5 Ways Criminals Are Using AI In Cybersecurity Attacks

Recent technology trends like machine learning and artificial intelligence have become mainstream in recent times, and every industry is reaping the benefits out of it in innovative ways.

AI development has made us realize how accurate the decision-making process could be and appreciating the valuable insights it accompanies.

The Hype Of AI-Backed Cybercrimes

Since every individual industry is implementing AI technology, cyberspace is not at all an exception. AI is recently used by cybercriminals in many ways while bringing a massive threat to businesses and their customers in the long run. Apart from cracking a business network’s passwords, cybercriminals are using AI to create complex malware that can’t be detected or identified by anyone.

Hackers using AI and AI hacking practices are increasing day after day. They are smartly utilizing the power of artificial intelligence in cyber security to access the confidential data of businesses. The sad part is this is only the tip of the iceberg; AI in cyber security has many other things that are worth studying.

How Are Cybercriminals Using AI Technology?

Backed by AI technology, cyber criminals are succeeding to a great extend in hacking sensitive data of global businesses. Though we need to learn ways to combat the growing threat of AI-backed cybercrimes, the foremost step is to be aware of how cybercriminals are making use of AI technology for AI cyber-attacks. So, in this post, we’ll discover the five major areas of how criminals are using AI in cyber security attacks. Without wasting any more time, let’s begin!

1. Algorithmic Manipulation

Cybercriminals are very well aware of the techniques to break AI data systems and manipulate the AI algorithm’s prioritization of information. They adjust the algorithm for changing what an AI system finds as valuable data or not, therefore causing an AI system to damage a business’s complete information system. All these attacks directly affect the AI system’s machine learning process, and these sorts of attacks on AI systems are not at all easy to fix.

2. Surveillance Systems Hacking

As AI video security systems are always creating data based on security footage, the hackers get direct access to the confidential data which is compiled by AI regarding the footage and hack the entire system. As cybercriminals manage to get access to AI-based surveillance footage, they will not only gain physical security footage but will even be able to access data that AI has ascertained about the footage.

2. GAN

Generative adversarial networks are basically sets of two AI systems that simulate data and learn from it. When the interactions are carried out, one system is responsible for presenting the data, and the other spots the errors, which further results in a content set similar to the original content set.

Generative adversarial networks are utilized by cybercriminals for- evading malware detection, password cracking, and deceiving facial recognition algorithms. Hackers use GAN to divert user’s attention away from attacks, mimic the actual traffic patterns, and get access to and exfiltrate sensitive data in no time.

3. Data Poisoning

Data poisoning manipulates the training dataset for controlling the predictive behavior of a trained model that is further responsible for tricking the model into incorrect operating like labeling spam mails as safe content, and so on. Data poisoning is of basically two types- attacks that target a network algorithm’s availability and the ones that target integrity.

4. Bot Manipulation

Since AI algorithms can make accurate decisions, they can be easily manipulated to make the wrong decisions. As hackers tend to understand these models, they can easily misuse and abuse the models, which directly increases businesses’ risk. Hackers figure out how bots are operating a process and further used the bots for tricking the algorithm.

5. The Verdict

Sooner or later, businesses need to be prepared for these unexpected attacks, and as of now, the future of cybersecurity attacks and AI is difficult to predict.

Since more and more businesses are implementing AI in today’s tech-driven landscape, numerous cybersecurity measures are available for protecting sensitive data and AI systems against cyberattacks.

For ensuring business protection, business owners need to stay informed once they implement AI technology in their network and be cautious about potential cybersecurity issues that might affect their business and the customers.

Author Bio

Liza Kosh is a senior content developer and a blogger who loves to share her views on diverse topics. She is currently associated with Seasia Infotech, an Artificial Intelligence Company. She holds great knowledge and experience in technical and creative writing.