Title: Push and nuke attacks detection using DNN-HHO algorithm

Authors: Veer Sain Dixit; Akanksha Bansal Chopra

Addresses: Department of Computer Science, ARSD College, University of Delhi, New Delhi, India ' Department of Computer Science, SPM College, University of Delhi, New Delhi, India

Abstract: Collaborative recommender systems are widely used as a tool to offer recommendation for a product to its users. These systems produce recommendations to its users using information based on user-item ratings. However, these systems are highly vulnerable to biased ratings injected by malicious users. These biased ratings lead to attacks, namely, push attacks and nuke attacks that degrade the performance of collaborative recommender systems. To handle this problem, the paper proposes a novel model to improve the detection of attack profiles in collaborative recommender systems by using a hybrid approach. The proposed algorithm is then compared with baseline algorithms. The study also evaluates and compares various measure metrics for both proposed and traditional algorithms.

Keywords: push attack; nuke attack; DNN-HHO.

DOI: 10.1504/IJICS.2023.128816

International Journal of Information and Computer Security, 2023 Vol.20 No.3/4, pp.248 - 268

Received: 04 Mar 2021
Accepted: 11 Apr 2021
Published online: 07 Feb 2023 *

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