How will artificial intelligence affect malware in the future?

As humans move toward the future, the prospects of AI-controlled systems will become more attractive. Artificial intelligence will help people make decisions, power smart cities and, unfortunately, also infect other types of nasty malware.

Let's explore how AI will impact malware in the future through the following article.

What is AI in malware?

When using the term 'AI-controlled malware', readers will easily imagine the scenario: AI causes destruction like a 'killer'. In fact, AI-controlled malicious programs will work stealthily

AI-controlled malware is common malware modified through artificial intelligence to make it more efficient. AI-controlled malware can use its intelligence to infect computers faster or execute attacks more efficiently. Instead of being an 'stupid' network program that adheres to pre-installed code, malware controlled by AI can 'think itself' to some extent.

How does AI empower malware?

There are several ways that artificial intelligence can empower malware. Some of these methods are metaphorical, while others are tangible in the real world in some way.

Typical targeted ransomware is DeepLocker

One of the examples of AI-controlled malware is Deeplocker. Thankfully, IBM Research has developed this malware as a proof of concept you can't find in real life.

The concept of DeepLocker has demonstrated how AI can put ransomware software on a target device. Malware developers may carry out an attack against a company with ransomware, but it is very likely that they cannot infect important computers. Therefore, the warning may rise too soon before the malware reaches its most important targets.

DeepLocker does not activate payloads (payloads). Instead, it merely performs its task as a teleconference program.

When doing its job, it will scan the faces of those who have used it. DeepLocker's goal is to infect a specific person's computer, so it monitors people when they use the software. When it detects the target face, it will activate the payload and cause the PC to be locked by WannaCry.

Worm is adaptive, able to learn from the times it was discovered

One theory of using AI in malware is in theory to use the worm to "remember" every time an antivirus program detects it. Once it knows what action causes an antivirus program to detect itself, it will stop performing that action and find another way to infect the PC.

This is especially dangerous, as modern antivirus software tends to follow strict rules and definitions. That means the action that all worms need to do is find a way not to trigger the alarm. Once it can be successfully implemented, it can notify other virus strains about the defenses in defense, so that they can infect other PCs more easily.

Works independently of malware developers

Current malware is quite 'stupid', unable to 'think for itself' or make decisions. It performs a series of tasks that the malware developer has assigned to it before the infection process occurs. If a malware developer wants it to do something new, they have to provide a follow-up list of malware.

This contact center is called the 'Command and Control' (C&C) server, and it must be extremely well hidden. If this server is detected, hackers can be captured.

However, if malware is able to think for itself, it doesn't need a C&C server anymore. Hackers can leave malware free to run and just sit still while malware does all the work. This means that a malware developer doesn't need to risk ordering. Just set up and let the malware do its job.

Monitor user's voice to get sensitive information

If AI-controlled malware controls the target's microphone, it can listen and record what people are saying nearby. The AI ​​then shares what it hears, converts it into text, then sends the text back to the malware developer. This makes hackers' lives easier, because they don't have to sit for hours recording and uncovering trade secrets.

How can a computer 'learn'?

Malware can learn from its actions through so-called 'machine learning'. This is a specific area of ​​AI, related to how computers can learn from their efforts. Machine learning is very useful for AI developers because they don't need code for every scenario. They tell AI what is right and what is not, then let it learn through trial and error.

When AI, 'trained' by machine learning, faces an obstacle, it will try different methods to overcome it. At first, it will not do very well when overcome challenges, but the computer will recognize what has been done wrong and what can be improved. Over and over again learning and trying, eventually the idea of ​​the 'right' answer will appear.

You can see an example of this process in the video above. The video shows an AI learning how to make different creatures walk properly. The first few generations walk as if they were drunk, but the next generation will start to maintain the correct posture. This is because AI learned from previous failures and did better on the following models.

Malware developers use this power of machine learning to figure out how to properly attack a system. If an error occurs, the system will record this error and note what caused the problem. In the future, malware will adjust the types of attacks for better results.

How can humans fight AI controlled by malware?

The big problem with 'trained' AI with machine learning is that they exploit the way antivirus programs work today. An antivirus software likes to work through simple rules. If a program matches what an antivirus knows to be malicious, anti-virus software will block it.

However, AI-controlled malware will not work according to pre-set fixed rules. It will constantly attack the defense system, trying to find a way through. Once it has entered the system, it can do its job without any problems until the antivirus software receives specific updates for the threat.

So what is the best way to combat this intelligent malware? Sometimes you need to fight fire, and the best way to do that is to offer AI-controlled antivirus programs. These software use fixed rules to catch malware, like many current models. Instead, they analyze what a program is doing and block, if it acts maliciously, in the view of an antivirus program.

The future is determined by artificial intelligence

Simple rules and simple guidelines will not identify future malware attacks. Instead, they will use machine learning to adapt and shape themselves against any security measures they encounter. It may not be as interesting as the way Hollywood portrays malicious AI, but the threat is real.