IBM’s Cost of a Data Breach Report is so highly cited because of one statistic—the average cost of a breach. However, when you delve deeper into the report, there are other numbers and facts that offer useful security insights. Perhaps the most overlooked of these is that organizations can save a whopping $3.05 million on average with fully deployed AI and automation.
So, with this number in mind, let’s take a deeper dive into the potential value of AI and automation for cybersecurity. You’ll get the lowdown on the benefits of both, suggestions on security functions to consider automating and more.
Automation executes security actions and tasks using technology, with reduced or no human assistance. Here are some key benefits of automating cybersecurity tasks.
The barriers to entry for cybercrime are lower than ever. Dark web marketplaces and underground forums offer suites of hacking tools that automate entire cyberattacks. When you try to defend against an onslaught of machine-based attacks using limited human security resources, you’re fighting a losing battle.
Security automation enables you to better defend your company’s data and systems against bots that carry out attacks like phishing and DDoS.
Alert fatigue places a huge burden on security teams and analysts who get overwhelmed with many different alerts from various systems. Some of these alerts are important, but many are false positives. The main problem that alert fatigue causes is when the feeling of overwhelm and stress causes alerts to get ignored or missed. Recent research found that up to 30 percent of security alerts either get ignored or not investigated.
Automation helps security analysts filter out the noise and focus on the most actionable information. Various solutions are available to help out here, including systems that correlate and filter data to generate high-fidelity alerts and systems that provide automated responses to lower-risk alerts.
Speaking of automated responses, there are entire classes of security solutions that automatically detect and respond to security incidents using rule-based logic and runbooks. In the race against time to contain security incidents before they result in a dreaded data breach, being as efficient as possible with incident response must be a priority. Automated incident response takes away the burden of repetitive or menial tasks from those in charge of responding to incidents so they can better apply their knowledge and skills.
It’s important to separate out the benefits of AI in cybersecurity from those of automation. These two terms regularly get conflated because of how AI and its sub-disciplines of machine learning and deep learning often facilitate greater automation. However, they are not the same thing.
AI is a branch of computer science focused on the simulation of human intelligence in machines and software. While AI solutions can streamline security tasks and speed up workflows, the scope of the discipline is far wider than just performing repetitive tasks with little or no human intervention. Rapid recent advancements in AI have spawned all kinds of economic and even philosophical debates, but from a security perspective, there’s no denying its potential.
AI security solutions that use machine learning can improve their performance over time. The underlying algorithms can adapt to changing threats and environments, learning from past experiences and network patterns to continually refine their performance. The self-learning nature of these systems brings adaptability to security defenses and greater accuracy in detecting deviations from standard network activity.
AI algorithms can analyze vast amounts of data and identify patterns, anomalies and potential threats much faster than human analysts. This does not make human expertise and input irrelevant, but the depth of data it can trawl and the breadth of sources it can utilize enables cybersecurity professionals to stay ahead of the curve, uncover evolving threats and detect attacks in close to real-time.
With AI-driven endpoint detection and response tools, you can establish a baseline of behavior for your endpoints through the pattern recognition capabilities of these algorithms. If something out of the ordinary happens on an endpoint, AI will flag it and take action, whether that’s sending a notification to your security teams or reverting to a safe state after a ransomware attack.
Some of the use cases for AI in cybersecurity are:
As networks get more complicated and threat actors constantly probe for weaknesses, there’s no denying that both AI and automation can bolster cybersecurity defenses in many important ways. These benefits are even more evident in a world where security workforce shortages leave many companies lacking the expertise and resources needed to fend off fast-paced, high-volume cyberattacks.
To extend these benefits and transform your security operations even further, managed security service providers (MSSPs) can also prove invaluable. By outsourcing different cybersecurity functions to a team of third-party security experts, you reduce the burden on existing staff and become more efficient in your operations. Combined with the smart selection of AI tools and automating as many menial tasks as feasible, MSSP services can take you to unrivaled levels of security monitoring and protection.