**1. Introduction**

What is a Malware? Malware is an umbrella term that refers to anything that is malicious. It can be used to refer to malicious hackers, viruses, or even worms. Malware is a very broad term that refers to any malicious software. Annoying popups, spyware, viruses, ransomware, and worms are all examples of malware.

Identifying the Types of Malware, There are many different types of malware, depending on what the purpose of the attack is. Viruses are malicious software that can replicate themselves and infect files on your computer. Trojans are malicious software that masquerades as something legitimate, like a helpful PDF reader, but actually do something harmful. Worms are software that spreads across networks and computers, like the dreaded WannaCry attack. Spyware collects information about you and your computer's activity without your knowledge. Ransomware can lock your computer or your files until you pay a ransom. Malware can do many different things, but you can protect yourself by keeping your computer clean and being careful about what you download.

How Malware Gets into Image Files, Malware is most commonly found in image files online. The most common cases of this happening are with stock photos from websites like Shutterstock and iStock. Sometimes, malicious software is also embedded in a company's digital images. This malware can do anything from collecting user information to carrying out a denial-of-service (DoS) attack on your company's servers. Websites that include images in their content often receive images from a stock photo website. It's possible that the image may include malicious software. If the website does not have an image scanning system in place, malicious software could make its way onto your website without you even knowing.

The crime-as-a-service field is rapidly evolving, making innovative operating emerging trends available to cybercriminals in order for them to successfully achieve their goals. These technologies have evolved into cyber threats that could be suited to the cryptographic protocols used by consumers and businesses to combat cybercrime. One of the major difficulties is undoubtedly malware classification.

Malware that appears "attractive" today will be obsolete tomorrow, filled by others with wholly distinct or improved features [1]. And all the while, newer isolates of malware collaborate with older varieties. As a result, designation in the malicious cyber environment is highly complex [2, 3].

In such a context, traditional cyber risk intelligence rollbacks and indices (IOCs) are insufficient to combat the threat. Who alters his behavior after learning that he has been identified? The biggest strength of cybersecurity deep learning is its capability to benefit from this evolution in real-time and generate classification criteria without the need for human intervention. This allows us to determine whether a person is communicating with their workstation or an automaton in real-time. Or if a cyber criminal is attempting to steal or interact with a user profile from any part of the community (remote access to a Trojan horse).

Many Facebook users revealed when they inspected a partial shot for hidden photograph tags attached to users' photos that images can undertake a lot of data that is typically inaccessible to the human eye. The type of data linked with Instagram and Facebook pictures and photos is not significant compared to the complex approaches used by targeted attacks to create images that can convey malicious code or embezzle user data. In the past several years, there has been a significant increase in malware advertisements in the wild that use the new technique of data encryption to embed subliminal meaning in photos and files.
