The NICE Cyber Security Framework by Izzat Alsmadi & Chuck Easttom & Lo’ai Tawalbeh

Author:Izzat Alsmadi & Chuck Easttom & Lo’ai Tawalbeh
Language: eng
Format: epub
ISBN: 9783030419875
Publisher: Springer International Publishing

The more modern and desirable approach though, would be using machine learning. Machine learning allows computers to process new conditions through analysis, self-training and observation [9]. This allows the machine to gain experience then use it for decision-making. Tools such as UEBA’s (User, Entity and Behavioral Analytics) incorporate machine learning and are gaining popularity in the industry to thwart attacks. UEBA’s discover security anomalies by aggregating data via logs and reports, packets, traffic flow, files, user accounts, endpoints and much more. This information is compared to other threat data to help train the model and determine what’s normal through repetition thus building a better security. This allows organizations to better understand what their users are doing daily and establish a baseline for network activity [10].

The machine will create its own rules and formulate opinions based what it learns then provide stats and metrics saving personnel from having to do the heavy lifting by performing hours of log sifting [11]. Those are manual processes and history has taught the industry that humans are error prone. Through automation, efficiency is gained, errors are reduced, and repeatability is achieved. Table 6.1 shows how these technologies may be combined to provide a layered defense in an organization. Almost every if not all security course teaches the “defense in depth” methodology and while this chart is not conclusive, it provides an idea of how these tools can be cross-functional in design and application.Table 6.1Layered defense in an organization

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