The next big thing in information technology and data security is the incorporation of machine learning and artificial intelligence systems. These systems are at the frontier of a new wave of technological developments transforming how companies and organizations combat cybersecurity attacks.
Traditionally, cybersecurity has relied on rules-based or signature-based pattern matching. With anti-virus (AV) for example, researchers at AV companies find malware and generate signatures that can be used to check files on an endpoint to see if they match a signature of known malware. This means that one can only detect malware that is known, and that matches a virus definition or signature.
With artificial intelligence, machine learning can provide an alternative to traditional cybersecurity solutions. What is extremely difficult for traditional solutions to combat is now a walk in the park for machine learning and artificial intelligence.
Artificial Intelligence and Machine Learning for Cybersecurity
Both these systems can be used to identify and safeguard systems from some of the latest cybersecurity threats. It is no secret that emerging threats work so fast making it extremely challenging for traditional security tools to pinpoint and combat the attack. This is where ML and MI come into play.
These systems can be applied to improve cybersecurity in the following ways:
- Detection and Prediction of New, Complex Threats
The nature of malware attacks is that they evolve over time, therefore, organizations need more dynamic approaches- like AI and ML systems- when working against these attacks. Artificial intelligence systems powered by machine learning leverage information garnered from previous attacks. They process the nature of past attacks and threats and identify other potential attacks that could occur in the same vein or style.
Due to the fact that hackers consistently build upon older threats – including new abilities or tweaking previously used samples to build out a malware family – utilizing AI and ML systems to look out for and provide notification of emerging attacks could be incredibly beneficial to stemming the tide of zero-day threats.
- Reduced Burden on Cybersecurity Personnel
Applying machine learning and artificial intelligence to improve cybersecurity saves an organization a considerable amount of time and money that would have otherwise been spent by cybersecurity experts.
Machine learning is most effective as a tool when it has access to a large pool of data to learn and analyze from, reducing attack surfaces through predictive analytics. The volume of security alerts that appear daily can be very overwhelming for the security team. Without the assistance of these systems, these experts would be forced to spend copious amounts of time identifying these threats on their own, or worse, waiting until an attack occurs for them to carry out diagnostic investigations.
Artificial intelligence and machine learning will become one of the key components of next-generation security, enabling elevated degrees of cybersecurity. Using AI and ML to achieve cyber hygiene and combat attacks from cyberattackers is the breakthrough idea that will help organizations secure their modern IT environments against the ever-evolving threat landscape.
