Abstract
Purpose: When communication networks and the internet of things are integrated into business control systems, they become more vulnerable to cyber-attacks, which can have disastrous consequences. An Intrusion Detection System is critical for identifying and blocking attacks in IoT networks. As a result, utilizing a unique Classification and Encryption approach, this article offered a novel architecture for attack node mitigation. Design/Methodology/Approach: This study reviews the current status of various cyber-attack detection models and their mitigation techniques. The proposed model works so that the system is first trained on the dataset, including the DDoS attack and ransomware components. The model examines if it contains malware from DDoS or Ransomware. When tested, we use trained information or a data set to provide the results on attack existence and what sort of attack we offer the extracted characteristics of the input. When the model identifies the attacker node, it is removed via the BAIT technique from the network. Findings/Result: Recognizing the importance of information security is critical to combating cybercrime and encouraging cyber security. There are numerous tactics, strategies, and equipment currently in use to detect intrusion in a computer network, and continuing research is being conducted to improve their ability to detect intrusion. The basic version of a cyber-assault detection and mitigation system using the BRELU-RESNET method was evaluated in this study. Originality/Value: This review-based research article examines the present state of cyber-attack detection and mitigation, as well as the research gaps and research goals. Paper Type: Review-based research analysis
Highlights
The virtual revolution of big-scale production environments promotes the usage of massive statistics analytics in solving plant outages, equipment breakdowns, fault prediction, and ensuring cybersecurity through the extension of computer networks and interconnectivity of computer systems in cyberphysical structures [1] [2]
The key database seeks string is "cyber-attack detection and mitigation" to raise awareness of the many processes that go into place to detect cyber-attacks. 3.2.2 Database searches: We developed a list of probable databases for laptop technological know-how study using the Google search engine
The Cyber-Physical System (CPS) connects the physical and electronic worlds and is typically used for industrial manufacturing control systems (ICS) to allow people to understand all types of necessary information in real-time
Summary
The virtual revolution of big-scale production environments promotes the usage of massive statistics analytics in solving plant outages, equipment breakdowns, fault prediction, and ensuring cybersecurity through the extension of computer networks and interconnectivity of computer systems in cyberphysical structures [1] [2]. The topic of cyber-defense has aroused academics' interest in recent years, as cyber-physical networks have evolved into extremely dangerous cyber-assaults that might endanger any section of the unexploited cyber surface [3] This highlights the need of implementing area green identification algorithms and robust solution mechanisms that protect both the cyber and physical parts of the infrastructure - a necessary precondition for improving operational technologies [3] [4]. Since CPS are so essential to contemporary society's day-to-day activities, they've become a tempting choice for cybercriminals Because of their extensive use, their attack surface has grown significantly [9]. Various components of the CPS, like every other physical control device, will malfunction at the same time Both faults and attacks can cause the machine to behave abnormally, but the consequences can be somewhat different. When the model identifies the attacker node, it is removed via the BAIT technique from the network
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