What are AI Attacks?

What are AI Attacks?

AI cyberattacks are a major concern for businesses worldwide. Machine learning and AI are quickly becoming an integral part of society. You'll deal with AI when:

  • Booking plane tickets
  • Receiving quotes for healthcare
  • Searching for information online

With the advent of large language models (LLM), we’re likely to witness even more AI attacks in the future. Offering cybersecurity in Miami, we already foresee an uptick in these types of vulnerabilities in the future.

What are AI Attacks?

AI attacks primarily come in two main forms:

  1. Hackers use AI to perform attacks and rely on machine learning to learn from each attack and find vulnerabilities.
  2. Hackers trick AI into providing the responses that they want. This is an attack on AI systems themselves.

Businesses must be ready to manage both types of attacks because they will increase in the coming years.

How AI Attacks are Performed

AI attacks for both types of attacks are complex and performed differently.

Attacks on AI Systems

An AI system itself can be attacked. For example, there are many times when AI is used to bypass spam or make a system respond in a way that is beneficial to the attacker. A hacker that is trying to get an insurance quote may “confuse” an AI system so that it:

  • Provides a beneficial quote
  • Offers steep discounts or better coverage than expected

It's also possible that an attack may work to damage the AI system in place.

Attacks Using AI

AI tools are state-of-the-art attacks that use AI to try and infiltrate a network. These tools use machine learning to better understand a system and the vulnerabilities that may exist. Automation in cyberattacks is not a new occurrence, but artificial intelligence is becoming more sophisticated.

It's possible to scan networks for common vulnerabilities and work off of failed attempts to try and hack into a network or device.

Solving complex challenges and cracking passwords and credentials is easier with AI tools than it is done manually. Learning to manage attacks and even using machine learning to stop them is something every business must consider.

Managing a New Form of Attacks

AI cyber-attacks require a multi-pronged approach that continues to evolve as threats increase. Security experts must incorporate state-of-the-art monitoring systems that work to identify threats and stop them before they are successful.

Even government agencies are working to strengthen their security against AI because the number of threats is increasing.

Additionally, for systems that rely on AI, a stronger focus on security, parameters and filters will be necessary. “Tricking” these systems to operate in a certain manner requires a lot of internal controls that developers must work on and learn about.

As with any software and new technologies, you’ll need to be agile and ready to adapt to threats that change rapidly.

Businesses that incorporate AI into their operations will need to consider increasing their cybersecurity measures. AI attacks do not lower the risk of traditional cyberattacks. Instead, a compounding effect will occur, meaning companies must begin thwarting attacks on two fronts and not just one.