Trust Management-Based Service Recovery and Attack Prevention in MANET

Abstract

The mobile ad-hoc network (MANET) output is critically impaired by the versatility and resource constraint of nodes. Node mobility affects connection reliability, and node resource constraints can lead to congestion, which makes the design of a routing MANET protocol with quality of service (QoS) very difficult. An adaptive clustering reputation model (ACRM) method is proposed to improve energy efficiency with a cluster-based framework. The proposed framework is employed to overcome the problems of data protection, privacy, and policy. The proposed ACRM-MRT approach that includes direct and indirect node trust computation is introduced along with the master recovery timer (MRT) for achieving an efficient service recovery process, and its service recovery time is calculated through the service execution process. During data transmission in MANET, various types of attacks can occur, of which the Sybil attack is the most dangerous. To address this problem, this paper proposed a method for the detection and prevention of Sybil attacks using a resilient scheme. The proposed method can improve system energy efficiency and address security, safety, and privacy issues of wireless network applications. Finally, the performance of the proposed method is evaluated regarding the time delay, throughput, energy efficiency, control overhead, and detection rate. The simulation results show that the proposed ACRM-MRT method can effectively improve the time delay, throughput, energy efficiency, control overhead, and detection rate compared to the existing methods. Topological change adaptive ad-hoc on-demand multi-path distance vector (TA-AOMDV)and ad-hoc on-demand multi-path distance vector (AOMDV) are simulated on the NS2 platform for the data rate in the range of 4-40 kbps and the number of nodes in the range of 10-100. The proposed method can reduce the service recovery time in the case of faults during service execution and can be used in real-time applications traffics since it is mostly affected by failure through the occurrence of delay and loss of packets.

A Transaction Frequency Based Trust for E-Commerce

“…In social activities, trust intention or trust behavior consists of the following parts: trusted belief, system trust, situational trust and intentional trust [23][24][25][26]. Trust belief refers to the belief that one party believes that the other party is willing and able to act according to the wishes of others; system trust refers to the use of appropriate non-human organization structure to ensure reliable behavior in the future; intentional trust refers to the general trust expectation of other entities gradually established along with the evolution of the entity's life cycle; situational trust is applicable to trust.…”