Open Access

ARTICLE

Blockchain: Secured Solution for Signature Transfer in Distributed Intrusion Detection System

by Shraddha R. Khonde^1,2,*, Venugopal Ulagamuthalvi¹

1 Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, 600119, India
2 Department of Computer Engineering, M.E.S. College of Engineering, S. P. Pune University, Pune, 411001, India

* Corresponding Author: Shraddha R. Khonde. Email:

Computer Systems Science and Engineering 2022, 40(1), 37-51. https://doi.org/10.32604/csse.2022.017130

Received 21 January 2021; Accepted 08 April 2021; Issue published 26 August 2021

Abstract

Exchange of data in networks necessitates provision of security and confidentiality. Most networks compromised by intruders are those where the exchange of data is at high risk. The main objective of this paper is to present a solution for secure exchange of attack signatures between the nodes of a distributed network. Malicious activities are monitored and detected by the Intrusion Detection System (IDS) that operates with nodes connected to a distributed network. The IDS operates in two phases, where the first phase consists of detection of anomaly attacks using an ensemble of classifiers such as Random forest, Convolutional neural network, and XGBoost along with genetic algorithm to improve the performance of IDS. The novel attacks detected in this phase are converted into signatures and exchanged further through the network using the blockchain framework in the second phase. This phase uses the cryptosystem as part of the blockchain to store data and secure it at a higher level. The blockchain is implemented using the Hyperledger Fabric v1.0 and v2.0, to create a prototype for secure signature transfer. It exchanges signatures in a much more secured manner using the blockchain architecture when implemented with version 2.0 of Hyperledger Fabric. The performance of the proposed blockchain system is evaluated on UNSW NB15 dataset. Blockchain performance has been evaluated in terms of execution time, average latency, throughput and transaction processing time. Experimental evidence of the proposed IDS system demonstrates improved performance with accuracy, detection rate and false alarm rate (FAR) as key parameters used. Accuracy and detection rate increase by 2% and 3% respectively whereas FAR reduces by 1.7%.

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Keywords

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