By: Syed Raiyan Ali – syedraiyanali@gmail.com, Department of computer science and Engineering( Data Science ), Student of computer science and Engineering( Data Science ), Madanapalle Institute Of Technology and Science, 517325, Angallu , Andhra Pradesh.
ABSTRACT
The aggressive growth of the technologies and the growing dependency on the networks have put the focus on proper handling of the threats and incidents in the current advanced risky world. Inadequate measures of the traditional model of incident response are that they do not address today’s rapid types of attacks; typically, these methodologies imply manual actions. This paper discusses on how AI holds the promise in improving responses to and management of incidents. With the applied AI automation, machine learning, and threat intelligence, the organizations are can enhance their level of security incident detection, analysis and mitigation. The implementation of artificial intelligence in handling incidents promotes growth and efficiency of the decision-making systems not mentioning the boost in effectiveness in threat identification and handling. This article provides an understanding of factors that go with AI-driven incident response systems, their advantages, disadvantages, and their effects on ethical concerns that are relevant in current security environments.
Keywords
AI driven incident response, cyber security, Machine Learning, threat detection, automated response, real time analytics.
INTRODUCTION
Due to rapidly enhancing number and varieties of cyber threats, the approaches and tools based up on reactive incident response and management strategies are no longer sufficient. This shows that the traditional ad-hoc disruptive approaches to cybersecurity which have dominated organisational protection for years can no longer handle the complex threats that endanger contemporary digital assets[1]. The implementation of AI in handling of incidents and management, therefore represents a revolution as it takes organizations away from past reactive measures.
The Role of AI in Incident Detection and Analysis
The first advantage of AI in incident response is thus the ability of handling large volumes of data in real-time. it equally presents a menace to the traditional methods of handling logs and alerts to track threats; ordinarily, it is standard practice to have personnel reviewing the logs[2]. As it is seen AI has become decisive in surveillance activities, detection of suspicious behaviors, patterns, anomaly and threats, AI systems employ different machine learning approaches to enhance these operations and procedures more effectively.
For instance, in supervised machine learning and in artificial neural network, the system can be trained on the past events that occurred and the system can be enabled to identify similar threats that may happen in the future. Nevertheless, the unsupervised learning is more appropriate when it comes to identification of new and previously unknown threats that departs from tendencies. All combine make the effectiveness in threat detection and incidents analysis much improved because of the approaches of AI.
AI Driven Automation in Incident Response
An important part of systems for incidents response powered by AI is automation. As soon as an adverse situation is discovered, at first AI is capable to stop acting as a human who is always prepared for something bad. Protecting bad sites from fires can be done within minutes only after the threat was announced or informed about but even before the right decision has been made by some fellow human beings so that they can save themselves from harm[3]. Thus both response time decreases and harmful results from attacks reduce in many cases.
Orchestration platforms driven by intelligence, like the security orchestration, automation and response (SOAR) systems serve to combine many different mechanisms of security so as to filter incidents reporting channels. SOAR systems allow for the automation of repeating activities and coordinating responses across various security boundaries, this way letting security teams shift their focus to more complex strategies and tactical measures. The below given figure shows the AI driven Incident Response work flow.
Enhancing Incident Management with AI
Managing incidents needs more than only reacting to isolated security occurrences; incident management requires a holistic approach, whereby incidents are managed right from their detection until they are resolved[4]. This way, it is possible to prioritize threats depending on how severe they may be and their potential effects thanks to AI which enhances incident management by providing information.
Moreover, every time a new incident occurs in AI-driven systems, learning never stops; thus, refining of response strategies happens automatically leading system improvement over time. Such an adaptive learning ability is paramount in terms of keeping pace with the rapidly evolving nature of new dangers as an organization’s incident management keeps evolving hand in hand with these threats.
Challenges and Ethical Considerations
Although leveraging the advantages of Artificial Intelligence (AI) in responding to and managing incidents, it does not come relying merely on such technologies has its own challenges. One of them is potential algorithmic bias which might result in wrong threatening assessments or misunderstanding of attacks tendencies leading inadequate responses. The use of artificial intelligence also raises ethical concerns about accountability and transparency with regard to situations where automatic decisions carry weighty implications.
It is also a challenge to keep AIs up to date and improve them from time to time. Algorithms and models utilized for detecting and responding to cyber threats should evolve as they do. This will require continuous funding in research and development together with partnerships between cybersecurity experts and developers of artificial intelligence systems.
CONCLUSION
Artificial Intelligence powered incident response and management are one of the most remarkable achievement in the field of cyber security. AI increases the speed and effectiveness of detection and analysis, as well as decision-making, which decreases the effect of cyber threats on organizations. However, to get the most of AI in this specific domain, it is necessary to control the encountered problems and define the ethical issues. The AI technology will, therefore, be more prominent in providing strong and effective security measures for technologies against cyber threats in the future.
REFERENCES
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Cite As
Ali S.R. (2024) AI-DRIVEN INCIDENT RESPONSE AND MANAGEMENT, Insights2Techinfo, pp.1