How to Protect your Business from AI Cyber Attacks

The Bank of England has warned that Artificial Intelligence could be a threat to financial security.

While it’s certain that AI-based systems can be manipulated by cybercriminals, there are so many preventative measures available for businesses to use. With protection in place, businesses can operate in full confidence.

Whether you’re thinking of starting a new business or you’ve been heading the same firm for decades, it’s worth knowing about AI attacks and how to keep your company safe.

How are cyberattacks becoming more advanced?

Government figures suggest that of all businesses that reported a cyber-attack in 2023, 83% encountered a phishing attack. But cybercrime is no longer limited to the risks posed by these phishing attacks and typical approaches to hacking.

AI-based platforms have planted the seed for more complicated forms of malicious activity. Now, deepfakes are quickly becoming one of the most pressing issues for high-profile individuals and companies. This is a term used to describe the manipulation of one image onto another, which often creates false but realistic images.

The development of AI-generated cyberattacks

AI attacks pose a considerable threat to digital identity security, data privacy laws, and personal safety. There are four key types of AI-based attacks worth knowing about:

• Poisoning: Data poisoning involves the modification of sensitive company or employee information. It could be replaced, modified, or altered with fabricated data injected into it. This can prompt considerable loss of reputation and carry financial consequences too.

• Inference: In this type of attack, a machine learning model draws conclusions from unaltered data. Essentially, the system applies logical rules to run live data through a pre-programmed model, resulting in predictions or decisions. Inference can trigger major leaks, which should prompt any firm to seek professional support from data protection lawyers.

• Extraction: Data extraction involves training an attack model. This means that a malicious source can collect and interpret data after accessing the victim model. To do this, it is usually disguised by very similar coding to the familiar input.

• Evasion: Evasion is described as a purposeful attempt to make a machine learning model deliver (or output) incorrect results. This is achieved by disturbing the data initially sent to the trained model. An evasion attack alters model behaviours and could result in total system sabotage, risking personal safety.

How to prevent AI cyberattacks

Following these five key strategies could help your company to mitigate the risks of AI-based cyberattacks. These include:

1. Frequent AI audits: If your company uses AI systems, they need to be reviewed regularly. Check with your internal experts for any security flaws or inconsistent data.
2. Limited access: Your AI-based systems should be protected and restricted. Only allow trusted, vetted employees to access them and make changes.
3. Staff training: Your team need to be aware of the risks. Ensure thorough training to raise awareness of mitigation and safety.
4. Strict data security: Protecting your company starts and ends with robust GDPR and privacy protocol. Never neglect your responsibility to keep sensitive data safe.
5. Incident response: Before your company is attacked, you need to know how you’ll respond. Run trials and ensure that every member of staff knows the drill.