Time is of the essence, but pressures abound and skills and resources are limited. How is a security team supposed to cope with attackers’ increased sophistication and focus? The answer may lie in cyber forensics.

Imagine if the analysts on your security team could be empowered to use their human intuition and logical deduction to retrace the activities of an attacker. The legacy of cyber forensics is that of a specialized few only being called upon when a situation was dire. Now, cyber forensics approaches are becoming crucial when it comes to determining the type, size and scope of a breach or attack. This growing significance means the practice has to evolve. Security teams must become more self-sufficient in order to identify and remediate gaps in their organization’s security posture.

With this in mind, IBM introduced its IBM Security QRadar Incident Forensics™ solution. It allows for a broader set of the security team — not just data scientists or trained forensics investigators — to retrace an attacker’s steps, visualize frequency-based entity-to-entity relationships and identify suspicious activities based on built-in rules that operate on the content of the conversation, such as document text or email content, rather than just the metadata. For big data analytics, this solution also does the following:

  • Performs the most prevalent use case — search-driven ad hoc investigative analysis — with no additional implementation overhead;
  • Provides a robust indexing solution to look at data in the context of a security incident and quickly develop an understanding that will enable a data scientist to build custom algorithms that operate across the wider data set to become more proactive.

Download: Ponemon Institute Study on Network Forensic Investigations

This approach to helping address incident response requirements provides a single platform in which organizations can encapsulate the core set of forensics tools and apply the QRadar principle of delivering security intelligence. The tools sift through data, perform analyses and visualize different perspectives, while the intelligence improves enterprise-wide productivity by planting guideposts in the data and automating crucial elements of the forensics.

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