A Novel Approach for Developing Intrusion Detection Systems in Mobile Social Networks

Intrusion Detection Systems (IDS) have been developed to improve security levels in networks. These systems can observe user activities and, upon detecting any abnormal behavior suggesting a potential hacker, issue an alert to network security managers while simultaneously limiting the hacker's activities. In this study, we propose an IDS based on communication analysis in social networks for ad hoc networks. The proposed IDS monitors the various relationships between ad hoc nodes and triggers an alert when one or more rules governing normal communications are violated. The performance of the proposed IDS is assessed under different system factors (such as mobility and traffic load). In this study, we tested the system against common attacks (such as packet dropping, black hole, sleep deprivation, and TCP SYN attacks). The results show that the proposed IDS can detect attacks with high speed, and the rate of false attack alerts is lower compared to previous work. Moreover, the results show that the proposed IDS offers significant advantages over IDSs based on the Apriori algorithm (in terms of computational complexity).