Читать книгу Machine Learning Approach for Cloud Data Analytics in IoT - Группа авторов - Страница 74

Along with machine learning, cyber security systems perform a proper analysis of patterns and learn the ways to help associate the ways of prevention of liked attacks and reciprocate to the changing behavior. At the same time, it can help the cyber security teams to be proactively involved in prevention of threats and reactively responding to the real-time active attacks. It can also lessen the amount of time spent on scheduled tasks and enable the users and the related organizations in any similar aspects for resource utilization more strategically. Machine learning can take over cyber security in a simpler and effective way which seems to be more proactive but less expensive. But it can only perform if the underlying data supporting machine learning gives a clear image of the environment. As they say, garbage in, garbage out [25]. As of the concerned study, the explicit description is much flexible with respect to the chang es carried out in the conditional algorithm in the utility functions that can be reflected by the identical data nodes in evaluating the decision network strong enough to accommodate the observational reflections in cyber metric network zones, which when applied will definitely go on for a substantial proliferation of safety and security in going at par with IoT devices in excellence.

As of a debated verse, these days that internet is hardly a secure environment itself that makes IoT devices even less so, but with technical knowhow and implementing those technical aspects, we can make a turnover to make it a differentiable in its context. There have been several high-profile events, involving the use of IoT devices as nodes in wider botnet attacks that highlight IoT’s vulnerability. With one of the finest examples being the Mirai malware which runs over the largest DDoS attack that targeted French cloud computing site OVH and even lighter in the particular year. Besides, along with the advent of maturity, security will tend to be a market differentiator.

A company selling web cameras which provides lifelong security upgrades may accumulate greater sales than a rivalry company which never does [26]. Further, many risks are enliven with both home and enterprise. IoT makes up the following non-exhaustive list:

 Secured data issues

 Risk of being safe personally and publicly physical safety

 Privacy issues like home devices being hacked

 Growth of IoT devices being followed by data storage management