相关论文: MALOnt: An Ontology for Malware Threat Intelligenc…

As computing systems become increasingly advanced and as users increasingly engage themselves in technology, security has never been a greater concern. In malware detection, static analysis, the method of analyzing potentially malicious…

The introduction of transformers has been an important breakthrough for AI research and application as transformers are the foundation behind Generative AI. A promising application domain for transformers is cybersecurity, in particular the…

An important problem of cyber-security is malware analysis. Besides good precision and recognition rate, a malware detection scheme needs to be able to generalize well for novel malware families (a.k.a zero-day attacks). It is important…

In today's world, we are performing our maximum work through the Internet, i.e., online payment, data transfer, etc., per day. More than thousands of users are connecting. So, it's essential to provide security to the user. It is necessary…

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…

The current pandemic situation has increased cyber-attacks drastically worldwide. The attackers are using malware like trojans, spyware, rootkits, worms, ransomware heavily. Ransomware is the most notorious malware, yet we did not have any…

Malware, a persistent cybersecurity threat, increasingly targets interconnected digital systems such as desktop, mobile, and IoT platforms through sophisticated attack vectors. By exploiting these vulnerabilities, attackers compromise the…

Thousands of malicious applications targeting mobile devices, including the popular Android platform, are created every day. A large number of those applications are created by a small number of professional under-ground actors, however…

Malicious software is an integral part of cybercrime defense. Due to the growing number of malicious attacks and their target sources, detecting and preventing the attack becomes more challenging due to the assault's changing behavior. The…

Textual descriptions in cyber threat intelligence (CTI) reports, such as security articles and news, are rich sources of knowledge about cyber threats, crucial for organizations to stay informed about the rapidly evolving threat landscape.…

Organizations are increasingly targeted by Advanced Persistent Threats (APTs), which involve complex, multi-stage tactics and diverse techniques. Cyber Threat Intelligence (CTI) sources, such as incident reports and security blogs, provide…

This project presents a unified detection framework that constructs a complete corpus of Microsoft Graph permissions, generates consistent LLM-based risk scores, and integrates them into a real-time detection engine to identify malicious…

In the current cybersecurity landscape, protecting military devices such as communication and battlefield management systems against sophisticated cyber attacks is crucial. Malware exploits vulnerabilities through stealth methods, often…

The use of machine learning and intelligent systems has become an established practice in the realm of malware detection and cyber threat prevention. In an environment characterized by widespread accessibility and big data, the feasibility…

As the Internet is growing rapidly these years, the variant of malicious software, which often referred to as malware, has become one of the major and serious threats to Internet users. The dramatic increase of malware has led to a research…

The volume of malware and the number of attacks in IoT devices are rising everyday, which encourages security professionals to continually enhance their malware analysis tools. Researchers in the field of cyber security have extensively…

In recent years, there has been a significant surge in malware attacks, necessitating more advanced preventive measures and remedial strategies. While several successful AI-based malware classification approaches exist categorized into…

Each day, anti-virus companies receive tens of thousands samples of potentially harmful executables. Many of the malicious samples are variations of previously encountered malware, created by their authors to evade pattern-based detection.…

In this research paper, our intent is to outline different types of malware, their means of operation, and how they are detected in order to protect yourself against such attacks. Varied permission, and limited technical resources mean that…

LLMs are increasingly explored for malware analysis; however, current LLM-based malware attribution remains limited by unsupported indicators and insufficient code-level grounding for identifying malicious and vulnerable code segments. To…