Abstract
Purpose: Because of the apparent rapid advancement in the field of information and communication technology and its constant connection to the internet, customer and organizational data have become vulnerable to cyber-attacks, necessitating the explanation of solutions to ensure the security and protection of information throughout the industry. Today, it is critical for governments and major corporations to implement cybersecurity systems to ensure the confidentiality and security of data in the face of cyber-attacks. As community-based fully systems have become more important in today's society, they've become targets for malicious actions, prompting both industry and the research community to place a greater emphasis on resolving community intrusion detection difficulties. In network intrusion detection challenges, gadget examining algorithms have proven to be a valuable tool. Design/Methodology/Approach: This research provided a fully unique architecture for attack node mitigation as a result of the use of a novel type and encryption mechanism. First, the UNSW-NB15 dataset is received and separated into training and testing data. Within the Training section, information is first and foremost pre-processed, and capabilities are extracted. The relevant features are then chosen using the Taxicab Woodpecker Mating algorithm (TWMA). The BRELU-ResNet classifier is then used to classify the attacked and non-attacked data. The typical statistics are encrypted using the ESHP-ECC method, which is then saved in the security log report. Following that, the shortest distance will be calculated using Euclidean distance. Finally, the information is decrypted utilizing a set of ideas known as DSHP-ECC. If the entry appears in the log record while testing, it is marked as attacked statistics and will not be communicated. The method of detecting cyber-assaults will continue if it is not detected. Findings/Result: The analysis is based on the UNSW-NB 15 dataset, which shows that the proposed approach achieves an excessive security level of 93.75 percent. Originality/Value: This experimental-based research article examines the malicious activities in the cyberspace and mitigated by using a SHP-ECC mechanism. Paper Type: Research Article
Highlights
Cyber security is a major concern for a wide range of businesses, agencies, government entities, and individuals all around the world
The proposed technique is implemented in Matlab, and the data are taken from the UNSW-NB 15 dataset, which is freely available on the internet
The experimentation assessment is completed, with an overall performance evaluation and comparative analysis of the offered methods in terms of some overall performance indicators to validate the effectiveness of the given set of rules
Summary
Cyber security is a major concern for a wide range of businesses, agencies, government entities, and individuals all around the world. According to Buczak and given in [1], cyber security is the total of all technology and methods for tracking and preventing unauthorized access, modification, misuse, and denial of service to computer networks and assets This involves inclinations to give access to labeled content, as well as community-on-hand infrastructure. The improvement and augmentation of cyber-attack detection structures have been stimulated by these dangers, as well as others that are expected to emerge in the future [3] This shift in the risk landscape is the result of the increased threat of cyber-attacks, which are regularly gaining control of all household, organizational, and business capacities. Several anomaly detection techniques are incorporated to tackle the problems and hazards encountered throughout the assault detection process These strategies are combined and used through the use of a variety of machine learning algorithms [7]. Phase five is the final section of the report, and it concludes with suggestions for further research
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