Related papers: Enhancing Enterprise Network Security: Comparing M…

In the presence of security countermeasures, a malware designed for data exfiltration must do so using a covert channel to achieve its goal. Among existing covert channels stands the domain name system (DNS) protocol. Although the detection…

Malware has been one of the most damaging threats to computers that span across multiple operating systems and various file formats. To defend against ever-increasing and ever-evolving malware, tremendous efforts have been made to propose a…

Enterprise networks are in constant danger of being breached by cyber-attackers, but making the decision about what security tools to deploy to mitigate this risk requires carefully designed evaluation of security products. One of the most…

Coping with malware is getting more and more challenging, given their relentless growth in complexity and volume. One of the most common approaches in literature is using machine learning techniques, to automatically learn models and…

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…

My research lies in the intersection of security and machine learning. This overview summarizes one component of my research: combining computer vision with malware exploit detection for enhanced security solutions. I will present the…

With the development in the field of smartphones and ever growing base of Internet, various softwares are left prone to many malicious activities like pharming, phishing, ransomware, spam, spoofing, spyware, eavesdropping, etc. These…

Robot systems are increasingly integrating into numerous avenues of modern life. From cleaning houses to providing guidance and emotional support, robots now work directly with humans. Due to their far-reaching applications and…

The present thesis addresses the topic of denial of service capabilities detection at malware binary level, with the aim of designing a framework that integrate results from different binary analysis methods and decide on the DDoS…

Converting malware into images followed by vision-based deep learning algorithms has shown superior threat detection efficacy compared with classical machine learning algorithms. When malware are visualized as images, visual-based…

Detection and analysis of a potential malware specifically, used for ransom is a challenging task. Recently, intruders are utilizing advanced cryptographic techniques to get hold of digital assets and then demand a ransom. It is believed…

The rapid evolution of malware has necessitated the development of sophisticated detection methods that go beyond traditional signature-based approaches. Graph learning techniques have emerged as powerful tools for modeling and analyzing…

Nowadays, malware and malware incidents are increasing daily, even with various antivirus systems and malware detection or classification methodologies. Machine learning techniques have been the main focus of the security experts to detect…

Over past years, the manually methods to create detection rules were no longer practical in the anti-malware product since the number of malware threats has been growing. Thus, the turn to the machine learning approaches is a promising way…

Following the increasing popularity of mobile ecosystems, cybercriminals have increasingly targeted them, designing and distributing malicious apps that steal information or cause harm to the device's owner. Aiming to counter them,…

We consider the problem of detecting malware with deep learning models, where the malware may be combined with significant amounts of benign code. Examples of this include piggybacking and trojan horse attacks on a system, where malicious…

One of the pivotal security threats for the embedded computing systems is malicious software a.k.a malware. With efficiency and efficacy, Machine Learning (ML) has been widely adopted for malware detection in recent times. Despite being…

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…

Increasingly, malwares are becoming complex and they are spreading on networks targeting different infrastructures and personal-end devices to collect, modify, and destroy victim information. Malware behaviors are polymorphic, metamorphic,…

Providing security for information is highly critical in the current era with devices enabled with smart technology, where assuming a day without the internet is highly impossible. Fast internet at a cheaper price, not only made…