In the last decade, there has been an increasing adoption of AI in various industries like finance, healthcare, e-commerce, retail, logistics, and more. That’s the reason some cyber attackers now look for potential vulnerabilities to directly attack and exploit AI models. The most common threats are adversarial attacks, i.e. harming AI models to make inaccurate decisions, and data poisoning, which refers to tampering with the training data. The protection of AI systems from these attacks is AI security.

The industries are using AI to protect their systems from malicious cyberattacks. However, the security of AI systems is equally important. In this article, we will help you understand AI security, what the different types of AI security risks are, the role of AI security and much more. Let’s begin with the basics.

What is AI security?

In simple terms, AI security refers to the protection of AI infrastructure from cyberattacks. Since AI has become the main engine behind modern development processes, bringing automation and big data analytics, it becomes extremely important to safeguard AI systems from cyberattacks. AI security works by identifying, assessing, and mitigating potential risks and vulnerabilities associated with artificial intelligence systems.

To improve the AI security we have to leverage the AI security itself:

  • Machine Learning to identify anomalies
    The machine learning algorithms can help in identifying unusual patterns and immediately raise a flag for a quick response.
  • Behavioral Analytics
    AI can build a cohort of common patterns and detect activities having high variation from these patterns. These could be vulnerabilities to address.
  • Security Model Deployment
    AI can monitor and limit model access to authorized individuals and processes while automating model deployment in secure containers.

Types of AI Security Risks

To combat AI security attacks, the foremost thing is to have knowledge of different types of AI security risks. Here are the major AI security risks and AI cyber threats that you must be aware of:

  • Increased Attack Surface As software development companies are leveraging AI tools for developing custom software, they introduce multiple unknown risks. It is similar to the broadening of the attack surface. Here, the major problem arises when the people in charge of security are also in charge of all the AI systems. With the proper knowledge of every aspect of the software, the developers can protect AI and lower the chances of any attack.
  • More chances of data breaches and leaks The broadening of the attack surface includes multiple risks like downtime of the application, disruption, profit losses, deterioration of brand image, and other long-term consequences.
  • Chatbot Credential Theft In the dark web, a new commodity is getting traction, which is the credentials of Gen AI chatbots like ChatGPT. Within 2022-23, nearly 100,000 ChatGPT accounts were compromised. It clearly showcases a dangerous AI security risk that’s likely to increase.
  • Data Poisoning When hackers manipulate the GenAI models used in software, it is referred to as Data Poisoning. The hackers inject various malicious datasets to influence GenAI model outcomes and create biases. 
  • Direct Prompt Injections In this attack, the attackers deliberately design LLM prompts with the intention of compromising or exfiltrating sensitive data. Direct prompt injection introduces various risks, which include the execution of malicious code and the exposure of sensitive data.
  • Hallucination Abuse AI has always been prone to hallucinating particular information. The developers and innovators are endlessly working to reduce the severity of hallucinations. However, until a solid solution arises, these hallucinations will continue to threaten systems. The attackers can register and legitimize potential AI hallucinations, ensuring that end users are influenced and incorrect results.

Benefits of AI Security

AI security delivers a myriad of advantages in protecting digital ecosystems and improving the overall architecture of cybersecurity. The benefits encompass security, efficiency, and resiliency of systems in the face of evolving threats. Let’s understand the role of AI security:

  • Improved Threat Detection

AI systems are capable of analyzing huge amounts of data to identify patterns and anomalies which may indicate cyber threats. In case of any threat, the security and maintenance teams will immediately get alerts about potential breaches, resulting in quick action and minimum damage.

 Furthermore, the ML models also learn continuously from new data. Thus, they become more reliable in detecting sophisticated threats like zero-day vulnerabilities or advanced persistent threats (APTs).

  • Automation

In cybersecurity, there are various manual tasks that get automated using AI and reduce human-prone errors. AI systems constantly monitor networks, endpoints, and applications for vulnerabilities without requiring human involvement. In fact, AI systems can neutralize low-risk threats automatically. It includes threats like isolating infected devices or blocking malicious IP addresses. In comparison to human action, AI-based actions will significantly reduce response times.

  • Scalability

AI security ensures the security of large-scale IT environments by handling Big Data and Cloud Security. In multi-cloud and hybrid environments, AI solutions offer consistent protection by monitoring traffic and ensuring compliance with security policies.

  • Proactive Defense

AI security works on a proactive approach, i.e. unlike humans that react to incidents, AI security predicts and prevents threats before they occur. AI models can utilize historical data to forecast threats and identify weak points in the system.

Recommendations for AI Security Practices

Being a top-notch AI security company, here are some AI security practices that we recommend to our clients:

  • Selection of a tenant isolation framework

You must find and select a tenant isolation framework. It is a powerful way to combat the complexities of GenAI integration. 

  • Customization of GenAI architecture

We always recommend our clients to customize the architecture of GenAI to ensure the security of all components. Some components require shared security boundaries while other needs dedicated boundaries.

  • Evaluate the contours and complexities of GenAI

It is a must to map the implications of integrating GenAI into the products and services of your company. Some important considerations are that your AI models’ responses to end users are private, accurate, and constructed with legitimate datasets.

  • Input sanitization must be a priority

You can put a level of restrictions on the input in GenAI systems for better protection. These restrictions aren’t necessarily required to be highly complicated. For e.g. instead of providing free text options, you can give drop-down menus.

  • Effective and Efficient Sandboxing

Sandboxing refers to taking applications that employ GenAI to isolated test environments and putting them under a scanner. It is a reliable practice to eliminate any AI security vulnerability.

Conclusion:

In this article, we have delved into all the major aspects for understanding AI security, its benefits, role of AI security and a few of the best practices to enhance AI security. Understanding AI security is becoming of paramount importance, considering its role in today’s digital infrastructure and systems. With the advent of GenAI, AI systems have witnessed more traction in the last few years.

We at Cygeniq provide AI-driven cybersecurity solutions that can enhance the security of your AI infrastructure.  Our AI-security solutions are highly secure and scalable to achieve maximum trust and efficiency. A few of our top offerings are Hexashield AI, GRCortex AI, CyberTiX AI, and others. 

Our team has vast experience developing AI security solutions focused on end-to-end security. Our solutions help companies identify and mitigate vulnerabilities and enhance the overall security of digital systems.

Let’s connect to discuss more.