AcronisSecurity Tips

How AI is Revolutionizing Cybersecurity: Opportunities and Risks

4 Mins read
AI in cybersecurity

Artificial Intelligence (AI) really “took-off” in 2022, with the launch of ChatGPT, the generative AI chatbot from OpenAI. This was something of an “inflection-point” wherein every business in the world started thinking in terms of integrating AI into its business operations. At this point, how could cybersecurity be left behind? But when it came to the use of AI in cybersecurity, security professionals were left with a “mixed” feeling.

Risks Associated with AI in Cybersecurity

On one hand, AI has a “force-multiplier” effect on cybersecurity with automation accelerating the pace of operation to unprecedented levels. Plus, AI equipped smaller cybersecurity teams to accomplish much more with fewer resources at their disposal. However, the advent of AI has opened up a “Pandora’s Box” because the same powerful AI technologies are within the reach of cyber criminals who are ever keen on exploiting an emerging loophole. Hence, cybersecurity teams became quite convinced about not having any technological advantage in the current cybersecurity environment. Moreover, with enhanced capability to create new threats, cybercriminals have made sure that the security landscape becomes even more complex.

How AI-led Cybersecurity Tools Stand-out?

Unlike traditional cybersecurity tools that work on predefined rules to detect threats, AI-powered cybersecurity systems “learn from experience,” this allows them to predict, detect and respond more effectively to both known and unknown threats. Hence, AI makes cybersecurity systems more robust in minimizing the possibility of any kind of security breach. Since many of the cybersecurity teams are “completely in the dark” when it came to “novel” cyber threats, use of AI-led automation for defensive purposes is by far regarded as the “best bet” in the currently precarious security environment. All this has made many businesses to seek out agile and adaptive ways to keep their IT infrastructure secure. And AI-powered cybersecurity does “fit the bill” in making teams efficient by augmenting their resources and available time.

Types of AI used in Cybersecurity

Foremost, we must remember that AI is an umbrella term that includes various technologies namely machine learning, neural networks, deep learning, natural language processing (NLP).

  • Machine Learning: Utilizes statistical algorithms that take in massive amounts of data and learn from it without any additional programming to make decisions. And with time, the AI-system becomes better and better with each iteration. In the context of cybersecurity, the machine learning system would be capable of “parsing through” relevant data and come-up with solutions to make informed decisions.
  • Neural Networks & Deep Learning: Both these happen to be subsets of machine learning that “create” systems which more or less mimic human thought. This helps in solving immensely complex tasks and can be used to prevent phishing, cyberattacks, detect and address malware, analyse network traffic, and even user behaviour.
  • Natural Language Processing (NLP): Here AI is used for making machines that understand human language. Amazon’s Alexa and Microsoft’s Siri are apt examples of NLP.
  • Expert Systems: These are systems within AI that are used to get done specific tasks, this would include analysing massive amounts of data to produce insights or predict scenarios on specific topics. Such systems are quite common in detecting anomalous behaviour, identify threats, and scan for vulnerabilities. The major down-side with these systems is that it requires huge investment of time and resources.

AI in Cybersecurity – Major Opportunities

The overall scope of AI in cybersecurity is quite vast but if we seek to understand the most pertinent opportunities, then we must focus on these three aspects:

  • Threat Detection: With AI, the possibility of finding new cyber-threats is quite formidable. Earlier, with traditional cybersecurity tools, the possibility of overlooking anomalies or missing zero-day threats is an undeniable possibility. However, with AI in cybersecurity, techniques such as pattern recognition and anomaly detection has become the norm. And these have “heightened capability” to spot unusual activity that could indicate a cyber-attack. Further, AI-powered cybersecurity systems are capable of round-the-clock scanning of systems and networks to indicate “weak-points” in the network vulnerable to a security breach.
  • Threat Management: There are a range of possibilities when it comes to cyber-threats, hence it become extremely pertinent to have a management process in place. This means, if multiple threats are detected, the AI-powered cybersecurity system can prioritise these threats based on their potential to cause damage and accordingly roll-out the appropriate response based on the “order of priority” chalked out by the AI-powered cybersecurity system. Moreover, AI is capable of orchestrating a response in real time, thereby minimizing the damage to the least extent possible.
  • Threat Response: AI-powered cybersecurity systems are completely capable of automating many aspects of threat response. This can include blocking malicious traffic, isolating affected systems, and even generating incident reports. This notwithstanding, AI systems come with the innate ability to “adapt and evolve,” this makes it a valuable tool for responding to emerging threats as they unfold in real time.

Future of AI in Cybersecurity

As mentioned earlier, the scope of AI in cybersecurity is quite vast, this brings us to the future of AI in cybersecurity. These happen to be the most pertinent uses into the future:

  • Generative AI and Threat Intelligence: By using generative AI, it is possible to create entirely new threat intelligence tools, this allows real-time analysis of emerging threats, that automatically generate security insights.
  • Security Automation: AI is being increasingly leveraged to automate complex security processes such as filling vendor questionnaires, and incident response workflows, these improve the efficiency of security systems to a very large extent.
  • Threat Deception Tactics: This allows security teams to create dynamic environments which can mislead and even trap cyber attackers, equipping organizations with valuable intelligence while neutralizing threats.

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Read next: How to safeguard your data from cyber-attacks in 2024?

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Amy Sarah John

About author
Amy Sarah John – content writer interested to learn and write about new things. She likes to write about technology and travel. Amy spends her free time watching travel videos and traveling with family.
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