Artificial Intelligence, Cyber Security

Artificial Intelligence and Cyber-Attacks

Artificial Intelligence and Cyber Attacks

A new generation of business opportunities has been created by artificial intelligence (AI). Through automation and the enhancement of human intelligence, organizations have been able to:

  • Transform Operations
  • Adopt New Business Models
  • Predict Cyber-Attacks
  • Understand Customer Behavior

This capability helps you and your team to prepare for challenges and opportunities before they happen and adapt the associated operations to meet the same. Unfortunately, AI has also empowered cybercriminals. Taking advantage of sophisticated and intelligent technological advances, they can:

  • Counter the limited security capabilities of an average company.
  • Launch large-scale Denial of Service (DoS) attacks
  • Find loopholes in corporate IT networks

AI-enabled cyber-attacks are one of the biggest threats facing organizations today. Let’s examine how this changes the enterprise cyber security landscape of your company.

What is Artificial Intelligence (AI)?

Artificial Intelligence (AI) is a vast field of computer science. It is concerned with building intelligent machines that can complete tasks with ease.

Over the last few years, AI hype has been accelerating. Vendors have been scrambling to promote how their products and services incorporate AI. However, what is referred to as AI is simply one of its components, such as machine learning.

Artificial intelligence requires specialized hardware and software for writing and training machine learning algorithms. No one programming language is synonymous with AI, but a few are well-known, including Python, R, and Java.

Now that we know the concept of Artificial Intelligence, it’s time to move on to the cyber threats posed by the same.

What is AI Cyber-Attacks?

AI cyber-attack is the term for any offensive operations launched on:

  • AI Systems
  • Data
  • The Data Processing Pipeline

Most AI practitioners excel at making sense of information, but they are rarely security experts who can secure their systems and data from cybercriminals.

As a result, adversarial AI is a concept that has emerged both in telecommunications and in cyberspace. Whenever a cyber-attack of this type occurs, it compromises your business’s ability to harness data and artificial intelligence to achieve its full potential.

What are the Most Common Types of Cyber Attacks?

To understand and mitigate potential risks, let’s look at these three AI-focused attack models.

Adversarial Samples

Small sample instances of adversarial samples introduce feature perturbations, which cause AI models to learn from manipulated data and, therefore, classify incorrectly when learning from them. Many of these are counterfactual and cannot be interpreted by machine learning models. Hence, the model becomes a source of incorrect classification decisions.

Training-Data Poisoning

Data poisoning refers to the manipulation of training data by AI practitioners when they train their models.

In addition to altering the original data, cybercriminals can introduce significantly different data sets that are fed into the learning models combined with the altered data once they obtain unauthorized access to the storage network.

AI Model Theft

AI model theft is the switch between designing or seizing AI models. Once a model is fabricated, modified with, and embedded on a vulnerable hardware chip or a cloud network, cybercriminals can:

  • Access the AI systems.
  • Reverse engineer the machine learning (ML)/AI models.

Confidential AI models are deployed on open systems accessible through API questions. Calculations can also be recreated based on the information ingested and conveyed as an output from deployed models.

How to Prevent AI Cyber Attacks?

We suggest you use AI-based security solutions that focus on faster analysis and mitigation of potential threats, which is essential for organizations in situations of latent menace. Artificial intelligence is used in cyber security for vulnerability management, network security, and asset management.

Additionally, as attack methods become more sophisticated, you must decide to deploy automated systems to reduce the burden on cyber security specialists. Rock-solid cyber security measures can help prevent cyber-attacks from well-funded groups, targeting small and large companies, as well as help us, as individuals, to be ready for possible threats like blackmail, ransomware attacks, and data breaches.

Need Cyber Security against AI-based Cyber-Attacks?

Contact Under-Controls Management System.

With Under-Controls Management System, you get to be compliant with standards, create a control framework and KPIs, track objectives and deal with risks and supplier management to get a clear picture of your business and prevent cyber-attacks.

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