What is AI Security
On a basic level, artificial intelligence (AI) security solutions are programmed to identify “safe” versus “malicious” behaviors by cross-comparing the behaviors of users across an environment to those in a similar environment. This process is often referred to as “unsupervised learning” where the system creates patterns without human supervision. For some AI platforms, like Vectra, “deep learning” is another key application for identifying malicious behaviors. Inspired by the biological structure and function of neurons in the brain, deep learning relies on large, interconnected networks of artificial neurons. These neurons are organized into layers, with individual neurons connected to one another by a set of weights that adapt in response to newly arriving inputs.
Sophisticated AI cybersecurity tools have the capability to compute and analyze large sets of data allowing them to develop activity patterns that indicate potential malicious behavior. In this sense, AI emulates the threat-detection aptitude of its human counterparts. In cybersecurity, AI can also be used for automation, triaging, aggregating alerts, sorting through alerts, automating responses, and more. AI is often used to augment the first level of analyst work.
Common Uses of AI in Cybersecurity
AI security solutions are able to identify, predict, respond to, and learn about potential cybersecurity threats, without depending on human input. Sophisticated AI security tools can:
- Learn independently based on previously detected behaviors
- Contextualize and conclude new or incomplete information or behaviors
- Present viable remediation strategies to threats or security vulnerabilities
The Benefits of Leveraging AI Technologies in Security
AI cybersecurity provides many benefits to companies and their existing IT and security teams. A few of the most high-value benefits include:
- AI capabilities allow a much higher volume of data to be processed
- AI helps fill the gap with smaller or less resourced cybersecurity teams
- AI provides more consistent and longer term protection for organizations
How To Evaluate An AI Cybersecurity Vendor For Your Network
When deciding on an AI security vendor, it is essential to ask the correct questions to evaluate whether or not that vendor provides an AI driven cybersecurity solution that can effectively protect your network. Below are nine of the best questions to ask and reflect on:
- What type of machine learning algorithms does your product use?
- How many machine learning algorithms does your product have and how are they categorized? How frequently do you update them and release new algorithms?
- How long until machine learning algorithms can trigger detections in a new environment? How many algorithms require a learning period, and how long does that take?
- How does your product prioritize critical and high-risk hosts that require immediate attention from an analyst?
- Does your product integrate seamlessly into existing detection, alerting, and incident response workflow?
- What firewall, endpoint security, or network access control (NAC) integration does your product provide to block or contain detected attacks? How does your product integrate with these platforms?
- What is the workload reduction your product provides for security analysts? What kind of efficiency increase can be expected?
- Does your product support running red team exercises to prove the value of machine learning algorithms and AI work in real world scenarios? Will you pay for the red team if your product doesn’t detect anything?
- Do you recommend that human analysts have remote access to the product during the evaluation? Why?
How are Malicious Actors Leveraging AI?
As enterprises are beginning to implement AI technology in their cybersecurity infrastructure, malicious actors are staying up to date and begin to adapt their methods to stay off the radar. Cybercriminals have the chance to figure out the solution’s threat flagging mechanism, allowing them to modify their attack’s strategy to avoid detection and increase the speed of attacks.
What are the advantages of using AI in cybersecurity?
Thanks to automated detection capabilities, AI cybersecurity tools enable enterprises to identify, locate, quarantine, and remediate threats more efficiently.
Will AI take over cybersecurity?
With the development of machine learning technologies, AI is set out to become an integral part of cybersecurity. Though AI might not take over cybersecurity completely, it will be able to manage a network’s safety with minimal supervision.
What are the downsides of using AI for cybersecurity?
There aren’t any inherent downsides to using AI for cybersecurity. The potential issues arise when cybersecurity experts start relying solely on the technology to hunt and fix threats.
Vectra: Security That Thinks
As a leader in network detection and response (NDR), Vectra AI protects your data, systems and infrastructure. Vectra AI enables your security operations center (SOC) team to quickly discover and respond to would-be attackers—before they act. Vectra AI rapidly identifies suspicious behavior and activity on your extended network, whether on-premises or in the cloud. Vectra will find it, flag it, and alert security personnel so they can respond immediately. Vectra AI is Security that thinks®. It uses artificial intelligence to improve detection and response over time, eliminating false positives so you can focus on real threats.
