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Title
شناسایی حملات DDoS با استفاده از الگو ریتم بهبود یافته مبتنی بر شبکه عصبی مصنوعی برای شبکه های اینترنت اشیا
Type of Research Thesis
Keywords
اینترنت اشیا، شبکه های عصبی مصنوعی(ANN)، کاهش ابعاد، تشخیص حمله، حمله DDoS، سیستم تشخیص نفوذ
Abstract
Information security, computer system protection, and data integrity and confidentiality have long been political, economic, social, and national issues that touch everyone[1], [2]. With the growing usage of computers, smart gadgets, and the Internet of Things (IoT) in everyday life, information security is becoming more important. According to Arbor [3], cyber-attacks or information security breaches are on the rise because hackers are continually developing new attacks, tools, and tactics to target networks, making it difficult to halt or even monitor them. These attacks have made certain firms less dependent on communication networks. because they are facing spyware, password theft, denial of service, and other assaults. According to A10 network services website statistics [4], major companies have been attacked by this form of attack, causing significant material harm. In February 2020, Google and Amazon were assaulted at 2.5 terabytes per second. The attack reached 2.3 Tbps. On 20 September 2016, cyber security expert Brian Krebs' site was hacked at over 620 Gbps, while on 28 February 2018, software developer platform GitHub was attacked at 1.35 terabytes per second for 20 minutes. Today we need a reliable approach to reduce electronic attacks like denial-of-service (DoS) attacks or identify them before the attacker gets control of the system, which disrupts service delivery by deprives deserving people, harming the system.
Researchers Hayder Jalo (Student)، Mohsen Heydarian (Primary Advisor)، Hossein Abbasimehr (Advisor)