Comprehensive Review of Artificial Intelligence and Statistical Approaches in Distributed Denial of Service Attack and Defense Methods
| Autor: | Wafaa Mustafa Abduallah, Salama A. Mostafa, Mazin Abed Mohammed, Aida Mustapha, Bashar Ahmed Khalaf |
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| Rok vydání: | 2019 |
| Předmět: |
General Computer Science
business.industry Computer science General Engineering DDoS defense 020206 networking & telecommunications Denial-of-service attack 02 engineering and technology statistical technique DDoS attack Identification (information) Attack model artificial intelligence technique 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing General Materials Science lcsh:Electrical engineering. Electronics. Nuclear engineering Artificial intelligence Electrical and Electronic Engineering business lcsh:TK1-9971 |
| Zdroj: | IEEE Access, Vol 7, Pp 51691-51713 (2019) |
| ISSN: | 2169-3536 |
| DOI: | 10.1109/access.2019.2908998 |
| Popis: | Until now, an effective defense method against Distributed Denial of Service (DDoS) attacks is yet to be offered by security systems. Incidents of serious damage due to DDoS attacks have been increasing, thereby leading to an urgent need for new attack identification, mitigation, and prevention mechanisms. To prevent DDoS attacks, the basic features of the attacks need to be dynamically analyzed because their patterns, ports, and protocols or operation mechanisms are rapidly changed and manipulated. Most of the proposed DDoS defense methods have different types of drawbacks and limitations. Some of these methods have signature-based defense mechanisms that fail to identify new attacks and others have anomaly-based defense mechanisms that are limited to specific types of DDoS attacks and yet to be applied in open environments. Subsequently, extensive research on applying artificial intelligence and statistical techniques in the defense methods has been conducted in order to identify, mitigate, and prevent these attacks. However, the most appropriate and effective defense features, mechanisms, techniques, and methods for handling such attacks remain to be an open question. This review paper focuses on the most common defense methods against DDoS attacks that adopt artificial intelligence and statistical approaches. Additionally, the review classifies and illustrates the attack types, the testing properties, the evaluation methods and the testing datasets that are utilized in the methodology of the proposed defense methods. Finally, this review provides a guideline and possible points of encampments for developing improved solution models of defense methods against DDoS attacks. |
| Databáze: | OpenAIRE |
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