Biblio

Ad hoc network is sensitive to attacks because it has temporary nature and frequently recognized insecure environment. Both Ad hoc On-demand Distance Vector (AODV) and Ad hoc On-demand Multipath Distance vector (AOMDV) routing protocols have the strategy to take help from Wireless and mobile ad hoc networks. A mobile ad hoc network (MANET) is recognized as an useful internet protocol and where the mobile nodes are self-configuring and self-organizing in character. This research paper has focused on the detection and influence of black hole attack on the execution of AODV and AOMDV routing protocols and has also evaluated the performance of those two on-demand routing protocols in MANETs. AODV has the characteristics for discovering a single path in single route discovery and AOMDV has the characteristics for discovering multiple paths in single route discovery. Here a proposed method for both AODV and AOMDV routing protocol, has been applied for the detection of the black hole attack, which is the merge of both SHA-3 and Diffie-Hellman algorithm. This merge technique has been applied to detect black hole attack in MANET. This technique has been applied to measure the performance matrices for both AODV and AOMDV and those performance matrices are Average Throughput, Average End to End delay and Normalized Routing Load. Both AODV and AOMDV routing protocol have been compared with each other to show that under black hole attack, AOMDV protocol always has better execution than AODV protocol. Here, NS-2.35 has been used as the Network Simulator tool for the simulation of these particular three types of performance metrics stated above.

Performance of routing is severely degraded when misbehaving nodes drop packets instead of properly forwarding them. In this paper, we propose a Game-Theoretic Adaptive Multipath Routing (GTAMR) protocol to detect and punish selfish or malicious nodes which try to drop information packets in routing phase and defend against collaborative attacks in which nodes try to disrupt communication or save their power. Our proposed algorithm outranks previous schemes because it is resilient against attacks in which more than one node coordinate their misbehavior and can be used in networks which wireless nodes use directional antennas. We then propose a game theoretic strategy, ERTFT, for nodes to promote cooperation. In comparison with other proposed TFT-like strategies, ours is resilient to systematic errors in detection of selfish nodes and does not lead to unending death spirals.

In recent years the use of wireless ad hoc networks has seen an increase of applications. A big part of the research has focused on Mobile Ad Hoc Networks (MAnETs), due to its implementations in vehicular networks, battlefield communications, among others. These peer-to-peer networks usually test novel communications protocols, but leave out the network security part. A wide range of attacks can happen as in wired networks, some of them being more damaging in MANETs. Because of the characteristics of these networks, conventional methods for detection of attack traffic are ineffective. Intrusion Detection Systems (IDSs) are constructed on various detection techniques, but one of the most important is anomaly detection. IDSs based only in past attacks signatures are less effective, even more if these IDSs are centralized. Our work focuses on adding a novel Machine Learning technique to the detection engine, which recognizes attack traffic in an online way (not to store and analyze after), re-writing IDS rules on the fly. Experiments were done using the Dockemu emulation tool with Linux Containers, IPv6 and OLSR as routing protocol, leading to promising results.

Rapid advances in wireless ad hoc networks lead to increase their applications in real life. Since wireless ad hoc networks have no centralized infrastructure and management, they are vulnerable to several security threats. Malicious packet dropping is a serious attack against these networks. In this attack, an adversary node tries to drop all or partial received packets instead of forwarding them to the next hop through the path. A dangerous type of this attack is called black hole. In this attack, after absorbing network traffic by the malicious node, it drops all received packets to form a denial of service (DOS) attack. In this paper, a dynamic trust model to defend network against this attack is proposed. In this approach, a node trusts all immediate neighbors initially. Getting feedback from neighbors' behaviors, a node updates the corresponding trust value. The simulation results by NS-2 show that the attack is detected successfully with low false positive probability.

Mobile Ad-Hoc Networks are dynamic and wireless self-organization networks that many mobile nodes connect to each other weakly. To compare with traditional networks, they suffer failures that prevent the system from working properly. Nevertheless, we have to cope with many security issues such as unauthorized attempts, security threats and reliability. Using mobile agents in having low level fault tolerance ad-hoc networks provides fault masking that the users never notice. Mobile agent migration among nodes, choosing an alternative paths autonomous and, having high level fault tolerance provide networks that have low bandwidth and high failure ratio, more reliable. In this paper we declare that mobile agents fault tolerance peculiarity and existing fault tolerance method based on mobile agents. Also in ad-hoc networks that need security precautions behind fault tolerance, we express the new model: Secure Mobil Agent Based Fault Tolerance Model.