Deviation From Normal Does Not Always Mean Malicious Intent

Deviation From Normal Does Not Always Mean Malicious Intent

An approach to solving cybersecurity problems is to use machine learning to baseline normal behaviors so that deviations from normal can be identified.  This, at first glance makes perfect sense.  However, there are flaws that must be considered and avoided. 

Threat Intelligence: Non-Malicious Deviations

One of the flaws is that deviations from normal may not be malicious in nature. They may reflect new behaviors that are non-malicious in nature. For example, new software, new policies, new scope of work, or any other of a myriad of changes may cause a deviation from normal. 

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Do Complex Cybersecurity Issues Cause You Chaos?

Do Complex Cybersecurity Issues Cause You Chaos?

Cybersecurity is really complicated. It is a topic of massive amounts of minute details. From those details, incredibly important big pictures must be formed. Cybersecurity is the art of being situationally aware in chaos.

Software engineering is really complicated. It is a topic of massive amounts of ones and zeros. From those bits (1s and 0s) helpful applications must be formed. Software engineering is the art of creating knowledge from big data formed of bits.

Cybersecurity is inherently complex, as is the world of software. How do we make complex things less complex? How do we "get our heads around" all the things in the cyber domain?

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