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Enterprise Security Magazine | Friday, November 30, 2018
Almost half of the businesses in the UK have experienced a cybersecurity attack or breach in the last year, claims the 2018 research from the Department for Digital, Culture, Media and Sport. As the General Data Protection Regulation (GDPR) requires organizations to report data breaches within 72 hours, it is of prime information that IT decision makers have complete control and visibility over their networks. Artificial intelligence would be another additional layer of support here by aiding in the identification of data breaches and sending out the necessary alerts, as well as aid in their prediction and post-event analysis.
As AI attempts to replicate human behavior, the automation of processing, decision-making, and facial and speech recognition are some of its uses in an enterprise security context. It has a significant impact on data processing. Machines analyze data points rapidly, making it easier to detect behavioral anomalies and flag potential threats when anything strays from the norm.
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Machines become increasingly accurate over time—machine learning is capable of replacing a large amount of tedious work. Machines eventually reach up to 90 percent accuracy, at which point it can operate autonomously—this frees IT staff to look into other important tasks.
The IT decision makers in the UK and the US in 2018 were surveyed on their opinions on AI in enterprise security. It was found that 21 percent believe that AI will eventually pay a significant role in the field, 58 percent think that it will play a minor part for the present, while 22 percent believe it to be too soon for AI to have a role in security. Decision makers on either side of the Atlantic are open to the idea of AI taking independent security action, with almost half aiming to incorporate AI into their security. A quarter of IT decision makers do not trust AI to mitigate security attacks, but just 1 percent believe that AI should not be allowed to act without human validation.
Experimentation is expected as enterprises attempt to create efficiencies in cybersecurity. As Ai is data-driven, machines are expected to deep learn with the appearance of new data sets. Successful AI projects will be constrained and targeted to solve a specific problem. The importance of codes reduce and models become significant in AI projects might apply for security over time.
AI plays a key role in several elements of the enterprise, so it is a matter of time before it becomes a mainstream enterprise security component. Initially, human involvement will be critical to its development, but over time, the staff will be free of automatable tasks and can look into other areas to ensure data security and regulatory compliance.
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