scholarly journals A Fuzzy Collusive Attack Detection Mechanism for Reputation Aggregation in Mobile Social Networks: A Trust Relationship Based Perspective

2016 ◽  
Vol 2016 ◽  
pp. 1-16 ◽  
Author(s):  
Bo Zhang ◽  
Qianqian Song ◽  
Tao Yang ◽  
Zhonghua Zheng ◽  
Huan Zhang
Keyword(s):  
Social Networks ◽  
Social Relationships ◽  
Attack Detection ◽  
Mobile Social Networks ◽  
Malicious Nodes ◽  
Detection Mechanism ◽  
Factor Node ◽  
Similar Factor ◽  
Collusive Attacks ◽  
Collusive Attack

While the mechanism of reputation aggregation proves to be an effective scheme for indicating an individual’s trustworthiness and further identifying malicious ones in mobile social networks, it is vulnerable to collusive attacks from malicious nodes of collaborative frauds. To conquer the challenge of detecting collusive attacks and then identifying colluders for the reputation system in mobile social networks, a fuzzy collusive attack detection mechanism (FCADM) is proposed based on nodes’ social relationships, which comprises three parts: trust schedule, malicious node selection, and detection traversing strategy. In the first part, the trust schedule provides the calculation method of interval valued fuzzy social relationships and reputation aggregation for nodes in mobile social networks; further, a set of fuzzy valued factors, that is, item judgment factor, node malicious factor, and node similar factor, is given for evaluating the probability of collusive fraud happening and identifying single malicious nodes in the second part; and moreover, a detection traversing strategy is given based on random walk algorithm under the perspectives of fuzzy valued nodes’ trust schedules and proposed malicious factors. Finally, our empirical results and analysis show that the proposed mechanism in this paper is feasible and effective.

scholarly journals An Effective Data Transmission Algorithm Based on Social Relationships in Opportunistic Mobile Social Networks

Algorithms ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 125 ◽  
Author(s):  
Yeqing Yan ◽  
Zhigang Chen ◽  
Jia Wu ◽  
Leilei Wang
Keyword(s):  
Social Networks ◽  
Social Relationships ◽  
Data Transmission ◽  
Human Activities ◽  
Opportunistic Networks ◽  
Network Routing ◽  
Transmission Delay ◽  
Mobile Social Networks ◽  
Routing Overhead ◽  
Opportunistic Mobile Social Networks

With the popularization of mobile communication equipment, human activities have an increasing impact on the structure of networks, and so the social characteristics of opportunistic networks become increasingly obvious. Opportunistic networks are increasingly used in social situations. However, existing routing algorithms are not suitable for opportunistic social networks, because traditional opportunistic network routing does not consider participation in human activities, which usually causes a high ratio of transmission delay and routing overhead. Therefore, this research proposes an effective data transmission algorithm based on social relationships (ESR), which considers the community characteristics of opportunistic mobile social networks. This work uses the idea of the faction to divide the nodes in the network into communities, reduces the number of inefficient nodes in the community, and performs another contraction of the structure. Simulation results show that the ESR algorithm, through community transmission, is not only faster and safer, but also has lower transmission delay and routing overhead compared with the spray and wait algorithm, SCR algorithm and the EMIST algorithm.

scholarly journals MAR_Worm: Secure and Efficient Wormhole Detection Scheme through Trusted Neighbour Nodes in VANETs

2019 ◽  
Vol 9 (2S) ◽  
pp. 180-183
Keyword(s):  
Trust Management ◽  
Attack Detection ◽  
Ieee 802.11P ◽  
Intelligent Transport System ◽  
Network Simulator ◽  
Malicious Nodes ◽  
Detection Mechanism ◽  
Traffic Condition ◽  
Detection Scheme ◽  
Efficient Detection

VANET is an application and subclass of MANET’s, in which nodes are mobiles and considered as moving, communicating vehicles in a wireless adhoc network. Vehicles communicate through dedicated short rage communication (DSRC) via IEEE 802.11p protocol. With the progress of wireless technology, vehicular ad hoc network has become emerging technology to support real-time traffic condition, safety, entertainment, enhance driver experience and emergency navigation in intelligent transport system (ITS). Core of VANETs application is the communication between vehicle to vehicle (V2V), vehicle to roadside unit (V2RSU) and securing the data messages from malicious activities and attackers in the network. Securing V2V and V2RSU communication has raised challenging issues in detecting and avoiding malicious attackers for secure communications. VANET’s are exposed to different threats while routing data, wormhole attack is the most threatening routing attack which severely effects VANET routing data and causes incorrect routing by private tunnels and damages to VANET’s communication in terms of data leakage, data dropping, and delayed delivery. However existing attack detection schemes have failed to meet secured VANETs communication leading to packet loss. In this paper we propose an efficient wormhole detection mechanism by creating potential and trusted neighbour nodes discovery (TNND) in VANETs, which can detect malicious nodes through enabling common forwarding neighbour nodes as witness to monitor data packets are forwarded by malicious nodes. Basically this mechanism is based on trust management. This scheme is resilient and resistant against attackers launching malicious nodes to corrupt entire network. Simulation is carried on event driven network simulator and results shows efficient detection of wormhole nodes, increases packet delivery and performs better than existing detection scheme.

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