Eliminate the Unknown with AI-Powered Threat Detection and Response

Eliminate the Unknown with AI-Powered Threat Detection and Response

Table of Contents:

1. Introduction
2. The Constant in Security: More Attack Surface
3. The Challenges of More Attack Surface 3.1. Explosion of Remote Workers 3.2. Hiding in the Unknown 3.3. Increasing Number of Tools and Rules 3.4. Dealing with Noise
4. The Problem of Compromise and Lack of Confidence
5. A Better Approach: Detection and Response
6. The Pillars of Effective Threat Detection and Response 6.1. Visibility Across All Attack Surface 6.2. Building Behavior-Based Detection 6.3. Providing Context at Every Stage of the Attack 6.4. Activating the Best Signals for Focus
7. Achieving Comprehensive Coverage 7.1. Public Cloud 7.2. SAS Applications 7.3. Network 7.4. Endpoint
8. Clarifying Attack Signals with AI Models
9. Leveraging AI for Triage and Prioritization
10. Integrating with Response Platforms
11. Conclusion

Detection and Response: A Better Approach to Modern Threat Protection

As technology continues to advance, the security industry faces ever-increasing challenges. The constant in the world of security is the fact that there is always more attack surface to defend. This means that the traditional approach of securing perimeters is no longer sufficient. With the rise of remote workers and the utilization of cloud-based applications, companies are expanding their attack surface like never before. This expansion leads to a higher demand for security tools, more data to be collected and analyzed, and an increasing number of security rules to be maintained.

However, with more attack surface comes more noise. The multitude of tools and rules can create a chaotic environment where security analysts are bombarded with alerts and struggle to distinguish between actionable threats and false positives. This noise can lead to burnout and make it difficult for analysts to focus on what really matters.

One of the biggest challenges companies face is the lack of visibility into their compromised state. Many organizations are unaware of whether they are currently compromised or not. This lack of knowledge is a significant problem that needs to be addressed. As an industry, we need to adopt a better approach to security, one that focuses on detection and response.

The key to effective threat detection and response lies in four pillars: visibility, behavior-based detection, providing context, and activation. First and foremost, it is crucial to have visibility across all attack surfaces. This includes public clouds, SAS applications, networks, and endpoints. By having a comprehensive view of the entire attack surface, organizations can identify and respond to threats more effectively.

Building behavior-based detection is another crucial aspect of effective threat detection and response. Traditional signature-based detection methods are no longer sufficient in today's rapidly evolving threat landscape. By utilizing AI models and specialized algorithms, it is possible to detect and identify critical behaviors that indicate an ongoing attack.

Providing context at every stage of an attack is essential for accurate and efficient threat detection. By correlating and analyzing data from various sources, such as network traffic and endpoint logs, analysts can gain a deeper understanding of the attack and prioritize their investigations accordingly.

Finally, by activating the best signals and focusing on what truly matters, organizations can improve their response capabilities. This involves triaging alerts using AI to differentiate between benign and malicious activities and prioritizing investigations based on the severity of the threat.

To achieve comprehensive coverage, organizations must extend their security measures to cover all attack surfaces. This includes public clouds, SAS applications, networks, and endpoints. Each of these areas presents unique challenges and requires specific tools and techniques to effectively detect and respond to threats.

The use of AI models is pivotal in accurately identifying and clarifying attack signals. By leveraging purpose-built models and algorithms, organizations can detect even the most sophisticated attacks and minimize false positives. This approach ensures high precision and low noise in threat detection.

Integrating with response platforms, such as CrowdStrike, further enhances the effectiveness of threat detection and response. By combining the signals from both the network and the endpoint, organizations can augment their threat intelligence and improve their ability to investigate and mitigate attacks in real-time.

In conclusion, a better approach to modern threat protection is needed in the ever-evolving world of security. By focusing on detection and response rather than relying solely on prevention, organizations can improve their security posture. This approach requires comprehensive coverage, behavior-based detection, context at every stage of the attack, and the activation of the best signals. By adopting these principles and leveraging AI technology, organizations can better protect themselves from the growing threat landscape.

Resources:

• CrowdStrike