Security Blog

In early March 2020, Interset CTO Stephan Jou had the honor of meeting with the Privacy Commissioner of Canada. The reason for the gathering: regulation for responsible and ethical AI.

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In the flurry of sessions, meetings, and the expo floor, Security, Risk and Governance team noted five key takeaways which stood out during the RSA Security Conference 2020 in San Francisco. These takeaways were echoed from RSA sessions to individual talks surrounding the current state of security and what we need to do as security professionals to be successful in an ever-changing world.

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The talent war is real in security operations. There is simply too much going on, and not enough skilled resources to effectively address the challenge. One of the key aspects of AI in security is about intelligent automation, which empowers your scarce resources to significantly accelerate detecting and addressing REAL threats; and rescues them from the sea of false positives and potentially catastrophic oversights.

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Insider threat could be an intentionally malicious employee who is stealing intellectual property from your organization or an innocent employee whose actions are inadvertently placing risk to your organization. How can we detect such threats? The answer, of course, is unsupervised anomaly detection.

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Whether you’re building a threat detection system using data science or evaluating a security vendor, this blog can serve as a guide to understanding how you can identify unusual behaviors in your enterprise with data science.

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Machine learning has the power to transform your security operations, but as with any powerful technology, it needs to be approached strategically. Interset has first-hand experience with helping organizations across the world implement and operationalize machine learning in their SOCs, and has identified four best practices that are critical for achieving success.

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