proposed. A Real Dynamic Cyber Trust Model has taken the scenario of seller and buyer who goes shopping for products online. This Real Dynamic Cyber Trust model acts as an interface between the Seller and Buyer. Both Modules of Seller and Buyer have the opportunity of getting registered and log in to the application. Buyer can give the feedback of any product he buys and checks the trust factor of any seller. Whereas the Seller can add, update or delete the products he sells. Based on the feedback given by the buyer the Real Dynamic Cyber Trust Model calculates the trust factor of the seller, which helps the buyer to find out whether the seller is trustworthy or not. Kuchillapati Chinnari | Dr. Adusumalli Balaji "A Real Dynamic Cyber Trust Model" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26420.pdfPaper URL: https://www.ijtsrd.com/computer-science/programming-language/26420/a-real-dynamic-cyber-trust-model/kuchillapati-chinnari
Analyzing and Surveying Trust In Cloud Computing Environmentiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Similar to A computational dynamic trust model (20)
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A computational dynamic trust model
1. A COMPUTATIONAL DYNAMIC TRUST MODEL FOR USER AUTHORIZATION
Abstract—Development of authorization mechanisms for secure information
access by a large community of users in an open environment is an important
problem in the ever-growing Internet world. In this paper we propose a
computational dynamic trust model for user authorization, rooted in findings from
social science. Unlike most existing computational trust models, this model
distinguishes trusting belief in integrity from that in competence in different
contexts and accounts for subjectivity in the evaluation of a particular trustee by
different trusters. Simulation studies were conducted to compare the performance
of the proposed integrity belief model with other trust models from the literature
for different user behavior patterns. Experiments show that the proposed model
achieves higher performance than other models especially in predicting the
behavior of unstable users.
EXISTING SYSTEM:
The social trust model, which guides the design of the computational model in this
paper, was proposed by McKnight and Chervany after surveying more than 60
papers across a wide range of disciplines. It has been validated via empirical study.
This model defines five conceptual trust types: trusting behavior, trusting intention,
2. trusting belief, institution-based trust, and disposition to trust. Trusting behavior is
an action that increases a truster’s risk or makes the truster vulnerable to the
trustee. Trusting intention indicates that a truster is willing to engage in trusting
behaviors with the trustee. A trusting intention implies a trust decision and leads to
a trusting behavior. Two subtypes of trusting intention are: 1) Willingness to
depend: the volitional preparedness to make oneself vulnerable to the trustee. 2)
Subjective probability of depending: the likelihood that a truster will depend on a
trustee. Trusting belief is a truster’s subjective belief in the fact that a trustee has
attributes beneficial to the truster. The following are the four attributes used most
often: 1) Competence: a trustee has the ability or expertise to perform certain tasks.
2) Benevolence: a trustee cares about a truster’s interests. 3) Integrity: a trustee is
honest and keeps commitments. 4) Predictability: a trustee’s actions are
sufficiently consistent. Institution-based trust is the belief that proper structural
conditions are in place to enhance the probability of achieving a successful
outcome. Two subtypes of institution-based trust are: 1) Structural assurance: the
belief that structures deployed promote positive outcomes. Structures include
guarantees, regulations, promises etc. 2) Situational normality: the belief that the
properly ordered environments facilitate success outcomes.
PROPOSED SYSTEM:
3. In this work, we propose a computational dynamic trust model for user
authorization. Mechanisms for building trusting belief using the first-hand (direct
experience) as well as second-hand information (recommendation and reputation)
are integrated into the model. The contributions of the model to computational trust
literature are:
_ The model is rooted in findings from social science, i.e., it provides automated
trust management that mimics trusting behaviors in the society, bringing trust
computation for the digital world closer to the evaluation of trust in the real world.
_ Unlike other trust models in the literature, the proposed model accounts for
different types of trust. Specifically, it distinguishes trusting belief in integrity from
that in competence.
_ The model takes into account the subjectivity of trust ratings by different entities,
and introduces a mechanism to eliminate the impact of subjectivity in reputation
aggregation.
Module1
Trust model
The trust model we propose in this paper distinguishes integrity trust from
competence trust. Competence trust is the trusting belief in a trustee’s ability or
4. expertise to perform certain tasks in a specific situation. Integrity trust is the belief
that a trustee is honest and acts in favor of the truster. Integrity and benevolence in
social trust models are combined together. Predictability is attached to a
competence or integrity belief as a secondary measure. The elements of the model
environment, as seen in Fig. 1, include two main types of actors, namely trusters
and trustees, a database of trust information, and different contexts, which depend
on the concerns of a truster and the competence of a trustee. For the online auction
site example in Section 1, let us assume that buyer B needs to decide whether to
authorize seller S to charge his credit card for an item I (authorize access to his
credit card/contactinformation). The elements of the model in this case are:
_ Trusters are the buyers registered to the auction site.
_ Trustees are the sellers registered to the auction site.
_ The context states how important for B the shipping, packaging and item quality
competences of S for item I are. It also states how important for B the integrity of
S is for this transaction.
_ B can gather trust information about S from a database maintained by the site or
a trusted third party. This information includes the ratings that S received from
buyers (including B’s previous ratings, if any) for competence in shipping,
packaging and quality of I as well as S’s integrity. It also includes the ratings of
buyers (including B) for sellers other than S in different contexts and ratings of S
5. for different items. Trust evaluation is recorded in the database when a buyer rates
a transaction with a seller on the site.
