Things to Do After Implementing Cybersecurity AI for Alert Management

In the security operations center, human knowledge will always be crucial (SOC). Overworked, underfunded teams do their best to manage the cybersecurity environment, but they’re frequently handicapped by the sheer volume of alerts, reports, and warnings issued by various security systems around the business. Implementing cybersecurity AI could be a viable option. This security strategy, which began as a rumor and then a wish, is now gaining traction as a viable way to shift the responsibility of alert management away from security professionals and teams and onto the digital shoulders of artificially intelligent solutions. But what happens after cybersecurity products have caused a stir and employees have escaped the barrage of alerts?

1. Deep Clean your Network

No network is impenetrable, and according to new TechRadar research, practically all mobile apps are vulnerable to malware. Because of the rising application environments and expanding cloud services, the first thing IT experts need to do once AI makes things easier is deep clean the network. Sweep the area to check for cloud sprawl. Locate and shut down any instances or programs that aren’t in use or may constitute a security risk. Work with employees to discover apps that aren’t permitted by IT and then find solutions to secure them or provide approved alternatives. Next, check for common flaws and vulnerabilities that haven’t been patched. It is, of course, preferable to discover potential problems as soon as possible rather than later. Finally, make penetration testing a top priority for your whole network. Bring on a credible, competent, and capable third party to analyze and evaluate your complete IT ecosystem. Let’s face it: deep cleaning the network isn’t fun, but it’s the first step toward a more secure security approach once AI is in place.

2. Perform Deeper Analysis

With AI handling daily notifications, as well as automatically responding to small information security risks and eliminating false positives, IT professionals can now focus on deeper analysis. Artificial intelligence (AI) methods are now being used to assess application hazards and estimate their long-term danger potential. Staff may focus on finding trends at scale and being proactive in tackling security flaws using this data as a springboard.

3. Break Security Silos

Information security teams continue to struggle with silos. While cloud services have increased overall complexity, they have also democratized IT access. Consider how quickly multi-cloud environments are being adopted: According to recent Flexera survey data, enterprises are currently deploying roughly five separate clouds to properly manage IT. That implies businesses have five separate approaches to data management, information security, and asset mobility, and where these approaches collide at the intersection of department silos, security risks emerge. Information security professionals can focus on streamlining cloud solutions by discovering and installing multi cloud management solutions that improve visibility, security, and automation at scale, thanks to the deployment of cybersecurity AI.

4. Draft Solid Policies

With AI taking care of the fundamentals, it’s time to take a step back and write a policy that fulfills present expectations while also assisting businesses in future-proofing their protective processes. While AI tools can assist in detecting, identifying, and mitigating attacks, it is still up to IT professionals to implement and execute cybersecurity policies. As a result, security teams must collaborate with C-suite executives to design policies that allow key functions while reducing total risk. Network usage, access requirements, mobile deployments, application installation, and data storage and transfer should all be high on the policy priority list. They should also include clear remedies in the event of a policy violation. In other words, it’s vital for IT professionals to inform employees about what’s allowed, what’s expected, and what the implications could be if policy isn’t followed correctly.

5. Determine Who to Escalate the Alert to if It is Ignored

Not everyone in the firm values every warning equally. Make sure to send technical notifications to your technical team and marketing alerts to your marketing team if they point to a problem with campaigns or landing pages. The C-Level team may be interested in overall data like traffic and conversion. An inbox full of useless messages, like dashboard alerts, teaches individuals to ignore all alerts, including ones they should be acting on.

6. Instill Trust at the C-level

Despite AI tools’ rising capabilities, faith in them remains low. In fact, 60% of security experts prefer human-verified results over AI-generated results. Human intuition, originality, and prior experience, according to respondents, surpassed AI’s prediction processes. In the changing infosec environment, security personnel have a new role to play as fact-checkers and supporters of AI solutions. It’s possible for security teams to boost C-suite confidence and pave the way for continued AI deployment by developing data pipelines that enable human analysis and oversight.

By Jayanth Varma, Founder

CEO/Founder of AlertFusion. We aim to improve the productivity of our customers by tackling the challenges faced by their analysts day in and day out. We do this through centralising alerts, eliminating rework, and retaining key knowledge.