From the report, “We live in incredible times, where we trust more of our lives to machines that are becoming ever more powerful. We cannot leave the doors to our “digital kingdoms” wide open. Adversaries, both nation-states and for-profit malicious actors, have access to a seemingly unlimited supply of “all access keys”. Our responsibility is to revoke and disable these keys or to at least make that access as difficult as possible through thoughtful defense-in-depth security controls. These controls should not just rely solely on the “next gen” version of a well-known technology. Truly different types of protection and detection technologies need to be layered in order to create the strongest possible defense.” Read on to find out more.

From the report, “With endpoint security products continuing to be at the tip of the spear of cyber defenses for years to come, the question is how to ensure the best possible security posture. No matter which way an endpoint security buyer turns, there is no one magic bullet. It is likely that a layered approach with multiple different technologies working together is required.” Read on to find out why.

From the report, “An OS-Centric Positive Security isn’t a silver bullet, but it can be a tremendously valuable and complementary defense mechanism—your second or last line of defense. The majority of endpoint security solutions deployed today are based on the Negative Security model; so, it’s time to add a Positive Security solution to strengthen your endpoint protection.” Read on to find out more.

From the report, “Machine Learning (ML) is based around the idea machines can learn from data. ML techniques have been around for a very long time. In recent years, their use has exploded thanks to advancements in elastic cloud computing and big data. Now, ML is commonly used in fields as diverse as medical research, fraud detection, smart cars, online search and electronic commerce personalization and recommendations, to name just a few. ML has recently become the shiny new object for security and is the foundational pillar of products such as next-generation antivirus (NGAV) and User and Entity Behavior Analytics (UEBA). While most of these products have promised to be a “silver bullet” against malware, complete protection remains illusive. In fact, for a number of reasons, ML is more likely to detect and cure cancer than to stop all of today’s advanced threats. As far-fetched as this may sound, a detailed look at the distinctions between cancer detection and malware detection quickly demonstrate why this statement is true. Let’s have a look at why ML will only get you so far and what you can do about it. ” Read on to find out more.