Introduction
Nowadays, we have an extremely large number of Edge and IoT devices sending data across networks as the Edge continues to expand. What’s more, everything depends on and is connected to one another to provide the speed, scale, and interdependence essential to our modern digital existence, greatly increasing the target area that can be exploited by hackers.
It’s safe to say that organizations are having a hard time keeping up with cybercriminals, whose methods are continuously evolving and the number of attacks is growing. For example, this is evidenced by the 3,000% surge in IoT malware activity recorded in 2020. To top it off, there are now more potential entry points for malicious actors, such as negligent vendors or dissatisfied workers.
Phishing, data exfiltration, denial of service, malware, and ransomware are just a few of the methods hackers use to wreak havoc on businesses and consumers. In fact, it was recently reported that the average cost of a data breach reached $4.24 million, a 2021 record high.
Another thing to consider in the cybersecurity race is the fact that there is an acute shortage of cyber professionals around the world to keep up with attacks. This means that organizations need to leave traditional approaches in the past and find new ways to stay safe and ahead of the curve.
The pitfalls of traditional cybersecurity
Traditional cybersecurity is dead, or very close to being obsolete. We typically can’t go a day or two without reading the latest headline of a data breach that halts operations, demands ransomware, or worse, threatens national security. Unfortunately, the current methods of detection or protection of most organizations are insufficient, costing millions of dollars as a result of negligence. For example, a single cyber attack in the automotive industry can cost up to $1.1 billion, a hefty price tag that no one wants to pay, especially to cyber criminals.
As the new reality of the cyber space demands smarter, adaptive, and more assertive means of protection and detection that don’t just react, but proactively prevent losing corporate data, expose the business to severe losses, or even endanger human life as the result of a cyber attack.
AI for cybersecurity is gaining traction
Chief Information Security Officers face a critical situation as they balance digital transformation, growth enablement, and an expanding cyber attack surface. But in crisis, we often find opportunity, and that opportunity comes from innovative new approaches. Overall, the majority of executives—globally and across industries—are adopting or are considering adoption of AI and automation as a dynamic, modern, and effective approach to cybersecurity that goes beyond traditional means. Over 93% of organizations are increasingly interested or are considering adoption of AI and automation to boost security operations' visibility and efficiency. These are the top 10 benefits of integrating AI and automation into your cybersecurity strategy:
Massive volumes of data processing.
One of the main benefits of automated AI cybersecurity is the ability to process huge amounts of data quickly and efficiently, across a wide range of IT network elements, such as emails, websites visited, third-party software, shared files, and—perhaps, most importantly—patterns of activity that indicate attempts to break into the network.
Improved accuracy for empowered decision-making.
Security reports found that the lack of automation is a key challenge for security teams, as they are overwhelmed with a huge amount of false positive alerts. This can lead to missing genuine alerts of cyber attack. Automated AI is much less likely to make mistakes than humans because it doesn't get tired or distracted by doing the same tasks over and over again.
New, unknown threat detection and response.
AI-driven automation security systems can employ AI-generated insights to detect, learn, and adapt to threats based on user, device, or location, and then take appropriate actions while human specialists determine how to investigate and fix the problem.
Automated AI can spot unknown threats by noticing unusual behavior early on so they can be stopped before they spread a virus, start logging keystrokes, give hackers time to browse, etc.
Reduced detection time.
AI-powered security solutions reduce time to detect, respond to, and recover from incidents. An IBM example showed that organizations who take 230 calendar days to detect, respond, and recover from a cyber incident without AI, could cut that time by up to 99 days by applying automated AI.
Cybersecurity cost reductions and increased ROSI.
Reports show that automated AI helps reduce cybersecurity costs by at least 15%, highlighting that processes for protection, prevention, detection, and response are more efficient and productive as a whole.
Automated AI also cuts data breach costs by at least 18%. By employing automated AI, you can see an increased return on security investment (ROSI) by 40% or more.
Ongoing protection, 24/7/365.
AI and cybersecurity work well together to keep an eye on the security of a network 24 hours a day, 7 days a week, and 365 days a year. Hackers don't work during regular business hours, and their attacks come from all over the world. If you want to know about malicious items and attempts to break into your network right away, not at the start of the next business day, you need to keep an eye on your IT system around the clock.
Security governance and compliance.
Automation in cybersecurity can help improve compliance, which is important for many companies because they need to keep their data private. AI and automation help make it easier for procedures to be escalated, reviewed, and fixed, leading to strong security governance.
Fatigue mitigation and elimination of redundancy.
40% of IT workers, as reported by McKinsey, devote one-fourth of their time to routine duties. Automated AI helps security analysts quickly tell the difference between harmful and harmless network activity. These insights let people focus on harmful activity and possibly program AI to stop it in the future. In short, AI with cybersecurity helps make better use of a company’s human resources.
AI helps get rid of duplicate processes, and its algorithms can save analysts a lot of time that they would have spent doing the same things over and over again on thousands of datasets.
Better performance and cyber resilience.
When AI and automation work together, the results on performance are far improved, whether in terms of speed, insights, or flexibility. These performance improvements let cybersecurity teams shift their attention to what really matters: reducing corporate risks, leading digital transformation initiatives, and strengthening business and IT alignment.
As evidenced by the aforementioned benefits, automated AI tools will become vital in modern cyber warfare and organizations need to take action to prevent being the next victim of a cyber attack that could cripple their operations.
At a time when cybersecurity strategies are underfunded when funding and support is needed more than ever, the adoption of automated AI security breathes relief and resilience in organizations ahead of the next major business disruption.
AI EdgeLabs is an advanced and autonomous cybersecurity AI platform that equips security teams with threat intelligence software to protect, detect, and remediate risks in real time with the highest precision against malware, DDoS, botnets, and more, at the Edge and IoT/OT layers.