An Improved Wormhole Attack Detection and Prevention Method for Wireless Mesh Networks

Network coding has been shown to be an effective approach to improve the wireless system performance. However, many security issues impede its wide deployment in practice.Besides the well-studied pollution attacks, there is another severe threat, that of wormhole attacks, which undermines the performance gain of network coding. Since the underlying characteristics of network coding systems are distinctly different from traditional wireless networks, the impact of wormhole attacks and countermeasures are generally unknown. In this paper, we quantify wormholes� devastating harmful impact on network coding system performance through experiments. We first propose a centralized algorithm to detect wormholes and show its correctness rigorously. For the distributed wireless network, we propose DAWN, a Distributed detection Algorithm against Wormhole in wireless Network coding systems, by exploring the change of the flow directions of the innovative packets caused by wormholes. We rigorously prove that DAWN guarantees a good lower bound of successful detection rate. We perform analysis on the resistance of DAWN against collusion attacks.We find that the robustness depends on the node density in the network, and prove a necessary condition to achieve collusion-resistance. DAWN does not rely on any location information, global synchronization assumptions or special hardware/middleware. It is only based on the local information that can be obtained from regular network coding protocols, and thus the overhead of our algorithms is tolerable. Extensive experimental results have verified the effectiveness and the efficiency of DAWN

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

Detection of Hidden Wormhole Attack in Wireless Sensor Networks using Neighborhood and Connectivity Information

Wireless sensor networks (WSNs) have inspired many applications such as military applications, environmental monitoring and other fields. WSN has emergence in various fields, so security is very important issue for sensor networks. Security comes from attacks. Due to the wireless and distributed nature anyone can connect with the network. Among all possible attacks, wormholes are very hard to detect because they can cause damage to the network without knowing the protocols used in the network. It is a powerful attack that can be conducted without requiring any cryptographic breaks. Wormholes are hard to detect because they use a private, out-of-band channel invisible to the underlying sensor network. In this paper we have proposed a wormhole detection protocol based on neighborhood and connectivity information. Performance analysis shows that our proposed approach can effectively detect wormhole attack with less storage cost. Keywords: Wireless sensor network, wormhole, out-of-band, security, neighborhood

A Unified Wormhole Attack Detection Framework for Mobile Ad hoc Networks

The Internet is experiencing an evolution towards a ubiquitous network paradigm, via the so-called internet-of-things (IoT), where small wireless computing devices like sensors and actuators are integrated into daily activities. Simultaneously, infrastructure-less systems such as mobile ad hoc networks (MANET) are gaining popularity since they provide the possibility for devices in wireless sensor networks or vehicular ad hoc networks to share measured and monitored information without having to be connected to a base station. While MANETs offer many advantages, including self-configurability and application in rural areas which lack network infrastructure, they also present major challenges especially in regard to routing security. In a highly dynamic MANET, where nodes arbitrarily join and leave the network, it is difficult to ensure that nodes are trustworthy for multi-hop routing. Wormhole attacks belong to most severe routing threats because they are able to disrupt a major part of the network traffic, while concomitantly being extremely difficult to detect. This thesis presents a new unified wormhole attack detection framework which is effective for all known wormhole types, alongside incurring low false positive rates, network loads and computational time, for a variety of diverse MANET scenarios. The framework makes three original technical contributions: i) a new accurate wormhole detection algorithm based on packet traversal time and hop count analysis (TTHCA) which identifies infected routes, ii) an enhanced, dynamic traversal time per hop analysis (TTpHA) detection model which is adaptable to node radio range fluctuations, and iii) a method for automatically detecting time measurement tampering in both TTHCA and TTpHA. The thesis findings indicate that this new wormhole detection framework provides significant performance improvements compared to other existing solutions by accurately, efficiently and robustly detecting all wormhole variants under a wide range of network conditions

A Secure AdHoc Wireless Clustering Scheme for Improving Security

wireless communication is easy to use, rapid implementable and low cost communication technique as compared to the traditional wired communication.Therefore a number of different applications are consumes the wireless communication technology. In wireless ad hoc technology the networks are supporting the mobility and ad hoc configuration of topology development. Therefore the on demand nature of routing is much helpful. Such kind of networks are suffers from the performance and security issues. Therefore the given paper addresses the key security issues and a solution is redesigned to incorporate the security solutions. This method utilizes the weighted clustering algorithm for demonstrating the security solution and the performance issues. In addition of that the implementation strategy and the obtained outcomes of the proposed secure weighted clustering algorithm is also provided. DOI: 10.17762/ijritcc2321-8169.15033

Naïve Bayes Classifier to Mitigate the DDoS Attacks Severity in Ad-Hoc Networks

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 are considered as more severe attacks. DDoS attack detection and mitigation is still a challenging issue in Ad-Hoc Networks. The existing solutions consider the fixed or dynamic threshold value to detect the DDoS attacks without any trained data, and 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 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 out performs in the hostile environment and secure the legitimate traffic from DDoS attack

Policy-Based Immunization Framework for MANET

Mobility is one of the most important driving forces of hyper-interconnected world that we are living in. Mobile computing devices are becoming smaller, more ubiquitous and simultaneously providing more computing power. Various mobile devices in diff rent sizes with high computing power cause the emergence of new type of networks\u27 applications. Researchers in conferences, soldiers in battlefields, medics in rescue missions, and drivers in busy high- ways can perform more efficiently if they can be connected to each other and aware of the environment they are interacting with. In all mentioned scenarios, the major barrier to have an interconnected collaborative environment is the lack of infrastructure. Mobile Ad hoc Networks (MANETs) are very promising to be able to handle this challenge. In recent years, extensive research has been done on MANETs in order to deliver secure and reliable network services in an infrastructure-less environment. MANETs usually deal with dynamic network topologies and utilize wireless technologies, they are very susceptible to different security attacks targeting different network layers. Combining policy-based management concepts and trust evaluation techniques in more granular level than current trust management frameworks can lead to interesting results toward more secure and reliable MANETs

Security wireless sensor networks: prospects, challenges, and future

With the advancements of networking technologies and miniaturization of electronic devices, wireless sensor network (WSN) has become an emerging area of research in academic, industrial, and defense sectors. Different types of sensing technologies combined with processing power and wireless communication capability make sensor networks very lucrative for their abundant use in near future. However, many issues are yet to be solved before their full-scale practical implementations. Among all the research issues in WSN, security is one of the most challenging topics to deal with. The major hurdle of securing a WSN is imposed by the limited resources of the sensors participating in the network. Again, the reliance on wireless communication technology opens the door for various types of security threats and attacks. Considering the special features of this type of network, in this chapter we address the critical security issues in wireless sensor networks. We talk about cryptography, steganography, and other basics of network security and their applicability in WSN. We explore various types of threats and attacks against wireless sensor networks, possible countermeasures, mentionable works done so far, other research issues, etc. We also introduce the view of holistic security and future trends towards research in wireless sensor network security