Related papers: Devising Malware Characterstics using Transformers

Recently, a considerable amount of malware research has focused on the use of powerful image-based machine learning techniques, which generally yield impressive results. However, before image-based techniques can be applied to malware, the…

The number of malicious software (malware) is growing out of control. Syntactic signature based detection cannot cope with such growth and manual construction of malware signature databases needs to be replaced by computer learning based…

Machine learning progress is advancing the detection of malicious URLs. However, advanced Transformers applied to URLs face difficulties in extracting local information, character-level details, and structural relationships. To address…

Malware affects millions of users worldwide, impacting the daily lives of many people as well as businesses. Malware infections are increasing in complexity and unfold over a number of stages. A malicious downloader often acts as the…

In recent years, malware with tunneling (or: covert channel) capabilities is on the rise. While malware research led to several methods and innovations, the detection and differentiation of malware solely based on its DNS tunneling features…

Modern malware evolves various detection avoidance techniques to bypass the state-of-the-art detection methods. An emerging trend to deal with this issue is the combination of image transformation and machine learning techniques to classify…

By their very nature, malware samples employ a variety of techniques to conceal their malicious behavior and hide it from analysis tools. To mitigate the problem, a large number of different evasion techniques have been documented over the…

Code metamorphism refers to a computer programming exercise wherein the program modifies its own code (partial or entire) consistently and automatically while retaining its core functionality. This technique is often used for online…

Malware analysis is still largely a manual task. This slow and inefficient approach does not scale to the exponential rise in the rate of new unique malware generated. Hence, automating the process as much as possible becomes desirable. In…

In this paper, we present a novel method of differentiating known from previously unseen malware families. We utilize transfer learning by learning compact file representations that are used for a new classification task between previously…

The widespread adoption of Large Language Models (LLMs) in critical applications has introduced severe reliability and security risks, as LLMs remain vulnerable to notorious threats such as hallucinations, jailbreak attacks, and backdoor…

Modern infrastructures rely on software systems that remain vulnerable to cyberattacks. These attacks frequently exploit vulnerabilities documented in repositories such as MITRE's Common Vulnerabilities and Exposures (CVE). However, Cyber…

Most behavioral detectors of malware remain specific to a given language and platform, mostly PE executables for Windows. The objective of this paper is to define a generic approach for behavioral detection based on two layers respectively…

The increasing number of sophisticated malware poses a major cybersecurity threat. Portable executable (PE) files are a common vector for such malware. In this work we review and evaluate machine learning-based PE malware detection…

Malware are becoming a major problem to every individual and organization in the cyber world. They are advancing in sophistication in many ways. Besides their advanced abilities to penetrate and stay evasive against detection and…

The use of TLS by malware poses new challenges to network threat detection because traditional pattern-matching techniques can no longer be applied to its messages. However, TLS also introduces a complex set of observable data features that…

Despite defensive advances in the Internet realm, Malware (malicious software) remains a Cybersecurity threat. These days, Malware can be purchased and licensed on the Internet to further customize and deploy. With hundreds of Malware…

Malware detection has become a major concern due to the increasing number and complexity of malware. Traditional detection methods based on signatures and heuristics are used for malware detection, but unfortunately, they suffer from poor…

Successful malware attacks on information technology systems can cause millions of dollars in damage, the exposure of sensitive and private information, and the irreversible destruction of data. Anti-virus systems that analyze a file's…

Research shows that over the last decade, malware has been growing exponentially, causing substantial financial losses to various organizations. Different anti-malware companies have been proposing solutions to defend attacks from these…