A Lightweight and Attack Resistant Authenticated Routing Protocol for Mobile Adhoc Networks

In mobile ad hoc networks, by attacking the corresponding routing protocol, an attacker can easily disturb the operations of the network. For ad hoc networks, till now many secured routing protocols have been proposed which contains some disadvantages. Therefore security in ad hoc networks is a controversial area till now. In this paper, we proposed a Lightweight and Attack Resistant Authenticated Routing Protocol (LARARP) for mobile ad hoc networks. For the route discovery attacks in MANET routing protocols, our protocol gives an effective security. It supports the node to drop the invalid packets earlier by detecting the malicious nodes quickly by verifying the digital signatures of all the intermediate nodes. It punishes the misbehaving nodes by decrementing a credit counter and rewards the well behaving nodes by incrementing the credit counter. Thus it prevents uncompromised nodes from attacking the routes with malicious or compromised nodes. It is also used to prevent the denial-of-service (DoS) attacks. The efficiency and effectiveness of LARARP are verified through the detailed simulation studies.Comment: 14 Pages, IJWM

Security and Privacy Issues in Wireless Mesh Networks: A Survey

This book chapter identifies various security threats in wireless mesh network (WMN). Keeping in mind the critical requirement of security and user privacy in WMNs, this chapter provides a comprehensive overview of various possible attacks on different layers of the communication protocol stack for WMNs and their corresponding defense mechanisms. First, it identifies the security vulnerabilities in the physical, link, network, transport, application layers. Furthermore, various possible attacks on the key management protocols, user authentication and access control protocols, and user privacy preservation protocols are presented. After enumerating various possible attacks, the chapter provides a detailed discussion on various existing security mechanisms and protocols to defend against and wherever possible prevent the possible attacks. Comparative analyses are also presented on the security schemes with regards to the cryptographic schemes used, key management strategies deployed, use of any trusted third party, computation and communication overhead involved etc. The chapter then presents a brief discussion on various trust management approaches for WMNs since trust and reputation-based schemes are increasingly becoming popular for enforcing security in wireless networks. A number of open problems in security and privacy issues for WMNs are subsequently discussed before the chapter is finally concluded.Comment: 62 pages, 12 figures, 6 tables. This chapter is an extension of the author's previous submission in arXiv submission: arXiv:1102.1226. There are some text overlaps with the previous submissio

BLACK HOLE ATTACK IN AODV & FRIEND FEATURES UNIQUE EXTRACTION TO DESIGN DETECTION ENGINE FOR INTRUSION DETECTION SYSTEM IN MOBILE ADHOC NETWORK

Ad-hoc network is a collection of nodes that are capable to form dynamically a temporary network without the support of any centralized fixed infrastructure. Since there is no central controller to determine the reliable & secure communication paths in Mobile Adhoc Network, each node in the ad hoc network has to rely on each other in order to forward packets, thus highly cooperative nodes are required to ensure that the initiated data transmission process does not fail. In a mobile ad hoc network (MANET) where security is a crucial issue and they are forced to rely on the neighbor node, trust plays an important role that could improve the number of successful data transmission. Larger the number of trusted nodes, higher successful data communication process rates could be expected. In this paper, Black Hole attack is applied in the network, statistics are collected to design intrusion detection engine for MANET Intrusion Detection System (IDS). Feature extraction and rule inductions are applied to find out the accuracy of detection engine by using support vector machine. In this paper True Positive generated by the detection engine is very high and this is a novel approach in the area of Mobile Adhoc Intrusion detection system

Intelligent black hole detection in mobile AdHoc networks

Security is a critical and challenging issue in MANET due to its open-nature characteristics such as: mobility, wireless communications, self-organizing and dynamic topology. MANETs are commonly the target of black hole attacks. These are launched by malicious nodes that join the network to sabotage and drain it of its resources. Black hole nodes intercept exchanged data packets and simply drop them. The black hole node uses vulnerabilities in the routing protocol of MANETS to declare itself as the closest relay node to any destination. This work proposed two detection protocols based on the collected dataset, namely: the BDD-AODV and Hybrid protocols. Both protocols were built on top of the original AODV. The BDD-AODV protocol depends on the features collected for the prevention and detection of black hole attack techniques. On the other hand, the Hybrid protocol is a combination of both the MI-AODV and the proposed BDD-AODV protocols. Extensive simulation experiments were conducted to evaluate the performance of the proposed algorithms. Simulation results show that the proposed protocols improved the detection and prevention of black hole nodes, and hence, the network achieved a higher packet delivery ratio, lower dropped packets ratio, and lower overhead. However, this improvement led to a slight increase in the end-to-end delay

A Prey-Predator Defence Mechanism For Ad Hoc On-Demand Distance Vector Routing Protocol

This study proposes a nature-based system survivability model. The model was simulated, and its performance was evaluated for the mobile ad hoc wireless networks. The survivability model was used to enable mobile wireless distributed systems to keep on delivering packets during their stated missions in a timely manner in the presence of attacks. A prey-predator communal defence algorithm was developed and fused with the Ad hoc On-demand Distance Vector (AODV) protocol. The mathematical equations for the proposed model were formulated using the Lotka-Volterra theory of ecology. The model deployed a security mechanism for intrusion detection in three vulnerable sections of the AODV protocol. The model simulation was performed using MATLAB for the mathematical model evaluation and using OMNET++ for protocol performance testing. The MATLAB simulation results, which used empirical and field data, have established that the adapted Lotka-Volterra-based equations adequately represent network defense using the communal algorithm. Using the number of active nodes as a measure of throughput after attack (with a maximum throughput of 250 units), the proposed model had a throughput of 230 units while under attack and the intrusion was nullified within 2 seconds. The OMNET++ results for protocol simulation that use throughput, delivery ratio, network delay, and load as performance metrics with the OMNET++ embedded datasets showed good performance of the model, which was better than the existing conventional survivability systems. The comparison of the proposed model with the existing model is also presented. The study concludes that the proposed communal defence model was effective in protecting the entire routing layer (layer 2) of the AODV protocol when exposed to diverse forms of intrusion attacks

Feature Engineering for Detection of Wormhole Attacking in Mobile Ad Hoc Networks with Machine Learning Methods

Due to the self-configuring nature of a Mobile Ad Hoc Network (MANET), each node must participate in the routing process, in addition to its other activities. Therefore, routing in a MANET is especially vulnerable to malicious node activity leading to potentially severe disruption in network communications. The wormhole attack is a particularly severe MANET routing threat since it is easy to launch, can be launched in several modes, difficult to detect, and can cause significant communication disruption. In this paper we establish a practice for feature engineering of network data for wormhole attack prevention and detection with intrusion detection methods based on machine learning