Learn how Artificial Intelligence and Machine Learning will transform cybersecurity for the good.
Fremont, CA: AI and ML are already being employed in several futuristic technologies. Autonomous cars and machines, auto-tagging friends on Facebook posts, robotic automation to reduce manpower, and the suggestions that keep popping up on laptop screens while browsing, all these systems and functions use Artificial Intelligence and Machine Learning. Both saw enormous growth during the covid-19 pandemic due to changing operations and work processes.
Needless to say, this is just the beginning. Researchers are conducting several experiments to explore other applications of Artificial intelligence and machine learning. Wonder if Jarvis will become a real thing soon.
Will Artificial Intelligence Improve Cybersecurity?
Given how AI has enabled several innovations in almost every field of technology, it is clear that it will enable a significant improvement in cybersecurity as well. In a couple of years, system integrations and data exchange will become unavoidable. During that time, having the finest security protocols and measures to secure personal data, system applications and company details will become extremely important. And that is where AI and ML will play a critical role.
Application in Identity and Access Management
The only thing protecting a person’s data from being stolen by a hacker is his password. Most people don’t even have a strong password, and they even tend to use the same password for every purpose. If even one of such passwords is compromised, then a hacker can steal data from all available platforms. This is where biometrics comes into play.
Biometric authentication removes the need for passwords. While biometric authentication is vulnerable to attacks, its accuracy and effectiveness can be increased using AI. AI can be employed to establish biometric authentication systems that perform dynamic face recognition so that a person’s photograph cannot be used to bypass security. AI can also improve face recognition technology in such a way that it could accurately identify the person even if features like hair, beard, glasses, etc have changed.
Behavioral Analysis and Predictions
Behavioral analysis is already being utilized by many brands. For example, when you watch a sci-fi movie on Netflix, it will automatically suggest other sci-fi movies. This is used by all social media platforms as well. While similar behavioral patterns can be used to identify the user, any abnormality can be used to identify a breach. With AI and ML, one can develop technologies that can analyze human behavior, such as walking, or facial movements, and detect discrepancies.
There are several tools available that can be used to identify threats. Companies have cybersecurity teams that use these tools to identify threats. Given the rate at which cyber-attacks happen nowadays, it is not possible to neutralize these threats with the help of a couple of analysts. Hence adopting AI becomes a necessity. It is a supplementary tool for us that can be employed in a way that solves our problems without much effort. AI and ML can understand a business structure, operations, and network. The algorithms can easily process thousands of events every day and detect abnormalities that are not possible for a human to perform. And they are continuously evolving and learning, hence they are becoming better versions every day. Hence becoming better at identifying threats.
Malware could be employed to cause damage to systems, servers, and networks without the need to be physically present to cause these damages. This equipment costs millions and billions of dollars, hence a major attack could create a financial crisis. Apart from that, damage like this could tarnish the image of the company. AI and ML can effectively detect such attacks and prevent them. ML algorithm could be fed a set of ‘correct behaviors’ any deviation from which could set an alarm. These techniques can increase the efficiency of malware detection.
Artificial intelligence and Machine Learning will enable a long list of innovations using which cybersecurity could be improved three folds. A strategic application and analysis are required to identify what will work best for a certain business and the algorithms could be implemented depending upon the same.