Fuzzy logic-based DDoS attacks and network traffic anomaly detection methods: Classification, overview, and future perspectives

服务拒绝攻击 计算机安全 计算机科学 声誉 异常检测 入侵检测系统 应用层DDoS攻击 政府(语言学) 业务 风险分析(工程) 互联网 数据挖掘 万维网 社会科学 语言学 哲学 社会学
作者
Danial Javaheri,Saeid Gorgin,Jeong–A Lee,Mohammad Masdari
出处
期刊:Information Sciences [Elsevier]
卷期号:626: 315-338 被引量:53
标识
DOI:10.1016/j.ins.2023.01.067
摘要

Nowadays, cybersecurity challenges and their ever-growing complexity are the main concerns for various information technology-driven organizations and companies. Although several intrusion detection systems have been introduced in an attempt to deal with zero-day cybersecurity attacks, computer systems are still highly vulnerable to various types of distributed denial of service (DDoS) attacks. This complicated cyber-attack caused many system failures and service disruptions, resulting in billions of dollars of financial loss and irrecoverable reputation damage in recent years. Considering the nonnegligible importance of business continuity in the Industry 4.0 era, this paper presents a comprehensive, systematic survey of DDoS attacks. It also proposes a hierarchy for this severe cyber threat, besides conducting deep comparisons from various perspectives between the studies published by reputed venues in this area. Furthermore, this paper recommends the most effective defensive strategies, with a focus on recently offered fuzzy-based detection methods, to mitigate such threats and bridge the gaps existing in the current intrusion detection systems and related works. The outcomes and key findings of this survey paper are highly advantageous for private companies, enterprises, and government agencies to be implemented in their local or global businesses to significantly improve business sustainability.
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