Kecerdasan Buatan untuk Security Orchestration, Automation and Response: Tinjauan Cakupan - Gustina DM, Venny; Ananda, Ananda (Jurnal Komputer Terapan, 2024)
The integration of artificial intelligence (AI) in Security Orchestration, Automation, and Response (SOAR) promises to revolutionise cybersecurity operations. The adoption of AI-powered SOAR technologies can help organisations improve their resilience to cyberattacks. Some research proposes the use of SOAR engines that can deploy customised honeypots and identify attacks, whereas others integrate artificial intelligence to improve situational understanding and response to security threats. The use of AI/ML technologies in cybersecurity can improve the effectiveness of SOC analysts in detecting, preventing, and responding to security attacks in ways such as better threat detection, automation of routine tasks, faster and more accurate data analysis, improved response to attacks, and reduced workload. Detection capabilities on the SOAR engine include HTTP IDS, Botnet, and DDoS detection, using machine learning models trained on various types of data. The SOAR engine is also equipped with other security threat detection capabilities, such as behavioural analysis, log analysis, malware analysis and threat intelligence analysis. SOAR systems equipped with artificial neural network-based machine learning are capable of analysing data in real-time and performing threat detection quickly. Thus, the use of AI technology and real-time analysis helps to reduce the workload of security professionals and increase efficiency in dealing with cyberattacks.