Module 2
Trusting belief
Beliefs in two attributes, competence and integrity, are separated. Context
identifier is included for competence belief. Values of both beliefs are real
numbers ranging from 0 to 1. The higher the value, the more a truster believes in a
trustee. Predictability is a positive real number. It characterizes the goodness of
belief formed. The smaller the predictability or uncertainty, the more confident a
truster is about the associated belief value. Both the variability of a trustee’s
behaviors and lack of observations negatively impact the goodness of belief
formed. iNumber in competence belief records the number of observations
accumulated. Trusting beliefs can be classified into initial and continuous trust.
Initial trust is the belief established before a truster t1 interacts with a trustee u1.
Continuous trust is the belief after t1 has had appropriate direct experience with u1.
Module 3
Global and Local Profiles
Each truster t1 has one global profile. The profile contains: (1) t1’s priori integrity
and competence trusting belief; (2) method preference policies; (3) imprecision
6. handling policies; (4) uncertainty handling policies; (5) parameters needed by
trust-building methods. t1 can have one local profile for each context. Local
profiles have a similar structure as global profiles. The content in a local profile
overrides that in the global one. Fig. 4 shows the definition of global and local
profiles. As aforementioned, method preference policies, defined as Preference
Policy, are to extend the partial order _ to a total order. Therefore, no two methods
have the same priority. iCompetence and cCompetence are used when building
initial and continuous competence trust respectively. iCompetence consists of four
parts corresponding to the four scenarios to build initial competence trust.
iIntegrity and cIntegrity are for establishing integrity trusting belief. Relationships
are separately defined on each ambiguous priority set.
Module 4
Integrity belief
Integrity may change fast with time. Furthermore, it possesses a meaningful trend.
Evaluation of integrity belief is based on two assumptions:
_ We assume integrity of a trustee is consistent in all contexts.
_ Integrity belief may vary largely with time. An example is a user behaving well
until he reaches a high trust value and then starts committing fraud. We used mean
as an estimator for competence belief as it is relatively steady with time. For
integrity belief, this assumption is excluded. When behavior patterns are present,
7. the mean is no more a good estimator. The similarity between a rating sequence
and a time series inspires us to adopt the method of double exponential moothing
[7] to predict the next rating based on a previous rating sequence. Let ri denote the
ith rating and fiþ1 denote the forecast value of riþ1 after observing the rating
sequence r1; . . . ; ri.
CONCLUSION
In this paper we presented a dynamic computational trust model for user
authorization. This model is rooted in findings from social science, and is not
limited to trusting belief as most computational methods are. We presented a
representation of context and functions that relate different contexts, enabling
building of trusting belief using crosscontext information. The proposed dynamic
trust model enables automated trust management that mimics trusting behaviors in
society, such as selecting a corporate partner, forming a coalition, or choosing
negotiation protocols or strategies in e-commerce. The formalization of trust helps
in designing algorithms to choose reliable resources in peer-to-peer systems,
developing secure protocols for ad hoc networks and detecting deceptive agents in
a virtual community. Experiments in a simulated trust environment show that the
proposed integrity trust model performs better than other major trust models in
predicting the behavior of users whose actions change based on certain patterns
over time.
8. REFERENCES
[1] G.R. Barnes and P.B. Cerrito, “A Mathematical Model for Interpersonal
Relationships in Social Networks,” Social Networks, vol. 20, no. 2, pp. 179-196,
1998.
[2] R. Brent, Algorithms for Minimization without Derivatives. Prentice- Hall,
1973.
[3] A. Das and M.M. Islam, “SecuredTrust: A Dynamic Trust Computation Model
for Secured Communication in Multiagent Systems,” IEEE Trans. Dependable and
Secure Computing, vol. 9, no. 2, pp. 261- 274, Mar./Apr. 2012.
[4] C. Dellarocas, “Immunizing Online Reputation Reporting Systems against
Unfair Ratings and Discriminatory Behavior,” Proc. Second ACM Conf.
Electronic Commerce, pp. 150-157, 2000.
[5] L. Fan, “A Grid Authorization Mechanism with Dynamic Role Based on Trust
Model,” J. Computational Information Systems, vol. 8, no. 12, pp. 5077-5084,
2012.
[6] T. Grandison and M. Sloman, “A Survey of Trust in Internet Applications,”
IEEE Comm. Surveys, vol. 3, no. 4, pp. 2-16, Fourth Quarter 2000.
[7] J.D.Hamilton, TimeSeriesAnalysis. PrincetonUniversity Press, 1994.
9. [8] J. Hu, Q. Wu, and B. Zhou, “FCTrust: A Robust and Efficient Feedback
Credibility-Based Distributed P2P Trust Model,” Proc. IEEE Ninth Int’l Conf.
Young Computer Scientists (ICYCS ‘08), pp. 1963- 1968, 2008.
[9] B. Lang, “A Computational Trust Model for Access Control in P2P,” Science
China Information Sciences, vol. 53, no. 5, pp. 896-910, May 2010.
[10] C. Liu and L. Liu, “A Trust Evaluation Model for Dynamic Authorization,”
Proc. Int’l Conf. Computational Intelligence and Software Eng. (CiSE), pp. 1-4,
2010.