Cutting the Gordian Knot

2008 ◽  
pp. 531-546
Author(s):  
John Felix Charles Joseph ◽  
Amitabha Das ◽  
Boon-Chong Seet ◽  
Bu-Sung Lee
Keyword(s):  
Intrusion Detection ◽  
Ad Hoc Networks ◽  
Routing Protocols ◽  
Intrusion Detection System ◽  
Ad Hoc ◽  
Detection System ◽  
Intrusion Detection Systems ◽  
Future Directions ◽  
Detection Systems ◽  
Hoc Networks

Intrusion detection in ad hoc networks is a challenge because of the inherent characteristics of these networks, such as, the absence of centralized nodes, the lack of infrastructure, and so forth. Furthermore, in addition to application-based attacks, ad hoc networks are prone to attacks targeting routing protocols. Issues in intrusion detection in ad hoc networks are addressed by numerous research proposals in literature. In this chapter, we first enumerate the properties of ad hoc networks which hinder intrusion detection systems. After that, significant intrusion detection system (IDS) architectures and methodologies proposed in the literature are elucidated. Strengths and weaknesses of these works are studied and are explained. Finally, the future directions which will lead to the successful deployment of intrusion detection in ad hoc networks are discussed.

Artificial Intelligence Based Intrusion Detection System to Detect Flooding Attack in VANETs

2018 ◽  
pp. 87-100 ◽  
Author(s):  
Mannat Jot Singh Aneja ◽  
Tarunpreet Bhatia ◽  
Gaurav Sharma ◽  
Gulshan Shrivastava
Keyword(s):  
Intrusion Detection ◽  
Ad Hoc Networks ◽  
Intrusion Detection System ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Performance Metrics ◽  
Detection System ◽  
Delivery Ratio ◽  
Flooding Attack ◽  
Hoc Networks

This chapter describes how Vehicular Ad hoc Networks (VANETs) are classes of ad hoc networks that provides communication among various vehicles and roadside units. VANETs being decentralized are susceptible to many security attacks. A flooding attack is one of the major security threats to the VANET environment. This chapter proposes a hybrid Intrusion Detection System which improves accuracy and other performance metrics using Artificial Neural Networks as a classification engine and a genetic algorithm as an optimization engine for feature subset selection. These performance metrics have been calculated in two scenarios, namely misuse and anomaly. Various performance metrics are calculated and compared with other researchers' work. The results obtained indicate a high accuracy and precision and negligible false alarm rate. These performance metrics are used to evaluate the intrusion system and compare with other existing algorithms. The classifier works well for multiple malicious nodes. Apart from machine learning techniques, the effect of the network parameters like throughput and packet delivery ratio is observed.

Hybrid Intrusion Detection Framework for Ad hoc networks

2016 ◽  
Vol 10 (4) ◽  
pp. 1-32 ◽  
Author(s):  
Abdelaziz Amara Korba ◽  
Mehdi Nafaa ◽  
Salim Ghanemi
Keyword(s):  
Intrusion Detection ◽  
Anomaly Detection ◽  
Ad Hoc Networks ◽  
Intrusion Detection System ◽  
Ad Hoc ◽  
Detection System ◽  
Security Framework ◽  
Detection Techniques ◽  
Wide Range ◽  
Hoc Networks

In this paper, a cluster-based hybrid security framework called HSFA for ad hoc networks is proposed and evaluated. The proposed security framework combines both specification and anomaly detection techniques to efficiently detect and prevent wide range of routing attacks. In the proposed hierarchical architecture, cluster nodes run a host specification-based intrusion detection system to detect specification violations attacks such as fabrication, replay, etc. While the cluster heads run an anomaly-based intrusion detection system to detect wormhole and rushing attacks. The proposed specification-based detection approach relies on a set of specifications automatically generated, while anomaly-detection uses statistical techniques. The proposed security framework provides an adaptive response against attacks to prevent damage to the network. The security framework is evaluated by simulation in presence of malicious nodes that can launch different attacks. Simulation results show that the proposed hybrid security framework performs significantly better than other existing mechanisms.

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