Cyber security executives are always looking for ways to keep a step ahead of the bad actors and the latest threats. Emerging technologies such as machine learning (ML) are providing a way to do that, and some IT and security leaders have begun taking advantage of tools that leverage these automated capabilities.
Earlier this year, consulting firm KPMG and database provider Oracle surveyed 450 global IT and security professionals, and found that 29% are using ML on a limited basis, 18% do so extensively, and another 24% are now adding ML capabilities to existing security tools.
These organizations need all the help they can get. The same report shows that organizations are struggling to protect their data amidst a growing number of security breaches. A large majority of respondents (90%) classify more than half of their cloud data as sensitive. And while 97% have defined cloud-approval policies, 82% said they are concerned about employees following these policies.
Additional issues companies are facing make security more challenging. Other key findings of the study that indicate this: only 14% of those surveyed are able to effectively analyze and respond to the vast majority of their security event data; 26% cited a lack of unified policies across disparate infrastructure as a top challenge; the new General Data Protection Regulation (GDPR) will impact cloud strategies and service provider choices, according to 95% of respondents who must comply; and 36% of the respondents said mobile device and application use make identity and access management (IAM) controls and monitoring more difficult.
For organizations storing sensitive data in the cloud, an enhanced security strategy is key to monitoring and protecting that data, the report noted. In fact, 40% of respondents indicates that detecting and responding to cloud security incidents is now their top cyber security challenge. As part of efforts to address this challenge, 40% have hired dedicated cloud security architects, while 84% are committed to using more automation to effectively defend against sophisticated attackers.
Cyber security spending on the rise, according to the report, with 89% of those surveyed expecting their organization to increase cyber security investments in the next fiscal year. It’s quite likely some of that spending will go toward ML capabilities.
A recent article on CSO Online identified the top nine uses of ML for enterprise security:
Clearly there are plenty of actual or potential use cases for ML within cyber security programs. To protect themselves against the latest attacks, organizations need to begin looking into these if they haven’t already.
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Former business journalist, Razvan is passionate about supporting SMEs into building communities and exchanging knowledge on entrepreneurship. He enjoys having innovative approaches on hot topics and thinks that the massive amount of information that attacks us on a daily basis via TV and internet makes us less informed than we even think. The lack of relevance is the main issue in nowadays environment so he plans to emphasize real news on Bitdefender blogs.
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