Is AI Causing Data Breaches?

This is a major fact of network cybersecurity: Every great new technology brings new problems. Artificial intelligence (AI) is rapidly transforming industries. It offers businesses innovative solutions and automation capabilities. But with this progress comes a growing concern: AI data breaches. As AI becomes more integrated into our systems, the risks increase. The data it collects, analyzes, and utilizes becomes a target.

In the last year, 77% of businesses have experienced a breach of their AI. This poses a significant threat to organizations. A breach can potentially expose sensitive data. As well as compromise intellectual property and disrupt critical operations.

But don’t hit the panic button just yet. We will show you steps you can take to safeguard your company's valuable information, but first, let's explore why AI data breaches are on the rise.

Why are AI Data Breaches Increasing?

There are several factors contributing to the growing instances of AI data breaches:

Expanded Attack Surface: When a technology like AI provides a wider attack surface, as in the number of potential vulnerable entry points, crooks hop right on board. As AI increases, so do the attacks. Hackers can target vulnerabilities in AI models and data pipelines as well as the underlying infrastructure supporting them.

Data Drives Everything: Data is the life’s blood of AI. The massive amount of data collected for training and operation makes a tempting target. This data could include customer information, business secrets, financial records, and even personal details of employees.

Too Big to Understand: Many AI models are complex and opaque. This makes it difficult to identify vulnerabilities and track data flow. This lack of transparency makes it challenging to detect and prevent security breaches.

Threats and Tactics Continue to Evolve: Cybercriminals are constantly developing new methods to exploit security gaps. Techniques like adversarial attacks can manipulate AI models. This can produce incorrect outputs or leak sensitive data.

The Damage Caused by AI Data Breaches

No data breach is ‘good,’ but the consequences of an AI data breach can be far-reaching:

Financial Losses: Data breaches can lead to hefty fines, lawsuits, and reputational damage. This can impact your bottom line significantly.

Disrupted Operations: AI-powered systems are often critical to business functions. A breach can disrupt these functionalities, hindering productivity and customer service.

Intellectual Property Theft: AI models themselves can be considered intellectual property. A breach could expose your proprietary AI models, giving competitors a significant advantage.

Privacy Concerns: AI data breaches can compromise sensitive customer and employee information. This can raise privacy concerns and potentially lead to regulatory action.

How to Protect Your Company from AI Data Breaches: A Proactive Approach

As we said above, hold back on hitting that panic button: take these steps to mitigate the risk of AI data breaches. First, consult with your IT support about the cybersecurity aspects involved, whether you have an internal IT Services Department or outsource it to a Managed Services Provider. Here are some proactive measures to consider:

Establish Data Governance

Adopt robust data governance policies and practices. This includes:

Classifying and labeling data based on sensitivity (if everything is ‘top priority’ then nothing is)

Establishing clear access controls (not everybody needs to know everything)

Regularly monitor data usage (if you want a good yield of eggs, keep an eye on the henhouse)

Design Specific Security for AI

Integrate security considerations into AI development or adoption, which may differ and be stronger than your typical network defenses. Standard procedures for AI projects should be:

Secure coding practices

Vulnerability assessments

Penetration testing

Explainability for Your AI Model

Spend a buck investing in techniques like explainable AI (XAI) that increase transparency in AI models. This allows you to understand how the model arrives at its results and identify potential vulnerabilities or biases.

Pay Special Heed to Threat Modeling

As with all your network defenses, conduct regular threat modelling exercises. These identify potential weaknesses in your AI systems and data pipelines, which helps you rank vulnerabilities and allocate resources for remediation.

Security Awareness Training!

Here at IT Support LA, we harp on keeping your employees aware of threats, how to spot them and what to do about them.  Security Awareness Training educates your employees about AI security threats and best practices for data handling, which empowers them to identify and report suspicious activity.

Updates and Patch Management

Keep all AI software and hardware components current with the latest security patches and general updates. Outdated systems are vulnerable to known exploits, which leaves your data at risk.

Ongoing Security Testing

Security testing of your AI models and data pipelines needs to be regular and ongoing. This work is never finished because it helps identify any vulnerabilities before attackers exploit them.

Stay Informed

Keep yourself informed on the latest AI security threats and best practices. You can do this if you:

Subscribe to reliable cybersecurity publications

Attend industry conferences

Seek out online workshops on AI and security

Develop Partnerships for Enhanced Protection

Consider working with a reputable Managed IT Services outfit that understands AI security. At IT Support LA, we offer expertise in threat detection as well as a vulnerability assessment and penetration testing tailored to AI systems.

Additionally, explore solutions from software vendors who offer AI-powered anomaly detection tools. These tools can analyze data patterns. They identify unusual activity that might suggest a potential breach.