Related papers: Information-Based Heavy Hitters for Real-Time DNS …

The rapid growth of connected devices has led to the proliferation of novel cyber-security threats known as zero-day attacks. Traditional behaviour-based IDS rely on DNN to detect these attacks. The quality of the dataset used to train the…

In the growing world of the internet, the number of ways to obtain crucial data such as passwords and login credentials, as well as sensitive personal information has expanded. Page impersonation, often known as phishing, is one method of…

Trojans are one of the most threatening network attacks currently. HTTP-based Trojan, in particular, accounts for a considerable proportion of them. Moreover, as the network environment becomes more complex, HTTP-based Trojan is more…

The ability to detect, in real-time, heavy hitters is beneficial to many network applications, such as DoS and anomaly detection. Through programmable languages as P4, heavy hitter detection can be implemented directly in the data-plane,…

The augmentation of Internet of Things (IoT) devices transformed both automation and connectivity but revealed major security vulnerabilities in networks. We address these challenges by designing a robust intrusion detection system (IDS) to…

Denial of service attacks are especially pertinent to the internet of things as devices have less computing power, memory and security mechanisms to defend against them. The task of mitigating these attacks must therefore be redirected from…

Efficient service discovery is a cornerstone of the rapidly expanding Internet of Things (IoT) and edge computing ecosystems, where low latency and localized service provisioning are critical. This paper proposes a novel location-based DNS…

Deep neural networks (DNNs) are now the de facto choice for computer vision tasks such as image classification. However, their complexity and "black box" nature often renders the systems they're deployed in vulnerable to a range of security…

The evolving necessity of the Internet increases the demand on the bandwidth. Therefore, this demand opens the doors for the hackers' community to develop new methods and techniques to gain control over networking systems. Hence, the…

State-of-the-art deep neural networks (DNNs) have been proven to be vulnerable to adversarial manipulation and backdoor attacks. Backdoored models deviate from expected behavior on inputs with predefined triggers while retaining performance…

Network traffic is growing at an outpaced speed globally. The modern network infrastructure makes classic network intrusion detection methods inefficient to classify an inflow of vast network traffic. This paper aims to present a modern…

The rapid expansion of Internet of Things (IoT) systems across various domains such as industry, smart cities, healthcare, manufacturing, and government services has led to a significant increase in security risks, threatening data…

Cloud operators require real-time identification of Heavy Hitters (HH) and Hierarchical Heavy Hitters (HHH) for applications such as load balancing, traffic engineering, and attack mitigation. However, existing techniques are slow in…

Domain name system (DNS) is a crucial part of the Internet, yet has been widely exploited by cyber attackers. Apart from making static methods like blacklists or sinkholes infeasible, some weasel attackers can even bypass detection systems…

Instance Search (INS) is a fundamental problem for many applications, while it is more challenging comparing to traditional image search since the relevancy is defined at the instance level. Existing works have demonstrated the success of…

This survey focuses on intrusion detection systems (IDS) that leverage host-based data sources for detecting attacks on enterprise network. The host-based IDS (HIDS) literature is organized by the input data source, presenting targeted…

The growing number of Internet users and the prevalence of web applications make it necessary to deal with very complex software and applications in the network. This results in an increasing number of new vulnerabilities in the systems,…

Machine learning (ML)-based intrusion detection systems (IDSs) play a critical role in discovering unknown threats in a large-scale cyberspace. They have been adopted as a mainstream hunting method in many organizations, such as financial…

DDoS attacks have become a major threat to the security of IoT devices and can cause severe damage to the network infrastructure. IoT devices suffer from the inherent problem of resource constraints and are therefore susceptible to such…

The rapid development and expansion of World Wide Web and network systems have changed the computing world in the last decade and also equipped the intruders and hackers with new facilities for their destructive purposes. The cost of…