Integrating AI in Cybersecurity Enhances Threat Detection Capabilities, Allowing More Proactive Defense Strategies
By Yashin Manraj, CEO — Pvotal Technologies
One of the greatest fears of any business is a cyberattack, as massive data breaches can have tremendous financial and legal consequences. The advent of AI technology has made cyberattacks even scarier, as companies like Amazon have reported that they now experience as many as 750 million cyber threats a day. However, by leveraging this same technology that wrongdoers use to power their attacks, businesses can bolster their own cybersecurity.
AI has become a powerful tool for cybersecurity professionals thanks to its advanced capabilities in data analysis, and cybersecurity is all about data. Not only is the primary goal of cybersecurity to keep the organization’s data and systems safe, but one could also look at networks as a series of interconnected data points. By analyzing data about these networks, AI models can effectively identify weaknesses, incidents, and other aspects of the network that may leave it vulnerable to attacks.
How AI assists in cybersecurity responses
Enhanced anomaly detection is one of the most exciting use cases for AI in cybersecurity. AI algorithms can be trained to identify unusual patterns that may indicate cyberattacks and alert system managers to these anomalies. This is in contrast to traditional rule-based systems of cybersecurity, which can only identify cyberattacks based on pre-defined rules. In other words, traditional systems are typically only effective against known attack patterns and malware, while AI systems can be much more effective at identifying new and different threats.
On top of that, AI models can enable automated threat response. When a system identifies a potential cyberattack, certain aspects of the response can be automated to mitigate any possible damage. For example, when an anomaly is detected, the system can be automated to implement access control and lockdown policies to prevent wrongdoers from accessing the rest of the network. Automated systems can also implement network segmentation, which involves putting barriers between an affected area of the network and the rest of the system to limit the scope of an attack and prevent it from spreading.
Once these automated steps are taken, human teams can get to work addressing or reversing any damage.
How AI enables a proactive approach to cybersecurity
However, artificial intelligence isn’t only a valuable tool for cybersecurity response; it can also enable businesses and cybersecurity providers to take a proactive approach. Although it is impossible to prepare for every potential cyber threat that will come your way, a proactive approach allows business leaders to minimize or even entirely eliminate the consequences of a cybersecurity incident.
One of the most powerful cybersecurity use cases for artificial intelligence is predictive threat analysis. By analyzing historical data, AI models can predict future cyberattacks, allowing for proactive security measures to be implemented. AI models can also be used to run simulations of potential cyberattacks, enabling network operators to better prepare for how a given threat might develop and expand throughout a network.
AI can also enable improved vulnerability scanning. An AI model can be trained to constantly probe a network for vulnerabilities, identifying these weaknesses before they are exploited. This can significantly improve the speed and accuracy of vulnerability assessments. Furthermore, it’s important to note that artificial intelligence can often pick up on patterns that even the human eye could not recognize, meaning that it could be even more effective at identifying these threats than a human cybersecurity professional alone.
Why cybersecurity MSSPs should implement artificial intelligence
For MSSPs that provide cybersecurity services to businesses, these capabilities will be invaluable in allowing them to provide better service to clients and achieve greater efficiency. By automating these aspects of threat detection and risk management, MSSPs can effectively provide around-the-clock protection for businesses and their networks and, in many situations, prevent cyberattacks before they even happen. This is unquestionably the best approach to avoiding the severe consequences of a data breach.
Indeed, thanks to artificial intelligence’s abilities to help with cybersecurity functions like anomaly detection, threat response, predictive threat analysis, and vulnerability scanning, businesses can rest assured that their data is safer than ever. If you are a cybersecurity service provider and do not take advantage of the power of AI, you are leaving your clients vulnerable.
Yashin Manraj launched Pvotal Technologies following a stint in academia as a computational chemist, an engineer working on novel challenges at the nanoscale, and building more secure systems at the world’s best engineering firms. With deep technical knowledge from product development, design, business insights, and coding, he has a unique nexus to identify and solve gaps in the product pipeline.