Cloud computing has become the mainstay in the industry, but cloud security remains a cause for concern according to a recent report by Bitglass researchers which found that 93% of organizations are concerned about cloud security. When ranked in terms of threat impact, the 2020 Cloud Security Report ranked misconfiguration as the highest, with nearly 68% of companies citing misconfiguration as their greatest concern.
This is where AI can offer a significant step up in terms of improving cloud security posture. It can be particularly helpful in keeping a lookout for security vulnerabilities and violations that arise primarily from user errors. Recent research suggests that, by 2025, 85% of successful attacks against user endpoints will simply exploit setup and user errors, as opposed to the popular conception of advanced malware. Also, companies are finding out that older, ‘perimeter-based’ security approaches are simply not working on the cloud. Artificial intelligence has the ability to reframe cloud security solution in a whole new way.
AI is Critical to the Future of Cloud Computing
87% of IT and data protection professionals say that cloud computing has enabled better or more cost-effective protection of company data. Couple this with the fact that AI-enabled technology offers 20 times more effective attack surface coverage than traditional methods of security. Here are three major ways in which AI can enhance cloud security.
AI can enable an “identity-based security perimeter” that can ensure only valid identity credentials authenticate and authorize access to resources within a company’s cloud environment.
Most AI security frameworks also employ a “zero trust” security approach that does not allow sharing of any data or resources without legitimate user credentials. This approach along with the identity-based security perimeter ensures a high degree of data integrity within the cloud environment.
Finally, AI security frameworks can also make use of a “zero leakage” policy that prevents unauthorized data movement outside the cloud environment. This essentially stops hackers in their tracks, as even if they do manage to get into the cloud environment – there is no way to take the data out of it. Also, it takes care of the problem of authorized employees accidentally or maliciously allowing the data to move out of the cloud environment. Cloud Direct Connect can be a great place to start looking into cloud security solutions for your company.
5 Ways AI Can Improve Cloud Security
Event Prediction – Given the availability of the right data, machine-learning solutions can be used to predict future events with a high degree of accuracy. This is called building a predictive model, which has the ability to map out the exact flow of future events. This can help businesses prepare for changing cycles of demand and supply, for instance, or help perform predictive defensive maneuvers to understand potential threats and simulate attack patterns.
This kind of prediction model can help us assess risks, security vulnerabilities, the flow of upcoming attacks, and where threats may arise. This allows companies to better prepare for attacks, thereby shortening response times between threat detection and remedial actions to safeguard data. Cloud security solutions also provide great benefits for Cloud cost management. It’s not a long stretch to say that within a span of a few short years, AI-powered enterprises will be in a much better place to respond quicker and better to customers, competitors, regulators, and partners than peers who lack AI integration.
Big Data Transformation – Security systems powered by big data hold troves of information that are beyond human capacity to process. Luckily, we now have machine-learning tools to parse through this bulk data to identify danger events. ML algorithms work on feedback loops that grow more defined as it parses through more and more data and grows capable of discovering more patterns and if/ how they deviate from normal ones. The degree of deviation can indicate a threat event.
Real-Time Monitoring and Alerts – AI is highly useful for detecting events and suspicious behavior and providing alerts when necessary. Keep in mind that the accuracy of the AI algorithm will depend on the quality of data that’s been fed into the system. Companies can use real-time monitoring along with automated action systems to enhance security posture. In the event of an anomaly, the AI system responds to the problem at hand just as it has been taught to do and keeps everyone updated on what’s happening, why and when.
Growth of Automation – With rising attack volumes, it’s only natural that companies will turn to AI and machine learning solutions to form the first line of defense against attacks and perform routine security checks and tasks. This will free up valuable human resources to focus on more complex problem solving.
Self-handling Security Analysis – According to the Cloud Security Alliance “Cloud Adoption Practices & Priorities Survey Report,” 34 percent of companies do not use the cloud because they don’t believe their staff has the requisite knowledge and experience to handle cloud computing. Automated technologies like AI and machine learning can go a long way in ensuring minimal human intervention, at least in the first level of cloud security. AI’s ability to sift through massive amounts of data and analyze patterns to detect anomalies provides you with valuable time when a breach is about to hit.
Vulnerability Discovery – Cloud computing technologies are secure on the backend and server-side, but face severe threats from user errors, improperly designed or implemented security measures and other vulnerabilities. Sometimes, issues can persist for years before they are discovered and patched through subsequent updates. AI can help to speed up the process by exploring large amounts of data and identifying potential problems that can allow developers to patch problems faster.
This can also throw up areas wherein users and/ or company staff may need additional support or training. This further strengthens your company’s security posture. Get in touch with local providers of cloud migration solutions today to get started on implementing AI in your enterprise cloud setup at the earliest.
About Ben Ferguson:
Ben Ferguson is the Vice President and Senior Network Architect for Shamrock Consulting Group, an industry leader in digital transformation solutions. Since his departure from Biochemical research in 2004, Ben has built core competencies around cloud direct connects and cloud cost reduction, SD WAN providers, enterprise wide area network architecture, high density data center deployments, cybersecurity and VOIP telephony. Ben has designed hundreds of complex networks for some of the largest companies in the world and he’s helped Shamrock become a top partner of the 3 largest public cloud platforms for AWS, Azure and GCP consulting. Stay connected at LinkedIn.