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AI and security: 4 potential risks and how to mitigate them

02/11/2023 minute read OneAdvanced PR

As AI technology continues to evolve and integrate into our daily operations, it brings with it a host of security risks. The increasing sophistication of AI-powered cyber-attacks, inherent vulnerabilities in AI systems, the challenge of protecting sensitive data, and the rise of Shadow IT and AI are all part of this complex landscape. This blog delves into these four key security risks associated with AI and explores how organisations can proactively mitigate these risks, using AI itself as a powerful tool for safeguarding against threats.

Top 4 security risks associated with AI

1.    AI-powered cyber-attacks

Protecting against cyber-attacks is a top priority for organisations of all sizes and sectors, however the rise of AI and its increased application has increased this challenge and resulted in new methods of attack.

AI can be used to boost the ability of cyber-attackers in a few different ways:

  • Making attacks more potent: Using AI, you can make cyber-attacks more potent and difficult to be detected by filters and detection programmes, making them more likely to do damage.
  • Creating new attacks: AI can be used to create fake data to impersonate individuals and create confusion, or even falsely gain credentials to access parts of an organisation that would otherwise be locked away.
  • Automating and scaling attacks: AI lets attackers easily automate and scale attacks without needing to exert many resources, meaning that the level of attacks might reach an unprecedented level.

Organisations need to be aware of these new threats and take proactive action to increase defences against them.

2.    Vulnerabilities in AI systems

While AI systems are incredibly intelligent, they’re not immune to vulnerabilities and other problems.

The main issue with AI systems is that if the AI’s data pool is changed, it can lead to a wholly different outcome. This is known as data poisoning and can be used to mess up whole AI-based systems. By injecting malicious data into the data pool, you can completely change what the AI is outputting and use that to manipulate information.

Another vulnerability is the supply chain. AI development usually integrates third party libraries, meaning that any vulnerabilities in that chain will affect your organisation as well. This is why making sure that you’re vigilant of the tools used within your AI implementation is vital.

3.    Sensitive data protection

AI systems require access to personal information and data to work effectively, so inadequate safeguarding of this data can lead to a possible data breach and sensitive data falling into the wrong hands. 

Using this data, malicious actors can gain access to an organisation’s systems and take advantage of these vulnerabilities to cripple or even hold an organisation hostage, and so being aware of the data that you’re using within your AI implementation is important.

4.    Shadow IT

Shadow IT refers to the unregulated use of IT resources within an organisation, bypassing the oversight of the IT department. This lack of control can potentially introduce significant problems. Similarly, Shadow AI is the unauthorised deployment of AI within your organisation, posing similar risks.

The advent of Generative AI amplifies the challenges posed by Shadow AI, making it a far more substantial problem than Shadow IT. Unlike Shadow IT, where risks primarily emerge during the development phase, Generative AI introduces potential hazards each time it's used. This constant exposure translates into an increased likelihood of data breaches due to the heightened discoverability associated with AI technology.

AI risk mitigation

The best way to fight against the risks that AI bring into your organisation is to fight fire with fire, using AI powered tools to help protect your organisation.

There are a couple of ways to do this:

  • AI powered detection: Using AI to power your threat detection capabilities will allow you to detect threats far before they become an issue, meaning you can stamp them out. Tools like Microsoft Security Copilot use AI to do so, giving you powerful options to ensure that you can stop threats quickly.

  • AI security analytics: Analytics will help you collect data throughout your organisation and investigate new threats and vulnerabilities with ease. Microsoft Security Copilot and Microsoft Sentinel are two of the many tools that give you powerful analytics capabilities to protect your organisation.

The other ways that you can mitigate AI risks is by being vigilant, keeping your organisation’s security hygiene high, and educating people throughout your institution.

By educating others in your organisation, you can ensure everyone is aware of the risks and challenges that you’ll face and ensure that people are doing their bit to make it difficult for any vulnerabilities to present themselves.

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 cyber security 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 cyber security world and create a strategy that’s best for your business specifically.

Want to learn more? Watch our on-demand webinar ‘ChatGPT & Generative AI, the revolution begins’ where experts discuss the latest developments in generative AI technology, showcase applications and use cases, and highlight key areas to focus on when preparing for its opportunities and challenges.