Faculty Publications
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Publications by NITK Faculty
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Item Intrusion detection technique for wormhole and following jellyfish and byzantine attacks in wireless mesh network(2012) Karri, K.; Santhi Thilagam, P.Wireless Mesh Networks (WMNs) have emerging application because of its ad-hoc features, high internet bandwidth capability, and interoperable with various networks. However, all features of WMNs vulnerable due to their inadequate security services, and most of the existing techniques protect WMNs from single adversary node, but failed to protect colluding attacks. We proposed new Intrusion Detection (ID) technique, to protect the WMNs from wormhole attack (colluding attack) and following jellyfish and byzantine attacks. The proposed ID technique works based on different delays such as initial end-to-end packet delay, average end-to-end packet delay, and worst case end-to-end packet delay because wormhole attackers attract the network nodes by sending lower latency. Eventually, simulation results show that, our ID technique improves throughput of the network, when source and destination nodes detect and isolate (select new path which does not contain adversaries) the adversaries in wormhole attack and its following attacks. © 2012 Springer-Verlag.Item Taxonomy of network layer attacks in wireless mesh network(2012) Karri, K.; Santhi Thilagam, P.Wireless Mesh Networks (WMNs) have emerging application because of its ad-hoc features, high internet bandwidth capability, and interoperable with various networks. However, all features of WMNs vulnerable due to their inadequate security services, and most of the existing techniques protect WMNs only.from single adversary node, but these techniques are failed to protect against multiple colluding attacks, and also have same reputation value for all types of attacks. To overcome these problems for future solutions, we have done clear analytical survey on network layer attacks. Eventually, we have come up with taxonomy of network layer attack. © 2012 Springer-Verlag GmbH.Item Cross-layer IDS for rushing attack in wireless mesh networks(2012) Karri, K.; Santhi Thilagam, P.; Rao, B.N.Wireless Mesh Networks (WMNs) are a promising technology to provide the wireless internet connectivity. WMNs are becoming a popular choice for wireless internet service providers to offer internet connectivity as it allows a fast, easy and inexpensive network deployment. However, security in WMNs is still in its infancy. Security and privacy has been a major concern in WMNs. WMNs are susceptible to broad variety of attacks due to its open medium, dynamic topology and lack of physical security. WMNs are more vulnerable in Network layer. Several attacks are possible in the network layer. Some of the attacks have possible solutions but there is no solution for to detect Rushing attack which leads to the Denial of Service. In this paper, the authors proposed Cross- Layer Intrusion Detection System (CLIDS) for Rushing attack. We evaluated the performance of our technique using network simulator 2. Simulation results show that CLIDS has less false positive and false negative rates than single layer intrusion detection system. Copyright © 2012 ACM.Item Naïve bayes classifier to mitigate the DDoS attacks severity in Ad-Hoc networks(Kohat University of Science and Technology ijcnis@gmail.com, 2020) Karri, K.; Santhi Thilagam, P.Ad-Hoc networks are becoming more popular due to their unique characteristics. As there is no centralized control, these networks are more vulnerable to various attacks, out of which Distributed Denial of Service (DDoS) attacks consider as more severe attacks. DDoS attack detection and mitigation is still a challenging issue in Ad-Hoc Networks. The existing solutions find the fixed or dynamic threshold value to detect the DDoS attacks without any trained data. Very few existing solutions use machine learning algorithms to detect these attacks. However, existing solutions are inefficient to handle when DDoS attackers perform this attack through bursty traffic, packet size, and fake packets flooding. We have proposed DDoS attack severity mitigation solution. Out DDoS mitigation solution consists of a new network node authentication module and naïve Bayes classifier module to detect and isolate the DDoS attack traffic patterns. Our simulation results show that naïve Bayes DDoS attack traffic classification outperforms in the hostile environment and secure the legitimate traffic from DDoS attack. © 2020, Kohat University of Science and Technology.