Abstract
Cybersecurity is very crucial in the digital age in order to safeguard the availability, confidentiality, and integrity of data and systems. Mitigation techniques used in the industry include Multi-factor Authentication (MFA), Incident Response Planning (IRP), Security Information and Event Management (SIEM), and Signature-based and Heuristic Detection.
MFA is employed as an additional layer of protection in several sectors to help prevent unauthorized access to sensitive data. IRP is a plan in place to address cybersecurity problems efficiently and expeditiously. SIEM offers real-time analysis and alerts the system of threats and vulnerabilities. Heuristic-based detection relies on detecting anomalies when it comes to the behavior of files and domains, whereas signature-based detection uses predefined malware codes and known signatures to help identify malware.
Artificial intelligence along with machine learning could enhance cyber detection and response by utilizing a vast amount of data and algorithms to help identify trends, make predictions, and take actions without human supervision. This paper discusses how this proposal can be accomplished and could help defeat malware.
Faculty Advisor/Mentor
Saltuk Karahan
Document Type
Paper
Disciplines
Artificial Intelligence and Robotics | Digital Communications and Networking | Information Security
DOI
10.25776/gqvy-fh28
Publication Date
4-4-2023
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Included in
Artificial Intelligence and Robotics Commons, Digital Communications and Networking Commons, Information Security Commons
Leveraging Artificial Intelligence and Machine Learning for Enhanced Cybersecurity: A Proposal to Defeat Malware
Cybersecurity is very crucial in the digital age in order to safeguard the availability, confidentiality, and integrity of data and systems. Mitigation techniques used in the industry include Multi-factor Authentication (MFA), Incident Response Planning (IRP), Security Information and Event Management (SIEM), and Signature-based and Heuristic Detection.
MFA is employed as an additional layer of protection in several sectors to help prevent unauthorized access to sensitive data. IRP is a plan in place to address cybersecurity problems efficiently and expeditiously. SIEM offers real-time analysis and alerts the system of threats and vulnerabilities. Heuristic-based detection relies on detecting anomalies when it comes to the behavior of files and domains, whereas signature-based detection uses predefined malware codes and known signatures to help identify malware.
Artificial intelligence along with machine learning could enhance cyber detection and response by utilizing a vast amount of data and algorithms to help identify trends, make predictions, and take actions without human supervision. This paper discusses how this proposal can be accomplished and could help defeat malware.