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Security in the fifth generation (5G) networks has become one of the prime concerns in the telecommunication industry. 5G security challenges come from the fact that 5G networks involve different stakeholders using different security…

Mobile malware and mobile network attacks are becoming a significant threat that accompanies the increasing popularity of smart phones and tablets. Thus in this paper we present our research vision that aims to develop a network-based…

The last decades have been characterized by unprecedented technological advances, many of them powered by modern technologies such as Artificial Intelligence (AI) and Machine Learning (ML). The world has become more digitally connected than…

Electric Vehicle (EV) charging infrastructure faces escalating cybersecurity threats that can severely compromise operational efficiency and grid stability. Existing forecasting techniques are limited by the lack of combined robust anomaly…

In the paced realms of cybersecurity and digital forensics machine learning (ML) and deep learning (DL) have emerged as game changing technologies that introduce methods to identify stop and analyze cyber risks. This review presents an…

Advanced Persistent Threats (APTs) are a main impendence in cyber security of computer networks. In 2015, a successful breach remains undetected 146 days on average, reported by [Fi16].With our work we demonstrate a feasible and fast way to…

Intrusion detection systems (IDSs) generate valuable knowledge about network security, but an abundance of false alarms and a lack of methods to capture the interdependence among alerts hampers their utility for network defense. Here, we…

Web Application Firewalls are crucial for protecting web applications against a wide range of cyber threats. Traditional Web Application Firewalls often struggle to effectively distinguish between malicious and legitimate traffic, leading…

Content delivery networks (CDNs) provide efficient content distribution over the Internet. CDNs improve the connectivity and efficiency of global communications, but their caching mechanisms may be breached by cyber-attackers. Among the…

Given sensor readings over time from a power grid, how can we accurately detect when an anomaly occurs? A key part of achieving this goal is to use the network of power grid sensors to quickly detect, in real-time, when any unusual events,…

In the evolving landscape of Federated Learning (FL), the challenge of ensuring data integrity against poisoning attacks is paramount, particularly for applications demanding stringent privacy preservation. Traditional anomaly detection…

The development and implementation of Internet of Things (IoT) devices have been accelerated dramatically in recent years. As a result, a super-network is required to handle the massive volumes of data collected and transmitted to these…

The popularity of 5G networks poses a huge challenge for malicious traffic detection technology. The reason for this is that as the use of 5G technology increases, so does the risk of malicious traffic activity on 5G networks. Malicious…

Anomaly activities such as robbery, explosion, accidents, etc. need immediate actions for preventing loss of human life and property in real world surveillance systems. Although the recent automation in surveillance systems are capable of…

The use of automation in digital forensic investigations is not only a technological issue, but also has political and social implications. This work discusses some challenges with the implementation and acceptance of automation in digital…

Anomalies or failures in large computer systems, such as the cloud, have an impact on a large number of users that communicate, compute, and store information. Therefore, timely and accurate anomaly detection is necessary for reliability,…

Data economy relies on data-driven systems and complex machine learning applications are fueled by them. Unfortunately, however, machine learning models are exposed to fraudulent activities and adversarial attacks, which threaten their…

Network operators and system administrators are increasingly overwhelmed with incessant cyber-security threats ranging from malicious network reconnaissance to attacks such as distributed denial of service and data breaches. A large number…

Blockchain technology has rapidly emerged to mainstream attention, while its publicly accessible, heterogeneous, massive-volume, and temporal data are reminiscent of the complex dynamics encountered during the last decade of big data.…

Automated cyber threat detection in computer networks is a major challenge in cybersecurity. The cyber domain has inherent challenges that make traditional machine learning techniques problematic, specifically the need to learn continually…