Identifying network connection: Benign vs. DoS attack - A comparative analysis of binary classifiers

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The escalating complexity of cyber-attacks coupled with the increasing sophistication of attackers have created an imperative need for robust and adaptable defense mechanisms to ensure the security of network infrastructure. Among these threats, Denial of Service (DoS) attacks stand out prominently. These attacks focus on inundating systems with high-frequency traffic to exhaust resources and disrupt the availability of services. Consequently, the accurate and timely identification of 'DoS Attacks' is of paramount importance in upholding the integrity and functionality of networks. In this context, the present paper aims to delve into the efficacy of various binary classifiers in effectively distinguishing normal network connections from instances of 'DoS Attacks.' By undertaking this exploration, the study aims to pinpoint the classifiers that exhibit the highest level of effectiveness in tackling this specific task. Ultimately, a comprehensive understanding of which classifiers perform best in discerning these types of cyber threats can significantly contribute to enhancing the overall security posture of network infrastructures.