Related papers: Oops!...I think I scanned a malware
With the increasing reliance of smart grids on correctly functioning SCADA systems and their vulnerability to cyberattacks, there is a pressing need for effective security measures. SCADA systems are prone to cyberattacks, posing risks to…
Nowadays security is major concern for any user connected to the internet. Various types of attacks are to be performed by intruders to obtaining user information as manin-middle attack, denial of service, malware attacks etc. Malware…
Malware represents a significant security concern in today's digital landscape, as it can destroy or disable operating systems, steal sensitive user information, and occupy valuable disk space. However, current malware detection methods,…
The financial industry relies on deep learning models for making important decisions. This adoption brings new danger, as deep black-box models are known to be vulnerable to adversarial attacks. In computer vision, one can shape the output…
Smartphones have become an intrinsic part of human's life. The smartphone unifies diverse advanced characteristics. It enables users to store various data such as photos, health data, credential bank data, and personal information. The…
Capsule Networks preserve the hierarchical spatial relationships between objects, and thereby bears a potential to surpass the performance of traditional Convolutional Neural Networks (CNNs) in performing tasks like image classification. A…
Software-defined networking (SDN) eases network management by centralizing the control plane and separating it from the data plane. The separation of planes in SDN, however, introduces new vulnerabilities in SDN networks since the…
A survey of machine learning techniques trained to detect ransomware is presented. This work builds upon the efforts of Taylor et al. in using sensor-based methods that utilize data collected from built-in instruments like CPU power and…
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…
Malware is a piece of software that was written with the intent of doing harm to data, devices, or people. Since a number of new malware variants can be generated by reusing codes, malware attacks can be easily launched and thus become…
Cybersecurity education is considered an important part of undergraduate computing curricula, but many institutions teach it only in dedicated courses or tracks. This optionality risks students graduating with limited exposure to secure…
Deep packet inspection is widely recognized as a powerful way which is used for intrusion detection systems for inspecting, deterring and deflecting malicious attacks over the network. Fundamentally, almost intrusion detection systems have…
Research and development of techniques which detect or remediate malicious network activity require access to diverse, realistic, contemporary data sets containing labeled malicious connections. In the absence of such data, said techniques…
Machine learning and neural networks have become increasingly popular solutions for encrypted malware traffic detection. They mine and learn complex traffic patterns, enabling detection by fitting boundaries between malware traffic and…
Practical quantum communication (QC) protocols are assumed to be secure provided implemented devices are properly characterized and all known side channels are closed. We show that this is not always true. We demonstrate a laser-damage…
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…
Cyber security can be enhanced through application of machine learning by recasting network attack data into an image format, then applying supervised computer vision and other machine learning techniques to detect malicious specimens.…
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, or software designed with harmful intent, is an ever-evolving threat that can have drastic effects on both individuals and institutions. Neural network malware classification systems are key tools for combating these threats but…
In this paper, we show that attackers can exfiltrate data from air-gapped computers via Wi-Fi signals. Malware in a compromised air-gapped computer can generate signals in the Wi-Fi frequency bands. The signals are generated through the…