In the past few months and years, one thing has become certain in the technological world — artificial intelligence (AI) is here to stay.
As new AI-based technologies are developed and explored both by individuals and businesses around the world, the onslaught of AI has meant that there are a number of cybersecurity risks to now consider in the modern world. This is due to the sheer power of AI — to lots of malevolent actors, AI is simply a tool to cause more havoc and harm to their targets.
However, for businesses, AI also provides a powerful opportunity to get ahead of those same people. That’s why in this article, we’re going to go over everything that you need to know regarding AI and cybersecurity.
The Rise of AI in 2023
Recently, artificial intelligence (AI) has taken the world by storm. With new AI technologies like ChatGPT and Midjourney providing revolutionary services with a simple entry of a prompt, there’s no wonder that the world is enamoured by the ever-growing capabilities that AI has displayed.
With this, though, comes a question of ethics and morality in many forms. Specifically regarding security and business, though, AI has given a tremendous amount of power to further allow malicious threats to engineer their way to wreak havoc on individuals and businesses alike.
This is why knowing the threats that you could face — and how you can utilise AI to reduce your vulnerability to them — is so important for any organisation.
AI in Cybersecurity
Generative AI Phishing Attacks
A phishing attack is an attack that aims to make someone malicious appear as though they’re a trusted entity, to gain credentials. This attack is a very common social engineering attack, and — while quite transparent now — can be very effective if the victim is unprepared.
AI essentially helps speed up this process and make it more realistic and effective — these new attacks are much harder to spot at face value than the phishing attacks of old, and AI lets them specifically target demographics of people.
AI-powered Malware Attacks
AI-powered malware is malware that’s been trained using machine learning to be more powerful and effective than traditional malware. The malware used is much smarter — essentially being able to adaptively think for itself instead of using a preprogrammed directive.
This means that AI-powered malware is now smarter and more effective, and will specifically target and spread to victims far more easily than ever.
AI Dataset Poisoning
AI dataset poisoning is a way to corrupt the training and output of an AI. By poisoning the data that it uses to train, it’s possible to change an AI to become malicious and essentially teach it to do things that are at best malicious, and at worse massively destructive.
This is because every AI progressively learns from some kind of dataset. It takes the data given to it and forms intelligence based on it, meaning that corrupting that process can have massive repercussions down the line.
AI-based Malware Detection and Response
Just as AI can power up malware, it can also power up malware response tools and systems to be faster and more accurate.
By using AI-powered malware detection tools, you can spot potential threats and malware faster and stamp it out far more efficiently — as an AI will be able to adaptively monitor and deal with malware far more effectively than a human or a simple human-coded program.
Avoid Human Errors
A lot of breaches and hazards come from human error, due to the fact that humans simply make mistakes sometimes.
If programmed correctly, artificial intelligence is unable to make a mistake due to being trained purely on a dataset without letting emotion, fatigue, or any other human trait affect the output.
By identifying weaknesses in your organisation that can be automated with ease, you can easily mitigate the risk of human error using a well-trained artificial intelligence model dedicated to the tasks required.
Combat the Cybersecurity Skills Shortage
As the world becomes more advanced, the demand for cybersecurity personnel goes up.
However, there is a major skills shortage in these areas due to the lack of supply to meet that demand — with how new and quickly technology is evolving, not a lot of people are trained or knowledgeable enough about newer technologies and threats.
With a large dataset that can pull from anywhere, AI helps combat this — it can teach you anything you need to know about cybersecurity and help you strategise and mobilise the security measures that will be most effective for your organisation with ease.
Benefit From Larger Datasets
Utilising new and advanced AI technologies means that you have a larger data pool, due to the sheer power and knowledge of newer AI models.
This means that you have access to a larger dataset right at your fingertips — which can have benefits for machine learning and AI applications throughout your organisation. A larger dataset means finding trends is both easier and more effective.
This has benefits throughout your organisation but — regarding cybersecurity specifically — means that you’ll be able to detect threats more quickly and easily by spotting patterns and trends, and have a much smarter intelligence tool available for cybersecurity.
Want to Find Out More?
With the rapid advancement of AI technologies, there are lots of drawbacks and opportunities for businesses to consider.
Where before, threats simply existed within the realm of human intelligence and possibility, AI is rapidly making it easier for new attacks to cause damage to organisations — and for new ways to stop them.
If you’re looking for new ways to implement AI into your business and ensure that your cybersecurity strategy is completely futureproof, get in touch with us today. Our experts will be able to help you ensure that your business is able to mitigate the risks and issues of an AI-based cybersecurity world — and create a strategy that’s best for your business specifically.
Reach out to us today and see how we can help.
If you want to learn more on this subject we include 5 books:
Buczak, A. L., & Guven, E. (2016). A survey of data mining and machine learning methods for cyber security intrusion detection. IEEE Communications Surveys & Tutorials, 18(2), 1153-1176. This paper provides a comprehensive survey on the application of AI in detecting cyber intrusions, and discusses the concerns associated with false positive and negative rates.
Taddeo, M., & Floridi, L. (2018). Regulating artificial intelligence and robotics: ethics by design in a digital society. Contemporary Issues in Law, 14(1), 129-148. This article highlights the ethical issues related to AI and cybersecurity, including data privacy, bias, and robustness of AI algorithms.
Akhtar, Z., & Saeed, S. (2019). An artificial intelligence-based cybersecurity framework for protected health information. IEEE Access, 7, 73090-73101. This paper discusses the concerns of using AI to protect sensitive health information, and how to address these concerns through a well-designed cybersecurity framework.
Brundage, M., Avin, S., Clark, J., Toner, H., Eckersley, P., Garfinkel, B., Dafoe, A., Scharre, P., Zeitzoff, T., Filar, B., & Anderson, H. (2020). Toward trustworthy AI development: mechanisms for supporting verifiable claims. arXiv preprint arXiv:2004.07213. This paper delves into the issues of trust and verifiability in AI development, both of which are critical in the context of cybersecurity.
Shrobe, H., Shrier, D., & Pentland, A. (2021). New solutions for cybersecurity. MIT Press. This book provides a comprehensive discussion on the latest solutions for cybersecurity, with a particular focus on the role of AI. It highlights the potential risks and concerns associated with using AI for cybersecurity, and offers solutions to mitigate these risks.