cloud computing and technology
getty
In cloud-based systems, most security is reactive. This means that the security provisions won’t be triggered until something happens, such as malware starting to attack your cloud applications. When this happens, it is likely that some damage has already been done and malware is already present within the server. This means security staff must deal with removing the malware and repairing the damage.
“All cloud security solutions to date have responded to problems that have already occurred,” explains Principal Architect Keith J. Vincent. technology. “There are many problems with this approach, especially when it comes to threat detection.”
In other words, reactive solutions aren’t fast enough to protect your data and applications in the cloud. “When it comes to cloud security, organizations need the ability to respond quickly to cybersecurity threats and manage threat detection more efficiently.” cloud security alliance. “Today, cloud ecosystems and technology stacks are increasingly complex, and the rise of generative AI business tools is making this even more complex. and adapt to a customer’s specific cloud environment to improve security awareness, visibility, and response.”
Yeoh said that due to cybersecurity skills shortages and budget constraints, generative AI for cloud security is important for automated threat detection and response, as well as vulnerability management and compliance.
And it’s not a minute sooner. According to Forbes contributor Stu Sjouwerman, the first AI-based malware has already been launched as part of an academic exam. He also said that IBM’s DeepLocker, an AI-powered ransomware package, is not yet available, but could be soon and is already being tested.
real time security
cyber security technology
getty
The most effective approach is to attack security using real-time solutions to identify and stop threats before they can harm data and applications on cloud servers, but until recently, proactive approaches of this kind No tools existed to achieve this. It didn’t exist. But now, AI-based anti-malware solutions are starting to emerge. The first one is skyhawk securityhas upgraded its synthesis platform to perform real-time vulnerability research and state management.
What the Skyhawks are doing now is taking a military approach, using red teams and blue teams to look for weaknesses. Each of these AI-based teams attacks the protected cloud infrastructure in its own way, while each shares what it learns with the other teams. The team looks for the path of least resistance as it learns security features and the nature of the data being protected.
The team then uses what they learn to launch mock attacks looking for gaps in security. Chen Burshan, CEO of Skyhawk Security, called this approach a paradigm shift and said the process is continually iterating and evaluating defenses in real time.
“The paradigm we are shifting is moving beyond today’s current ‘reactive’ solutions,” Burshan said. Skyhawk is automatic, but can be fine-tuned for specific implementations. “Response automation operates on two levels, in assisted or fully automated response mode,” he said.
“Skyhawk has three layers of AI running within its system,” Bursjam explained. “The first layer detects suspicious behavior. These are suspicious activities known as malicious behavior indicators. The second layer correlates the activity and alerts when correlated activity indicates an incident. Publish. This layer is responsible for ensuring customers receive genuine alerts and reducing alert fatigue caused by false positives. The third layer uses generative AI to create virtual incident responders. “It works like this and analyzes correlated events during construction. It can increase the alert level and add grounds to the alert,” he added.
Because Skyhawk is a cloud-native application, it is typically relatively easy to implement with the capabilities of in-house staff. The company says that system performance will not be affected.