Related papers: The Architectural Dynamics of Encapsulated Botnet …

The rapid growth of the Internet of Things (IoT) has expanded opportunities for innovation but also increased exposure to botnet-driven cyberattacks. Conventional detection methods often struggle with scalability, privacy, and adaptability…

Today, several people and organizations rely on cloud platforms. The reliability of cloud platforms depends heavily on the performance of their internal programs (agents). To better prevent regressions in cloud platforms, the design of…

Detecting social bots has evolved into a pivotal yet intricate task, aimed at combating the dissemination of misinformation and preserving the authenticity of online interactions. While earlier graph-based approaches, which leverage…

Recent advancements in social bot detection have been driven by the adoption of Graph Neural Networks. The social graph, constructed from social network interactions, contains benign and bot accounts that influence each other. However,…

AI-powered edge computing security is moving Intelligent Transportation Systems (ITS) from passive, rule-based protections to proactive, smart, zero-touch, self-sufficient safeguards that neutralize threats in milliseconds. As…

In recent years, there has been a shift in computing architectures, moving away from centralized cloud computing towards decentralized edge and fog computing. This shift is driven by factors such as the increasing volume of data generated…

Power electronic systems (PES) face significant threats from various data availability and integrity attacks, significantly affecting the performance of communication networks and power system operation. As a result, several attack…

Network embedding has recently emerged as a promising technique to embed nodes of a network into low-dimensional vectors. While fairly successful, most existing works focus on the embedding techniques for static networks. But in practice,…

Additive manufacturing (AM) is rapidly integrating into critical sectors such as aerospace, automotive, and healthcare. However, this cyber-physical convergence introduces new attack surfaces, especially at the interface between…

Edge nodes are crucial for detection against multitudes of cyber attacks on Internet-of-Things endpoints and is set to become part of a multi-billion industry. The resource constraints in this novel network infrastructure tier constricts…

Architectural backdoors pose an under-examined but critical threat to deep neural networks, embedding malicious logic directly into a model's computational graph. Unlike traditional data poisoning or parameter manipulation, architectural…

Block-chain world is very dynamic and there is need for strong governance and underlying technology architecture to be robust to face challenges. This paper considers Ethereum, a leading block chain. We deep dive into the nature of this…

This proposes a novel ensemble deep learning-based model to accurately classify, detect and localize different defect categories for aggressive pitches and thin resists (High NA applications).In particular, we train RetinaNet models using…

The rapid increase of diverse Internet of things (IoT) services and devices has raised numerous challenges in terms of connectivity, computation, and security, which networks must face in order to provide satisfactory support. This has led…

Following the recent adoption of deep neural networks (DNN) accross a wide range of applications, adversarial attacks against these models have proven to be an indisputable threat. Adversarial samples are crafted with a deliberate intention…

Mixnets provide strong meta-data privacy and recent academic research and industrial projects have made strides in making them more secure, performance, and scalable. In this paper, we focus our work on stratified Mixnets -- a popular…

Many security issues have come to the fore with the increasingly widespread adoption of Internet-of-Things (IoT) devices. The Mirai attack on Dyn DNS service, in which vulnerable IoT devices such as IP cameras, DVRs and routers were…

Over the past decade, the Cyberspace has seen an increasing number of attacks coming from botnets using the Peer-to-Peer (P2P) architecture. Peer-to-Peer botnets use a decentralized Command & Control architecture. Moreover, a large number…

Deep Neural Networks (DNN) are vulnerable to adversarial perturbations-small changes crafted deliberately on the input to mislead the model for wrong predictions. Adversarial attacks have disastrous consequences for deep learning-empowered…

Recently, there has been an interest in improving the resources available in Intrusion Detection System (IDS) techniques. In this sense, several studies related to cybersecurity show that the environment invasions and information kidnapping…