September 1, 2022
As days are passing by, the hunt to create smart machines and technologies is advancing. Day by day, we are creating intelligent bots and machines to make our life easier and more convenient. AI comes on top of it, it has enabled humans to utilize the technology at its best. Now we are seeing AI-driven objects in our day-to-day life.
These days, most organizations have Security Operation Center (SOC), either internally or through some vendor. In a SOC, the SOC Analysts are responsible for monitoring logs, creating models, investigating alerts, etc. They are the first line of defense in an organization. SOC Analysts are generally bombarded with alerts, out of which most are false positives. This alert fatigue reduces the productivity of SOC Analysts. That's when AI can bring a change.
AI is highly useful when it comes to automated detection and response in cyber security with the use of bots. These bots use AI/ML-based algorithms to perform the operations they are programmed for. Bots automate the process of detection through their advanced algorithm-based training and real-time behavior pattern analysis. These AI Bots get smarter day by day as their algorithm allows them to improve their abilities by learning from real-time events. Next-Generation Firewalls and SIEM Tools are made smarter using these AI-based technologies. The best part about AI is, it supports a vast amount of integrations and can be deployed almost anywhere. Automation in cyber security is the next big thing we are looking for, and AI is making it possible.
As time passes, we get to know about new threats and vulnerabilities being introduced. Day by day, even attackers are advancing in their attacking methodologies. Cybercriminals are always in quest of new vulnerabilities that they can exploit to their advantage. Mainly, SOC Analysts follow a pre-defined method for their threat hunting practices which sometimes is not sufficient enough to protect an organization from upcoming threats and emerging attack techniques. Zero Day vulnerabilities like scenarios make it even tougher for an Analyst to tackle hard situations like real-time attacks which turn into breaches costing millions of dollars.
At such places, AI automates the Threat hunting process. In general, threat hunters use signatures and IOCs based methods to hunt for threats, they are effective for already known threats but new threats may go undetected. Undiscovered threats have been known to cause the most amount of damage. AI works based on the behavior and unusual patterns of various entities, which is why it detects abnormalities beforehand. Making the use of AI will not only raise the effectiveness in threat hunting but also reduce the number of false positives by a marginal amount.
AI and ML are highly effective in Endpoint security management. When combined with endpoint security solutions, AI brings the power of autonomous scanning and detection of files, processes, and executions at the endpoints. Malware is a huge concern for the endpoints, stealth malware is capable of evading protection software, in such cases, AI-based detection can be implemented as it will not only verify the signature but also the behavior of malicious software. This will prevent the systems from Hoaxes, Remote Access Trojans (RAT), Worms, etc.
The biggest challenge faced by a SOC Analyst is finding threats from a huge chunk of data. Finding threats in a huge number of unstructured data becomes the task of finding a needle in the haystack. Thankfully, AI-based algorithms are now made available which are capable of structuring, sorting, and indexing the data. This enables data to be visualized and perform analytics in a neat and structured manner. Life of SOC Analysts becomes easier and analysis makes a better impact enhancing the overall security posture of an organization. Modern data SIEM and XSIAM Tools use AI/ML-based algorithms to generate analytical models and they are capable of writing rules automatically on the behalf of an Analyst. Due to automation in model creation, as soon as the data ingestion begins, AI-based models start detecting anomalies and malicious patterns. Implementation and utilization of such technologies have been proving to be highly effective in improving the life of an Analyst and the security posture as well.
Identifying, Assessing, and Managing existing vulnerabilities plays a vital role in the overall security of an organization. The latest Vulnerability Assessment and Penetration Testing tools use AI-based algorithms to detect and identify unknown vulnerabilities. Once they are identified and flagged as per their severity, the next big challenge is to manage them.
Where AI brings power to it. AI enables the integration of multiple vulnerability databases which is key to the management of existing security weaknesses of the organization. Databases like CVE, NVD, and others can be taken into consideration and implemented with AI-based analytics to the SIEM and XDR platforms but are not limited to it.
Overall, AI has been improving day by day, it can be assumed clearly that this can be the future of cyber security. The use of AI in the latest tools for security has been proving its effectiveness without leaving any doubt. With the advancement of AI/ML into cyber security, the life of an Analyst is getting better. Reducing false positives, tackling alert fatigue, detecting bad bots, and improving EDR in many places, AI has brought a positive change. As they are capable of learning more through real-time analytics, they get better day by day which makes it tougher for new threats and vulnerabilities to evade the security infrastructure. The day will come soon when we can see AI handling security like a pro.
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