Year: 2023
Type: article
Abstract: Malware, an acronym for "malicious software," refers to any application or piece of code created with the intention of damaging or abusing a computer system, network, or other device.Malware may cause a variety of issues, including data theft, system malfunctions, and unauthorized access.It can appear in many forms, including viruses, worms, Trojan horses, spyware, and ransomware.Attacks by malware are growing more frequent and sophisticated, and they may have serious repercussions for people, companies, and governments.Because of this, malware detection and prevention have emerged as crucial components of cybersecurity, and experts and researchers are continually creating new methods and tools to counter malware threats.The employment of multiple techniques, such as signature-based detection, behavioral analysis, and machine learning-based methodologies, is often required for effective malware detection.These methods can assist in defending against both known and unidentified threats since they seek to detect and stop harmful code before it can damage a system or network.It is vital that cybersecurity experts remain up to speed with the newest advances and employ a variety of defense tactics to counter these attacks as malware threats continue to change and get more complex.The malware binary that is created by transforming it into greyscale will first be converted into picture format as part of our recommended fix.We are utilizing publicly accessible malware picture datasets to train the algorithm.This method allows us to spot new malware mutations since a malware family's pictures never change.This approach makes it incredibly efficient to determine if malware writers have damaged a file or not.
Language: English
Subfield: Software
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4386748111