Rajinder Kaur ¹, Monika Sachdeva ¹, Gulshan Kumar ²

Affiliations
1 Department of Computer Science Engineering, Shaheed Bhagat Singh State, Technical Campus, Ferozepur, IN
2 Department of Computer Applications, Shaheed Bhagat Singh State, Technical Campus, Ferozepur, IN

Abstract

Objectives: To reduce the dimensionality of network traffic dataset by selecting the relevant and irredundant features for accurate and quick intrusion detection. To achieve the target, we proposed a new feature selection approach based on the nature. Methods/Statistical Analysis: The proposed Modified CuttleFish Algorithm (MCFA) approach plays a crucial role in intrusion detection by selecting appropriate subset of most relevant features from huge amount of dataset. Griewank fitness function is used to calculate the fitness of the modified cuttlefish algorithm. Naive bayes classifier is employed at the generated subset of features from benchmark KDD 99 dataset in WEKA data mining tool Compare the results of proposed approach with the existing approaches of WEKA and Improved Cuttlefish Algorithm (ICFA), with different performance metrics. Findings: As per the outcomes are obtained by the WEKA Experimenter with the 9 feature selection approaches on KDD 99 10% training dataset, it has been observed that the Consistency Subset feature selection approach with Greedy stepwise search method gives higher accurate results than other approaches and from the literature survey has been found that the ICFA performs well, but still there is problem of low True positive (TP) rate and False negative (FN) rate. These problems are addressed by the proposed feature selection approach which outer perform best from others in accuracy rate (91.79%), True positive rate (0.947), false positive rate (0.025) and ROC area (0.9982) with the minimum amount of time at 19 relevant subset of features instead 41 features. As the consequence, the proposed approach is novel from existing approaches to increase the intrusion detection rate and discard the redundant and irrelevant subset of features. Application/Improvements: MCFA has improved intrusion detection rate by increasing the TP rate and decreasing the FP rate, so MCFA can be used for the real time applications of intrusion detection system.

Keywords

Accuracy, Dimensionality, Feature Selection Approach, FP Rate, Intrusion Detection, Modified Cuttlefish Algorithm, TP Rate.

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Shivam Dhuria ¹, Monika Sachdeva ², Gulshan Kumar ³

Affiliations
1 CSE, SBSSTC, Ferozepur – 152004, Punjab, IN
2 IKGPTU Main Campus, Kapurthala – 144603, Punjab, IN
3 SBSSTC, Ferozepur – 152004, Punjab, IN

Abstract

Objectives: Recognition and Handling of Insider and Outsider DDoS attacks are very important in WSN. Various schemes have been proposed in the past to fight against DDoS attacks in WSN. But they have either used a complex approach for recognizing the attack or they were not able to handle the attack efficiently after recognizing it. The presented method has followed a simplified and effective approach to recognize and handle the DDoS attack. Methods: In this paper two methods have been introduced, Authentication method is based upon a mathematical formula which is only known to legitimate nodes in the network. In data filtration method, each node in the network checks the input data volumes coming from other nodes against a threshold value to find the traffic abnormalities. Both these methods are simple and can be deployed at every node in the network. Findings: The results have been verified using the Network Simulator 2 (NS2) on various performance metrics i.e. throughput, delay, lost packets, energy consumption and PDR. It has been observed that fixing the threshold value results in recognition of attack at very early stages and blocking the communication with the attacker results in saving approx 56% energy of the network.. The threshold value can be decided as per the bandwidth usage that may vary in different applications. Improvements: The data filtration method can be enhanced in future by using historical methods so as to analyze and mitigate other severe attacks like blackhole and sinkhole attacks.

Keywords

Authentication, Data Filtration, DDoS, NS2, Threshold, WSN.

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