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How Is AI Disrupting The Cyber Security Industry?

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As cybercrime becomes a rapidly evolving facet of the modern criminal enterprise, the emergence of nascent technologies such as artificial intelligence (AI) and machine learning (ML) has been seen as a powerful tool for both digital attackers, as well as those working within the cyber security sector.

As artificial intelligence becomes more mainstream, how will this disrupt the role of the modern cybersecurity industry? Will the rapid acceleration of cybercrime destroy this rapidly growing industry, or is there a place for AI alongside the skills and techniques taught in qualifications such as an online masters in cybersecurity?

Emerging cyber trends appear to indicate that AI may not be the initial menace that analysts once feared – so let’s explore this new frontier in digital crime, and how AI and ML will transform the ways that data is both attacked and protected in the years to come.

A New Frontier in Digital Warfare

In modern computing history, there have been a number of events that have defined new eras in digital conflict. The late 1980s and early 1990s saw the beginning of drive sector attacks, with simplistic viruses spread over removable media such as 5.25” floppy disks, as well as the advent and proliferation of viruses over the Internet in its nascency, such as the spread of the Morris Worm.

It can be said that as time progressed, new vectors of communication have allowed for devices to be infected in a number of increasingly alarming ways. With computing devices becoming increasingly interconnected, whether it be through internal networks or the Internet, vectors for attack have increased – even an air-gapped system isn’t safe, as has been seen through the saga of Stuxnet.

The explosion of new artificial intelligence tools has opened a brand new door for the creators of malware and malicious content, presenting a critical new risk not seen since the early days of the internet.

The Always-On Monitor

While it’s apparent that AI can be used for negative behaviors, if used appropriately, it can also be a powerful complement to existing cyber teams. One such way that this is highlighted is through the development of AI-supported continuous monitoring programs.

For many businesses, systems may need to be always on – whether it be due to data capture, transactional requirements, or the simple requirement of needing to access a system at all times. This can present a security risk, particularly if it’s possible to remote access a corporate network.

While human operators can monitor connections, people can inherently be vulnerable to the risks of social engineering. This was highlighted in the 2020 social engineering attack on high-profile Twitter accounts, encouraging users to send cryptocurrency to individuals such as former US President Barack Obama.

As a supplementary tool, AI can be used to support security teams in identifying when risky behaviors (such as social engineering) are being used to target teams. For example, an AI tool may be able to use recordings of customer calls and support emails to identify a potential scammer, trying to phish their way into a network.

At an operational level, simple, continuous monitoring may be used in conjunction with human operators to identify suspicious behavior, enhancing access control measures. Identifying when staff accounts are being accessed outside of regular operating hours may be something that is easily missed by security staff, but easily highlighted by an AI with awareness of company rostering.


One of the rapidly proliferating elements of Artificial Intelligence in recent years has been the use of advanced large language models (LLMs). These AI algorithms use advanced techniques to interpret, summarize, and generate new content. While the most widely known model is ChatGPT, there are a number of alternative products on the market.

The ability to rapidly summarize and generate new information from existing datasets is an incredibly powerful tool, particularly with the increasing volume of information that is generated in today’s modern world. However, this can present an element of risk – with early models allowing for open text input, an opportunity arose for bad actors to generate crude malware.

Where software development may iteratively take an extended period of time, the notion that malware could be generated in mere minutes presents a significant risk to information systems worldwide. Fortunately, the risk appears to be contained at the moment, with current large language models being apparently incapable of creating quality malicious code that actually works.

While build-your-own-malware may not be a risk for now, it’s important that cyber security professionals are aware of the latest trends in the market. With many platforms creating legitimate uses for generative AI in the fields of sales, marketing and content creation, it may only be a matter of time before generative malware becomes a serious and active risk to data systems worldwide.

Friend or Foe? The Question AI Poses

Ultimately, one must ask whether AI presents itself as an opportunity or an inherent threat to the cybersecurity industry. Generative AI in particular represents the next significant leap since the advent of networked computing, and we must ask ourselves – is AI a friend, or a foe?

One could argue that AI can be beneficial in a number of ways if used correctly. Using AI to support and enhance existing security practices could be a way to enhance corporate security, much like the creation of multi-factor authentication in computer systems. This may be seen as beneficial for small businesses that may not have the time or funding to afford a fully-fledged cyber solution for their business.

Conversely, AI can present significant risks at an operational level. AI may be able to identify and address some anomalous behaviors, but it appears less likely that it will be able to defend against complex, evolving digital attacks as they evolve. With modern security measures such as Captcha being defeated by AI models, it remains to be seen whether security strategies such as the use of multi-factor authentication may also become targets for AI attacks in the future.

The Future of AI in Cyber Security

While it remains to be seen what the negative impacts of AI will have on computer development in the decades ahead, it is readily apparent that the rise of AI will change the way that cybersecurity professionals interact and engage with the networks they use on a day-to-day basis.

It will become imperative for all organizations to stay up with contemporary security trends – more than just regular password updating, but also making sure that both internal and external systems are actively monitored and defended.

AI will undoubtedly become a tool that is used to help identify malicious content – and as bad actors evolve, it will become imperative for cyber security professionals to do the same. With these new and emerging threats on the horizon, it will be fascinating to see how the cybersecurity industry responds to them in the months and years ahead.

Are You Ready to Embrace the Future of Cybersecurity with AI and Data Science?

As the digital landscape evolves, so does the nature of cyber threats. Artificial intelligence and data science are at the forefront of this transformation, both as powerful allies in defense and potential adversaries in the world of cybersecurity. At TDS, we offer cutting-edge AI and data science services to help you stay ahead of cyber threats.

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Don’t wait for the next cyber threat to disrupt your operations. Embrace the future of cybersecurity with TDS. Contact us today to learn more about our services and courses. Together, we can secure your digital future.

Wanna become a data scientist within 3 months, and get a job? Then you need to check this out !