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

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Title: Fuzzy logic-based DDoS attacks and network traffic anomaly detection methods: Classification, overview, and future perspectives.
Authors: Javaheri, Danial1 (AUTHOR) javaheri@chosun.ac.kr, Gorgin, Saeid1 (AUTHOR) gorgin@chosun.ac.kr, Lee, Jeong-A1 (AUTHOR) jalee@chosun.ac.kr, Masdari, Mohammad1,2 (AUTHOR) m.masdari@iaurmia.ac.ir
Source: Information Sciences. May2023, Vol. 626, p315-338. 24p.
Subjects: Denial of service attacks, Anomaly detection (Computer security), Traffic monitoring, Cyberterrorism, Computer systems, System failures, Quality of service, Data security
Abstract: 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. [ABSTRACT FROM AUTHOR]
Copyright of Information Sciences is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 162503790
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PubType: Periodical
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  Data: Fuzzy logic-based DDoS attacks and network traffic anomaly detection methods: Classification, overview, and future perspectives.
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  Data: <searchLink fieldCode="AR" term="%22Javaheri%2C+Danial%22">Javaheri, Danial</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> javaheri@chosun.ac.kr</i><br /><searchLink fieldCode="AR" term="%22Gorgin%2C+Saeid%22">Gorgin, Saeid</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> gorgin@chosun.ac.kr</i><br /><searchLink fieldCode="AR" term="%22Lee%2C+Jeong-A%22">Lee, Jeong-A</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> jalee@chosun.ac.kr</i><br /><searchLink fieldCode="AR" term="%22Masdari%2C+Mohammad%22">Masdari, Mohammad</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> m.masdari@iaurmia.ac.ir</i>
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  Data: <searchLink fieldCode="JN" term="%22Information+Sciences%22">Information Sciences</searchLink>. May2023, Vol. 626, p315-338. 24p.
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  Data: <searchLink fieldCode="DE" term="%22Denial+of+service+attacks%22">Denial of service attacks</searchLink><br /><searchLink fieldCode="DE" term="%22Anomaly+detection+%28Computer+security%29%22">Anomaly detection (Computer security)</searchLink><br /><searchLink fieldCode="DE" term="%22Traffic+monitoring%22">Traffic monitoring</searchLink><br /><searchLink fieldCode="DE" term="%22Cyberterrorism%22">Cyberterrorism</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+systems%22">Computer systems</searchLink><br /><searchLink fieldCode="DE" term="%22System+failures%22">System failures</searchLink><br /><searchLink fieldCode="DE" term="%22Quality+of+service%22">Quality of service</searchLink><br /><searchLink fieldCode="DE" term="%22Data+security%22">Data security</searchLink>
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  Data: 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. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Information Sciences is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1016/j.ins.2023.01.067
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      – Code: eng
        Text: English
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        PageCount: 24
        StartPage: 315
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      – SubjectFull: Denial of service attacks
        Type: general
      – SubjectFull: Anomaly detection (Computer security)
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      – SubjectFull: Traffic monitoring
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      – SubjectFull: Cyberterrorism
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      – SubjectFull: Computer systems
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      – SubjectFull: System failures
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      – SubjectFull: Quality of service
        Type: general
      – SubjectFull: Data security
        Type: general
    Titles:
      – TitleFull: Fuzzy logic-based DDoS attacks and network traffic anomaly detection methods: Classification, overview, and future perspectives.
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            NameFull: Javaheri, Danial
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            NameFull: Gorgin, Saeid
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            NameFull: Lee, Jeong-A
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              M: 05
              Text: May2023
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