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Build a Robust Cyber Security Strategy Using AI & Machine Learning

AI and Machine Learning In Cyber Security

Is AI and machine learning the secret sauce for evolving cyber security, and will this eventually eliminate the human role?

You can’t deny everyone’s current obsession with Artificial Intelligence (AI). The ‘wow’ factor of AI amazes us with its ever-evolving impact our daily lives. From driving the quickest route to finding the ‘best fit’ solution for your business objective, AI has it all.

This analytic capability has been recently exploited, among not only AI enthusiasts, but also early-adopters, techies, and industry experts. Cyber Security utilizes this approach though machine learning and natural language processing to enrich and improve our corporate security operation effectiveness.  AI provides cyber threat detection and prevention with speed and capabilities not achievable by people.

With broad connectivity and access points, the idea of a hard impenetrable shell is obsolete with in-depth protection as the only viable mitigation to the world’s ongoing cyber threats.  AI brings a technological advance in protecting sensitive business data across broad and global distributed enterprise environments. Let’s explore how AI and machine learning can help you to create a robust cyber security strategy to detect and combat threats.

Staying ahead of Cyber Threats

The role of AI in cyberspace is beyond the simple command and control role of computer systems of the past.  AI provides the ability to recognize patterns in large bodies of data and learn from not only the pattern but how the pattern evolved to identify new (zero day) patterns without human intervention. This is done through the use of a number of advanced mathematical models used on both structured and unstructured data.

The massive adoption of connected devices over cloudmobile, and IoT platforms makes it more difficult for cyber security experts to trace the attack vectors of sophisticated hackers. Advanced analytics and AI technologies are being leveraged across all industries for not only data analysis, but also for making better business decisions and securing your data.

From a cyber security perspective, AI powers the engine to protect our business data from new vulnerabilities and threat vectors through anomaly detection from current and future cyber attacks. Cyber security gains a competitive edge by combining security teams with adaptive technology that continually grows smarter.

 

Effective Resource Allocation

Advanced data analytics will enable your cyber security experts to detect and respond to threats faster and work more effectively to mitigate threats earlier in the cyber kill chain. The biggest focus of machine learning and AI’s  role in cyber security is pattern recognition, which enables security operations to find the virtual needle in the haystack.

A lot has been said and done using mean field theory to perform anomaly detection across large corpuses of data. It outlines all the possible permutations and combinations of structured and unstructured data as well as security-based data from various data sources including non-traditional data sources. This correlation with the security logs identifies the spikes in the data that are the key to finding deep-rooted and Advanced Persistent Threats (APT’s).  A strong combination of automated intelligence and personnel security expertise will bring the best cyber security solution for your overall security posture.

Continuous Hybrid Security Support

By putting this intelligent automation into your cyber security process, you can provide consistent monitoring, tracking, and automated remediation. Introducing AI and machine learning into cyber security lessens the burden on cyber security teams, as well as minimizes damage caused by human limitations and errors. With a cyber security strategy that’s powered by intelligent automation, machines do much of the heavy lifting while sending timely alerts about potential threats to respective cyber experts and officials. This blend of artificial and human powernwill enable your organization to allocate your cyber security team effectively, providing maximum effect with minimal staffing.

 

 

Summary

For all the value that AI and advanced data analytics provide to the security world, it is still obvious that the human element can never be eliminated. There will always be a person in the loop for business critical decisions especially in the automation of remediation. There is no “Easy” button in cyber security and there likely never will be. As technologies advance to protect the data, the same technologies will be used to exploit the data. It creates an endless cycle of advance and defend. And even with new technologies, old wisdoms ring true. An ounce of prevention is always worth a pound of cure.

In the cyber security space that means “proactive security” (Shift Left) is more cost-effective and provides less risk than reactive security during an active attack. Baking the security into applications up front rather than bolting it on after the development cycle is more cost and time effective. The advent of Agile development and DevOps puts even more pressure on this need since the security oversight can be pushed aside for the purpose of speed to develop.

Incorporating security professionals early in the development process such as QualiTest Group provides customized  cyber security testing, with an added advantage of business assurance services. QualiTest Group is a customer-centric independent software testing company and is the world leader in pure play software testing. Our deep cyber security testing expertise is a crucial component of our end to end testing solutions.



  • Tooshima Sarkar

    It was a great read. New information on Cyber protection through AI is necessary for blooming tech companies.