The AI security conundrum: Finding the balance between innovation and vulnerability

With easy and democratic access to AI tools by the good guys and bad guys alike, even the most tech-savvy organisations will find it challenging to navigate – let alone dodge - a predicted tsunami of AI-powered cyberattacks. Equally tricky to avoid will be the potential for bias, privacy dilemmas, the enigma of AI explainability, and the ever-present threat of yet more regulatory compliance.  

IBM’s “Cost of a Data Breach Report 2023” underscores the financial benefits of leveraging security AI and automation. Organisations that deploy these technologies extensively report substantial cost savings and reduced breach containment times. And that’s great.  

Not so great, though, is that the deployment of AI in security also opens a Pandora's box that should have remained tightly closed. As highlighted by the NCSC (the UK’s National Cyber Security Centre), a new tranche of sophisticated cyber-attacks, including the manipulation of AI through data poisoning and prompt injection attacks, has been let loose upon the world​​. 

Equally worrying is AI's reliance on vast data pools for its learning processes. This reliance introduces vulnerabilities, from data quality issues to adversarial manipulations specifically aimed at deceiving AI systems​​. In its article “Why AI Methods Need Heightened Security,” Forbes stresses the importance of adopting heightened security measures to protect AI models from various attacks and calls out the innovative efforts of those companies who are thankfully pioneering secure AI technologies​​.

So, what are these new attacks emerging from Pandora's box – and why are they so concerning?  

Data poisoning is a cyberattack where the threat actor deliberately compromises the training dataset used by your AI tool or ML (machine learning) model – and influences how it operates. To put this in context, suppose your airport, bank, or shopping mall AI security system is trained to scan and spot anyone entering your building while carrying a gun.

Then, all of a sudden, the system recognises guns as acceptable (as the dataset has been corrupted), and a gun-toting person walks in freely. The outcome could be disastrous.      

Prompt injection attacks are considered to be perhaps the most dangerous of all the techniques targeting AI systems. If you imagine someone standing on the side of a motorway holding up an official-looking speed limit sign of 150km an hour and every AI-enabled car instantly speeding up to meet that new limit (despite it normally being a 100km/h area), then you’ll get the principle of a prompt injection attack. These prompts trick your AI tool into bypassing its normal controls. So, information you thought was safe (because you’d set up access restrictions) can be accessed, and your tool can even be duped into generating malware.  

The intersection of AI and cybersecurity isn’t just a matter of technological advancement. Rather, it’s a pivotal shift in how we protect our digital ecosystems. And there’s a significant degree of urgency when it comes to understanding and appreciating how AI will, on one hand, enhance your cybersecurity defences, yet, on the other, introduce new vulnerabilities.  

For businesses, government entities, and individuals, getting to grips with this knowledge isn’t going to be optional – it will be essential to their survival. For those who don’t take the potential outcomes of security failures seriously, the fallout can be significant. Think: financial losses, fines, reputational damage, and the erosion of hard-won trust.  

Only by understanding AI’s capabilities and risks can stakeholders make informed decisions. Harnessing AI’s power for good requires innovation carefully balanced with security. And this awareness is crucial for developing robust security postures that can withstand the complexities of the modern cyber threat landscape. 

It’s hard not to be excited by AI tools such as ChatGPT or Copilot in the workplace. After all, it’s natural (and very human) to leap at the opportunity to spend less time on menial tasks, improve our productivity, and simply become better at our jobs.   

But it’s also impossible to overlook that AI has become integral to cybersecurity. With over half of employees that use AI at work not disclosing that they're using AI tools to their employer, there is gaping hole in your security waiting to be exploited. 

This means educating ourselves and our fellow employees about its benefits and risks is crucial. Vigilance should be at an all-time high, with training (and constant refresher sessions) on recognising AI-powered phishing attempts, understanding the implications of data poisoning, and appreciating the importance of data privacy. This hyper-awareness needs to extend to the careful scrutiny of AI-generated communications for anomalies, safeguarding your training data, and steadfastly adhering to security best practices.  

In short, being part of a well-informed workforce remains your strongest defence against sophisticated AI-driven threats that can expose, steal, sell, or ransom your valuable personal and company data. 

No one wants to be ‘that person’ whose ill-considered or careless actions directly impact their organisation’s security posture and endanger jobs, client relationships, and finances.  

Here’s our checklist for navigating AI security challenges: 

• Invest in security AI and automation: Embrace these advanced technologies to reduce breach costs and containment times. 
• Beware of AI vulnerabilities: Recognise the risks of AI-powered attacks and the importance of data integrity. These threats are constantly evolving and proliferating in many ways, but we can categorise them into four major categories; evasion, poisoning, privacy and abuse.  
• Prioritise data quality: Ensure the collection and maintenance of high-quality, diverse datasets to train AI models effectively in a securely contained environment.  
• Adopt a Secure-by-Design approach: Integrate security considerations into all stages of AI system development, deployment, and policy creation. 
• Stay compliant and ethical: Ensure AI applications comply with legal standards and ethical considerations, particularly concerning privacy and fairness. The EU Artificial Intelligence Act is leading the world with proposed regulation on AI. As with the General Data Protection Regulation (GDPR), the EU AI Act could become the global standard, and is a good place to start understanding your AI risk exposure. 
• Continuously monitor and update AI systems: Stay vigilant against new threats by regularly updating and monitoring AI systems for vulnerabilities. 

Yes, AI does present us all with significant opportunities to enhance our cybersecurity measures. However, it also requires a balanced approach to navigate its inherent risks.  

It’s only by adopting a proactive, informed stance that your business can successfully harness AI to significantly fortify your cyber defences while mitigating the challenges that come with its use.