Cybersecurity is one of the more difficult problems we face, and artificial intelligence is well suited to address it. Machine learning and AI can be used to “keep up with the bad guys,” automating threat detection and responding more effectively than conventional software-driven approaches, with today’s constantly developing cyber-attacks and proliferation of gadgets.

At the same time, cybersecurity has several particular difficulties:

  • A vast attack surface
  • 10s or 100s of thousands of devices per organization
  • Hundreds of attack vectors
  • Big shortfalls in the number of skilled security professionals
  • Masses of data that have moved beyond a human-scale problem

Several of these issues should be resolved by an AI-based cybersecurity posture management system that is self-learning. It is technologically possible to correctly hone a self-learning system such that it can autonomously and continuously collect data from all of your corporate information systems. Following data analysis, correlation of patterns across millions to billions of signals pertinent to the enterprise attack surface is performed.

How Artificial Intelligence in cybersecurity can help stop cyber-attacks?

Business organisations can defend themselves, recognise dangers, and take action. AI may have a significant impact on cyber security professionals and solutions. Since AI’s creation, it is possible to:

  • Provide accuracy in detection.
  • Help in accelerating the investigation.
  • Automating the response
  • Provide a proactive mechanism of protection so that businesses and users are safe against threats.
  • It can be used for doing continuous verification of a user based on behavioural biometrics.

Artificial intelligence (AI) is playing a bigger role in cybersecurity when combined with machine learning. Emerging security solutions, according to ZDNet, analyse huge amounts of data from millions of cyber incidents and use that data to find threats like new malware strains and phishing schemes.


Sadly, some cybercriminals change their malware code to evade detection by security software, putting them one step ahead of these efforts. The burden of identifying every malware variation is great, but AI and ML can help. Since it may use information from any type of malware that has been previously identified, ML in particular makes a great component of anti-malware security systems.

As a result, when a new kind of malware emerges, the system may examine the code, compare it to the database, and stop the attack. This technique is effective even when a large amount of harmless or ineffective code surrounds the harmful code. ML can be applied in other ways to strengthen cybersecurity initiatives. What users frequently do can also be monitored by an AI-powered network monitoring tool. An important benefit in a world that is always changing is that the AI can detect abnormalities and respond appropriately by analysing this data.

Benefits of using AI in cybersecurity

AI continuously learns: 

AI is capable of continuing to learn on its own, which can be advantageous when network security is gradually improved. AI employs machine learning and deep learning to identify patterns on the network and group them; it then uses this information to identify deviations or security incidents before taking action. Future security can be enhanced with the use of these patterns. Such potential risks can be found and stopped before they can do any damage. Continuous learning makes it difficult for hackers to beat their intelligence.

AI reasoning finds threats faster: 

In a matter of seconds or minutes, AI can analyse connections between risks like malware files, suspect IP addresses, or insiders.

AI eliminates time-consuming tasks: 

AI offers customised risk analysis, cutting down on the time security professionals need to address risks and make important judgements.

AI Can Handle a Lot of Data: 

Even when it comes to a big amount of data, AI is capable of spotting possible hazards. There is a lot of internal and external communication, as well as data interchange, in a corporation. This data needs to be secured against harmful software and persons. But, it is impossible for cybersecurity experts to monitor every communications for potential attacks. The greatest option in this situation is artificial intelligence, which can find any threat concealed in this communication.

Better Vulnerability Management: 

Managing vulnerabilities is essential to protecting a network for a business. An average organisation encounters numerous threats every day, as was already established. To be safe, it must be able to recognise, detect, and prevent them. AI research that analyses and evaluates current security methods can assist in managing vulnerabilities. Using a vulnerability management solution makes it much simpler for businesses to analyse threats.

Duplicative Processes Reduce

Attackers frequently switch up their strategies. The fundamental security best practises, however, never change. If you pay someone to complete these activities, they can become disinterested throughout. Alternately, they can be worn out and complacent and neglect a crucial security responsibility, exposing your network. Artificial intelligence (AI), which emulates the best aspects of humans while omitting their flaws, handles redundant cyber security procedures that could occupy your cyber security staff with tedious work.

Accelerates Detection and Response Times: 

When your company’s network is compromised, it’s critical to respond quickly and implement the required safeguards. Prevention is preferable to treatment. Blocking a threat is safer than going back and dealing with it after it has already caused significant harm. AI is able to recognise these hazards in advance and stop them from harming anyone.

Securing Authentication: 

When your company’s network is compromised, it’s critical to respond quickly and implement the required safeguards. Prevention is preferable to treatment. Blocking a threat is safer than going back and dealing with it after it has already caused significant harm. AI is able to recognise these hazards in advance and stop them from harming anyone. To access services or make purchases, most websites offer a user account function that requires logging in. Visitors are required to fill out sensitive information on some websites’ contact forms.

As a business, you must add an additional layer of protection because running such a site entails handling sensitive data and personal information. Your visitors’ safety while using your network is guaranteed by the extra security layer. Every time a user tries to connect into their account, AI secures authentication. For identification, AI use a variety of techniques, including fingerprint scanners, CAPTCHAs, and facial recognition.

Downsides of Artificial Intelligence in Cyber Security

The benefits mentioned above only scratch the surface of AI’s ability to enhance cybersecurity.

The use of AI in this industry does have its drawbacks, as with anything, though. Organizations would require a significant increase in resources and capital expenditures in order to develop and sustain an AI system.

Additionally, as data sets are used to train AI systems, you must collect numerous unique sets of malware codes, non-malicious codes, and abnormalities. All of these data sets must be acquired, which takes time and costs money that most enterprises cannot afford.

Without massive amounts of data and events, AI systems may produce false positives or inaccurate results. And obtaining false information from dubious sources can also be detrimental.

Another significant drawback is that thieves might use AI to assess their software and carry out more sophisticated attacks, which leads us to our next issue.

Conclusion

AI has become a necessary piece of technology for supporting the work of human information security teams in recent years. AI provides much-needed analysis and threat detection that can be used by cybersecurity professionals to decrease breach risk and strengthen security posture because humans can no longer scale to sufficiently guard the dynamic enterprise attack surface. In terms of security, AI can categorise risks, quickly identify any malware on a network, direct incident response, and discover intrusions before they happen.

AI enables cybersecurity teams to create strong human-machine alliances that advance our understanding, improve our lives, and advance cybersecurity in a way that looks more powerful than the sum of its parts.