As AI is put in the hands of keen product development teams around the world, there are some infosec concerns and issues that need to be addressed. How do we manage cybersecurity for AI?
On the other hand, AI and machine learning can also be used to improve cybersecurity. AI can be both an infosec liability and an asset.
Here are some key pointers about infosec and the use of AI.
Confused about what AI is? We break down the term in our blog here.
AI systems pose certain cybersecurity and infosec risks
AI systems are open to cybersecurity threats and risks, probably the main one being the vulnerability of the AI models themselves.
Some of the main infosec risks associated with AI:
- AI models can be vulnerable to attacks that alter, modify, or mislead the model. Ensure that your input is protected. (And remember that AI models themselves are not perfect and can be biased – more on that below).
- Data privacy is a major security threat, as AI models can leak out sensitive data. Differential privacy may help you here, but you should also limit how much data is available to model. (Read our guide to AI and data protection here).
- Lack of policies and understanding around AI means that regulations are developing alongside the technology, even lagging behind. Even if you listen to current regulations, you may not actually be in the clear. In order to follow best practice, you should educate yourself on the wider issues surrounding AI.
- Lack of human control is another potential infosec issue. If you just let AI models “run the show”, you will likely run into infosec issues. Here is our guide on AI in content production for publishers.
Cybersecurity for AI: some ideas on making your systems safe
So how can you make your AI systems as safe as possible? Here are some AI cybersecurity tips and ideas:
- Encrypt your data (at rest and in transit) to prevent unauthorised access. Protecting your data is one of the most important things you can do.
- Access controls and identity management should be robust. As always, access issues are often the hardest to tackle, but the ones that also bring the biggest infosec benefits.
- Vulnerability assessments and audits will help you stay on top of your AI usage. Have you an idea of what an attack on your AI systems would look like? What sorts of processes should you be following if you find a vulnerability?
- It goes without saying, but using reputable vendors and suppliers is always a good idea. Read the terms & conditions of the AI products you are using.
📝This is a good blog on the intersection between AI and cybersecurity to help you navigate this issue as a business.
AI + information security = force for good?
AI can also be used to counter cyberattacks and manage infosec risks. Like all things, AI can be used for both positive and negative outcomes, so be smart and use AI to combat risks to help upgrade your own cybersecurity systems.
Here are some ways that AI can be used for infosec and cybersecurity:
- Machine learning is great at detecting threats through anomaly and pattern recognition.
- Automated threat responses fuelled by AI can help your business respond to threats faster.
- Incident response times can be kept down and processes can be refined with AI. AI can really help your business with overall preparedness.
- NLP can be used to analyse communications and text for phising or malicious intent.
Compliance: the big AI sticking point
Compliance hasn’t caught up with the tech, and businesses are often operating in a deadzone when it comes to AI and infosec and data protection compliance. That doesn’t mean you don’t have responsibilities; it just means that you may have to work harder to follow best practice.
Keep in mind the following key issues to help you leverage AI in a safe and compliant way:
- Data protection laws like GDPR and CCPA are the big ones that you will need to factor into your AI usage. Follow infosec and cybersecurity blogs and publishers for ideas on how legislation is likely to develop in the future.
- Ethical AI is one of the biggest burgeoning issues of our times. Discrimination is a big issue in data models, and you need to take this into account.
- Transparency and accountability are two keywords that should guide your AI usage. Are you disclosing your AI usage? How do you ensure the integrity of the models you use? Do you have enough human intervention?
📝Here is how the concept of AI information security is developing – including issues of human stewarding of AI.
Staff and stakeholder training and comms
As always, communicating about AI is an important element of the AI pipeline. As an organisation, you should be having conversations about AI to help you use it safely.
- Staff and stakeholder training is key to helping people improve and develop their own AI literacy.
- Creating a security culture is very important as it will help embed infosec and cybersecurity best practices into everything that you do.
- Stay informed and involved when it comes to AI developments. Joining professional bodies or organisations is one way to help stay on top of AI developments and applications.
- Cultivate threat intelligence in your organisation and to ensure that infosec and cybersecurity concerns ara taken seriously.
General pointers & takeaways
So, what can you do to ensure that the way your business uses AI is done in the most secure way?
- Your business should be adapting all the time, and AI is no different. Be alive to changes happening in the AI space. Don’t use loopholes and cheap tactics.
- A culture of “it’s never done” is a good way to approach infosec. Don’t rest on your laurels but keep developing and upgrading your systems.
- Don’t be intimidated by AI and all the jargon that goes without. It’s a brilliant thing to use as a business, and you should be able to make the most of it.
- Be wary of models running wild without human intervention. This is how biases can develop.
- Be strict about AI disclosure and write your own company AI policies as well.
By integrating AI with robust information security practices, publishers and businesses can better protect their digital assets, maintain customer trust, and stay ahead of potential threats in an increasingly complex cyber landscape. Keen to learn more about AI? Check out our blog on how AI is revolutionising publishing or peruse our TimeAI products for ideas on how publishers can benefit from AI.
