Restoring the privacy and confidentiality of users over Mobile collaborative learning (MCL) environment (1309.4499v1)

Abstract: Mobile collaborative learning (MCL) is extensively recognized field all over the world. It demonstrates the cerebral approach combining the several technology to handle the problem of learning. MCL motivates the social and educational activities for creating healthier environment. To advance and promote the baseline of MCL, different frameworks have been introduced for MCL. From other side, there is no highly acceptable security mechanism has been implemented to protect MCL environment. This paper introduces the issue of rogue DHCP server, which highly affects the performance of users who communicate with each other through MCL. The rogue DHCP is unofficial server that gives incorrect IP address to user in order to use the legal sources of different servers by sniffing the traffic. The contribution focuses to maintain the privacy of users and enhances the confidentiality. The paper introduces multi-frame signature-cum anomaly-based intrusion detection systems (MSAIDS) supported with innovative algorithms, modification in the existing rules of IDS and use of mathematical model. The major objectives of research are to identify the malicious attacks created by rogue DHCP server. This innovative mechanism emphasizes the security for users in order to communicate freely. It also protects network from illegitimate involvement of intruders. Finally, the paper validates the mechanism using three types of simulations: testbed, discrete simulation in C++ and ns2. On the basis of findings, the efficiency of proposed mechanism has been compared with other well-known techniques.