Related papers: Survey on Architectural Attacks: A Unified Classif…

For nearly a decade the academic community has investigated backdoors in neural networks, primarily focusing on classification tasks where adversaries manipulate the model prediction. While demonstrably malicious, the immediate real-world…

With the phenomenal growth in the Internet, network security has become an integral part of computer and information security. In order to come up with measures that make networks more secure, it is important to learn about the…

Although adverse effects of attacks have been acknowledged in many cyber-physical systems, there is no system-theoretic comprehension of how a compromised agent can leverage communication capabilities to maximize the damage in distributed…

Modern industrial systems face a growing threat from sophisticated cyberattacks that can cause significant operational disruptions. This work presents a novel methodology for identification of the most critical cyberattacks that may disrupt…

Often, security is considered in an advanced stage of the implementation of a system, rather than integrating it into the system design. This leads to less secure systems, as the security mechanisms are only applied as an afterthought and…

The rise of the Internet of Things and Cyber-Physical Systems has introduced new challenges on ensuring secure and robust communication. The growing number of connected devices increases network complexity, leading to higher latency and…

While previous research backdoored neural networks by changing their parameters, recent work uncovered a more insidious threat: backdoors embedded within the definition of the network's architecture. This involves injecting common…

Future power networks will be characterized by safe and reliable functionality against physical malfunctions and cyber attacks. This paper proposes a unified framework and advanced monitoring procedures to detect and identify network…

Most state-of-the-art machine learning (ML) classification systems are vulnerable to adversarial perturbations. As a consequence, adversarial robustness poses a significant challenge for the deployment of ML-based systems in safety- and…

Architecture erosion (AEr) can adversely affect software development and has received significant attention in the last decade. However, there is an absence of a comprehensive understanding of the state of research about the reasons and…

Graphical security models constitute a well-known, user-friendly way to represent the security of a system. These kinds of models are used by security experts to identify vulnerabilities and assess the security of a system. The manual…

The purpose of this paper is to evaluate the impact of emerging network-centric software systems on the field of software architecture. We first develop an insight concerning the term "network-centric" by presenting its origin and its…

Industrial control systems are critical to the operation of industrial facilities, especially for critical infrastructures, such as refineries, power grids, and transportation systems. Similar to other information systems, a significant…

Machine learning models have been widely adopted in several fields. However, most recent studies have shown several vulnerabilities from attacks with a potential to jeopardize the integrity of the model, presenting a new window of research…

Critical infrastructure networks are a key ingredient of modern society. We discuss a general method to spot the critical components of a critical infrastructure network, i.e. the nodes and the links fundamental to the perfect functioning…

Risk assessment plays a crucial role in ensuring the security and resilience of modern computer systems. Existing methods for conducting risk assessments often suffer from tedious and time-consuming processes, making it challenging to…

By developing communications and increase of access points, computer networks have been vulnerable considerably against wide range of information attacks, specially new and complicated attacks. Every day, replication attacks attack millions…

Numerous works study black-box attacks on image classifiers. However, these works make different assumptions on the adversary's knowledge and current literature lacks a cohesive organization centered around the threat model. To systematize…

In the past, online social networks (OSN) like Facebook and Twitter became powerful instruments for communication and networking. Unfortunately, they have also become a welcome target for socialbot attacks. Therefore, a deep understanding…

This paper is devoted to measuring the security of cyber networks under advanced persistent threats (APTs). First, an APT-based cyber attack-defense process is modeled as an individual-level dynamical system. Second, the dynamic model is…