Risk-Aware Mitigation for MANET Routing Attacks(2012)

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Mobile Ad hoc Networks (MANET) have been highly vulnerable to attacks due to the dynamic nature of its network infrastructure. Among these attacks, routing attacks have received considerable attention since it could cause the most devastating damage to MANET. Even though there exist several intrusion response techniques to mitigate such critical attacks, existing solutions  typically attempt to isolate malicious nodes based on binary or nai¨ve fuzzy response decisions.

However, binary responses may result in the unexpected network partition, causing additional damages to the network infrastructure, and nai¨ve fuzzy responses could lead to uncertainty in countering routing attacks in MANET. In this paper, we propose a risk-aware response mechanism to systematically cope with the identified routing attacks. Our risk-aware approach is based on an extended Dempster-Shafer mathematical theory of evidence introducing a notion of importance factors. In addition, our experiments demonstrate the effectiveness of our approach with the consideration of several performance metrics.

Existing System:

Several work  addressed the intrusion response actions in MANET by isolating uncooperative nodes based on the node reputation derived from their behaviors. Such a simple response against malicious nodes often neglects possible negative side effects involved with the response actions. In MANET scenario, improper countermeasures may cause the unexpected network partition, bringing additional damages to the network infrastructure. To address the above-mentioned critical issues, more flexible and adaptive response should be investigated. The notion of risk can be adopted to support more adaptive responses to routing attacks in MANET. Subjective knowledge could be retrieved from previous experience and objective evidence could be obtained from observation while logical reasoning requires a formal foundation. Wang et al. proposed a nai¨ve fuzzy cost-sensitive intrusion response solution for MANET. Their cost model took subjective knowledge and objective evidence into account but omitted a seamless combination of two properties with logical reasoning.


However, risk assessment is still a nontrivial, challenging problem due to its involvements of subjective knowledge, objective evidence, and logical reasoning.

Proposed System:

We formally propose an extended D-S evidence model with importance factors and articulate expected properties for Dempster’s rule of combination with importance factors (DRCIF). Our Dempster’s rule of combination with importance factors is nonassociative and weighted, which has not been addressed in the literature.

We propose an adaptive risk-aware response mechanism with the extended D-S evidence model, considering damages caused by both attacks and countermeasures. The adaptiveness of our mechanism allows us to systematically cope with MANET routing attacks.

We evaluate our response mechanism against representative attack scenarios and experiments. Our results clearly demonstrate the effectiveness and scalability of our risk-aware approach.


Ø  Evidence collection

Ø  Risk assessment

Ø Decision making

Ø  Intrusion response

Ø Routing table recover

Evidence collection

In this step, Intrusion Detection System (IDS) gives an attack alert with a confidence value, and then Routing Table Change Detector (RTCD) runs to figure out how many changes on routing table are caused

by the attack.

Risk assessment

Alert confidence from IDS and the routing table changing information would be further considered as independent evidences for risk calculation and combined with the extended D-S theory. Risk of countermeasures is calculated as well during a risk assessment phase. Based on the risk of attacks and the risk of countermeasures, the entire

risk of an attack could be figured out.

Decision making

The adaptive decision module provides a flexible response decision-making mechanism, which takes risk estimation and risk tolerance into account. To adjust temporary isolation level, a user can set different thresholds to fulfill her goal.

Intrusion response

With the output from risk assessment and decision-making module, the corresponding response actions, including routing table recovery and node isolation, are carried out to mitigate attack damages in a distributed manner.

Routing table recovery

Routing table recovery is an indispensable response and should serve as the first response method after successful detection of attacks. In proactive routing protocols like OLSR, routing table recovery does not bring any additional overhead since it periodically goes with routing control messages. Also, as long as the detection of attack is positive, this response causes no negative impacts on existing routing operations.

Hardware Requirements:

•         System                        : Pentium IV 2.4 GHz.

•         Hard Disk        : 40 GB.

•         Floppy Drive   : 1.44 Mb.

•         Monitor           : 15 VGA Colour.

•         Mouse             : Logitech.

•         Ram                 : 512 Mb.

Software Requirements:

•                     Operating system :-  Windows XP Professional

•                     JDK                      :-1.5/ 1.6 and above

•                     Front End            :-  JAVA, Swing(JFC)

Click here to download Risk-Aware Mitigation for MANET Routing Attacks(2012) source code