Intelligent CIO Middle East Issue 30 | Page 60

FEATURE: AI ////////////////////////////////////////////////////////////////////////// By leveraging AI to automate the manual and time-consuming analysis of security events, AI can condense weeks or months of work into minutes, reducing the time spent on threat investigations by up to 90% helping SOC teams to focus on data loss prevention and mitigation. Therefore, cybersecurity experts are confident that AI can augment SOC teams to make operations more efficient, as well as detect the early signs of attacks in real time before key assets are stolen or damaged. What are some of the use cases for machine learning/AI technologies today? Why should CISOs care about machine learning? take preventive actions even before security threats manifest. With digital transformation, the explosion of connected devices, and the Internet of Things, cybersecurity experts have a lot on their plate. More connected devices equate to more traffic, more attack vectors, more attempts at security breaches and a lot more data that needs to be analysed. What are the prerequisites to deploying machine learning technologies? Add to this, today’s enterprises generate tremendous amounts of data by simply doing business. Human element alone won’t be enough to capture, analyse and mitigate, this amount of data. Thus, CISOs will need all the help they can get to prevent security incidents and respond to threats where machine learning can be one step in coping with its sheer complexity Will AI and machine learning drive the future of cybersecurity? Cybersecurity threats evolve with technology and adjust to overcome protection mechanisms. As a result, information security analysts must focus on mitigating the most severe risks first - and in an enterprise, this is a substantial effort. In this context, machine learning speeds up the process of initial risk identification and classification, which enables security teams to better manage their incident response function, and more importantly, 60 INTELLIGENTCIO In my opinion, the human element is essential to the development of viable machine learning and AI solutions in cybersecurity. Machine learning and AI need human interaction and ‘training’ to continue to learn and improve, correcting for false positives, and detecting cybercriminal innovations, as well as tailoring learning algorithms to our own problem domain. Man and machine working together. While we employ artificial intelligence in several production systems already, we’re working against skilled counterparts who are doing their best to not get detected. This means our approach needs to evolve over time, and we need to also keep evolving our AI- powered systems to become ever better at preventing and detecting threats in time. Will this help to automate key security operations? Many enterprises are establishing security operations centres (SOCs) in response to the rising tide of cyberattacks. Those SOCs can play a vital role in optimising security and improving incident response. However, traditional SOCs are struggling in addressing security threats effectively when it is made of the human factor only. One of the most common use cases is using AI and machine learning as part of the new SOCs architecture. As per Forbes, there are many other use cases where AI and machine learning are being used today such as data security, fraud detections and online trading. What are the risks involved with machine-learning if people are not adequately trained to understand and use these systems? As I mentioned above, the human element is essential to the development of viable machine learning and AI solutions in cybersecurity. Machine learning and AI need human interaction and ‘training’ to continue to learn and improve, correcting for false positives and detecting cybercriminal innovations, as well as tailoring learning algorithms to our own problem domain. Where does the region currently stand in terms of the application of machine learning for cybersecurity? How do you see it moving forward? The Middle East region is adopting technologies at a fast pace. Governments and companies in this region have taken cybersecurity seriously from the first moment focusing on developing a serious and cohesive regulatory framework around information security and data protection including the deployment of AI and machine learning to automate security operations and achieve early detection of threats. n www.intelligentcio.com