4 Ways ML Can Strengthen An Organisation’s Security Infrastructure
This ever-evolving tech-driven world is witnessing one of the most dangerous eras of cyber attacks. With this skyrocketing number of data breaches and hacks, it has become imperative for organisations across the world to adopt the new waves of technological advancements. Talking about advanced techs, artificial intelligence (AI) and machine learning (ML) definitely tops the list, Machine learning and artificial intelligence in security are the fast-growing trends and by implementing  AI and ML, organisations can strengthen their cybersecurity infrastructure and can mitigate cyber threats to a great extent. It can help business in threat analysing and make them better in responding to attacks, by automating a lot of tasks that used to be done by humans. Security is important and to make cybersecurity stronger, it is also important to have an environment with all the latest, advanced technologies. In this article, we are going to see some of the top machine learning and artificial intelligence use cases in cybersecurity. Beforehand Detection of Vulnerabilities To carry out a cyber attack it is mandatory for attackers to find out vulnerabilities, and once a flaw is found, attackers exploit that. Utilising ML and AI in cybersecurity infrastructure, organisations can develop or upgrade systems to scan for loopholes and vulnerabilities. Also, ML algorithms can help businesses detect malicious activity faster, which would help the cybersecurity team to act faster and better. That is not all with advanced AI systems, organisations could also have a picture of various scenarios of how hackers could exploit them. This would not only help mitigate cyber attacks but also prepare them for the upcoming attacks. Automate Tasks Cybersecurity is one of those domains that need a lot of manpower in order to keep every end working fine. However, sometimes it’s not possible to do everything, and this is where technologies like AI and ML comes in. Machine learning has the capability to automate tasks, allowing the cybersecurity professional to focus on other tasks. For example, it is not an easy task for a human to decide which vulnerability to fix first when there is a lot. Machine learning can do the sorting and let the human work on that vulnerability that seems more critical. Another example of using these sought after techs is when  there is a ransomware attack. While the machine can keep interrupting the attack, the cybersecurity professional can figure out ways to eliminate it. To Tackle Zero-Day Exploits If you know what Zero-Day exploits are then you would definitely understand the pain that cybersecurity professionals get while dealing or stopping someone from exploiting a zero-day vulnerability. Basically, a  zero-day vulnerability is a software vulnerability that is unknown to, or unaddressed by, those who should be interested in mitigating the vulnerability. So, this is where machine learning can be used to make it easier for cybersecurity professionals. By leveraging the powers of ML, one can build a system that would monitor traffic about security exploits. Meaning, if hackers are trying to intercept the traffic, it would alert the cybersecurity team that someone is trying to pwn. Basically, its like hacking the hackers. Helps In Analysing Mobile Endpoints Machine learning and artificial intelligence are already being used widely in a lot of mobile devices. However, now their application has been expanded and are now being used to analyse mobile endpoints in cybersecurity. Over the past couple of years, BYOD has gained a lot of popularity, but it is also posing a lot of security loopholes. Using machine learning, companies can analyse mobile devices and make sure they are not vulnerable and pose any threat. Machine learning-based threat detection systems can be used in the organisations’ network to keep an eye on the devices connected to the same network. And every time any loophole or vulnerability is found, it would alert the cybersecurity team to take immediate action against the device. Outlook The world is becoming more and more connected with every passing year, and along with all the technological advancements, more cyber threats are coming into the scenario. Technologies like machine learning and artificial intelligence have proved time and again their worth in this tech-driven era. So, if your organisation is not leveraging these sought after techs then the chances are really high that you are not only lagging behind in terms of business but also in terms of cybersecurity.
This ever-evolving tech-driven world is witnessing one of the most dangerous eras of cyber attacks. With this skyrocketing number of data breaches and hacks, it has become imperative for organisations across the world to adopt the new waves of technological advancements. Talking about advanced techs, artificial intelligence (AI) and machine learning (ML) definitely tops the […]
ML and AI in cybersecurity are fast-growing trends and by implementing  them, organisations can strengthen their security infrastructure
["AI (Artificial Intelligence)", "Cybersecurity", "latest technological advancements", "Machine Learning", "Network security"]
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["AI", "artificial intelligence", "machine learning", "ML", "RAG", "R", "Go", "GAN", "ViT", "programming_languages:R"]
Harshajit is a writer / blogger / vlogger. A passionate music lover whose talents range from dance to video making to cooking. Football runs in his blood. Like literally!
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