Related papers: SFCSD: A Self-Feedback Correction System for DNS B…
Domain Name System (DNS) is the backbone of the Internet. However, threat actors have abused the antiquated protocol to facilitate command-and-control (C2) actions, to tunnel, or to exfiltrate sensitive information in novel ways. The…
Traditional anomaly detection techniques onboard satellites are based on reliable, yet limited, thresholding mechanisms which are designed to monitor univariate signals and trigger recovery actions according to specific European Cooperation…
The Internet is composed of Autonomous Systems (ASes) or domains, i.e., networks belonging to different administrative entities. Routing between domains/ASes is realised in a distributed way, over the Border Gateway Protocol (BGP). Despite…
Domain Name System (DNS) domains became Internet-level identifiers for entities (like companies, organizations, or individuals) hosting services and sharing resources over the Internet. Domains can specify a set of security policies (such…
Domain generalization aims to learn a model from multiple training domains and generalize it to unseen test domains. Recent theory has shown that seeking the deep models, whose parameters lie in the flat minima of the loss landscape, can…
The Domain Name System (DNS) is the foundation of a human-usable Internet, responding to client queries for host-names with corresponding IP addresses and records. Traditional DNS is also unencrypted, and leaks user information to network…
Internet users are vulnerable to privacy attacks despite the use of encryption. Webpage fingerprinting, an attack that analyzes encrypted traffic, can identify the webpages visited by a user in a given website. Recent research works have…
Distributed Denial of Service (DDoS) attacks remain a persistent threat to the availability of Internet services, edge networks, and cyber-physical infrastructure. Although recent AI-security work has increasingly focused on foundation…
The feature diversity of different web systems in page elements, submission contents and return information makes it difficult to detect weak password automatically. To solve this problem, multi-factor correlation detection method as…
Cross-domain sentiment analysis (CDSA) helps to address the problem of data scarcity in scenarios where labelled data for a domain (known as the target domain) is unavailable or insufficient. However, the decision to choose a domain (known…
The adoption of Software Defined Networking (SDN) within traditional networks has provided operators the ability to manage diverse resources and easily reconfigure networks as requirements change. Recent research has extended this concept…
This paper proposes a novel Self-Supervised Intrusion Detection (SSID) framework, which enables a fully online Deep Learning (DL) based Intrusion Detection System (IDS) that requires no human intervention or prior off-line learning. The…
Demand-Side Management (DSM) is a vital tool that can be used to ensure power system reliability and stability. In future smart grids, certain portions of a customers load usage could be under automatic control with a cyber-enabled DSM…
Illegitimate reproduction, distribution and derivation of Deep Neural Network (DNN) models can inflict economic loss, reputation damage and even privacy infringement. Passive DNN intellectual property (IP) protection methods such as…
Distributed Denial of Service (DDoS) is one of the most prevalent attacks that an organizational network infrastructure comes across nowadays. We propose a deep learning based multi-vector DDoS detection system in a software-defined network…
Spiking Neural Networks (SNNs) are biologically-inspired deep neural networks that efficiently extract temporal information while offering promising gains in terms of energy efficiency and latency when deployed on neuromorphic devices. SNN…
The metadata aspect of Domain Names (DNs) enables us to perform a behavioral study of DNs and detect if a DN is involved in in-browser cryptojacking. Thus, we are motivated to study different temporal and behavioral aspects of DNs involved…
This work presents the convergence rate analysis of stochastic variants of the broad class of direct-search methods of directional type. It introduces an algorithm designed to optimize differentiable objective functions $f$ whose values can…
The ubiquity of deep neural networks (DNNs), cloud-based training, and transfer learning is giving rise to a new cybersecurity frontier in which unsecure DNNs have `structural malware' (i.e., compromised weights and activation pathways). In…
Distributed Reflective Denial of Service (DRDoS) attacks are an immanent threat to Internet services. The potential scale of such attacks became apparent in March 2018 when a memcached-based attack peaked at 1.7 Tbps. Novel services built…