Related papers: Principled Data-Driven Decision Support for Cyber-…
It is imperative for all stakeholders that digital forensics investigations produce reliable results to ensure the field delivers a positive contribution to the pursuit of justice across the globe. Some aspects of these investigations are…
In adversarial machine learning, new defenses against attacks on deep learning systems are routinely broken soon after their release by more powerful attacks. In this context, forensic tools can offer a valuable complement to existing…
In everyday life. Technological advancement can be found in many facets of life, including personal computers, mobile devices, wearables, cloud services, video gaming, web-powered messaging, social media, Internet-connected devices, etc.…
Despite their success and widespread adoption, the opaque nature of deep neural networks (DNNs) continues to hinder trust, especially in critical applications. Current interpretability solutions often yield inconsistent or oversimplified…
Health management has become a primary problem as new kinds of diseases and complex symptoms are introduced to a rapidly growing modern society. Building a better and smarter healthcare infrastructure is one of the ultimate goals of a smart…
Cyber attacks are growing in frequency and severity. Over the past year alone we have witnessed massive data breaches that stole personal information of millions of people and wide-scale ransomware attacks that paralyzed critical…
A digital forensic investigation aims to collect and analyse the evidence necessary to demonstrate a potential hypothesis of a digital crime. Despite the availability of several digital forensics tools, investigators still approach each…
In this paper, we propose a method for addressing the issue of unnoticed catastrophic deployment and domain shift in neural networks for semantic segmentation in autonomous driving. Our approach is based on the idea that deep learning-based…
Fast and accurate detection of cyberattacks is a key element for a cyber-resilient power system. Recently, data-driven detectors and physics-based Moving Target Defences (MTD) have been proposed to detect false data injection (FDI) attacks…
The forensic investigation of cyber attacks and IT incidents is becoming increasingly difficult due to increasing complexity and intensify networking. Especially with Advanced Attacks (AT) like the increasing Advanced Persistent Threats an…
Federated Learning systems are increasingly subjected to a multitude of model poisoning attacks from clients. Among these, edge-case attacks that target a small fraction of the input space are nearly impossible to detect using existing…
This paper studies the attack detection problem in a data-driven and model-free setting, for deterministic systems with linear and time-invariant dynamics. Differently from existing studies that leverage knowledge of the system dynamics to…
The increasing connectivity and intricate remote access environment have made traditional perimeter-based network defense vulnerable. Zero trust becomes a promising approach to provide defense policies based on agent-centric trust…
As control-flow protection gets widely deployed, it is difficult for attackers to corrupt control-data and achieve control-flow hijacking. Instead, data-oriented attacks, which manipulate non-control data, have been demonstrated to be…
Pharmaceutical industry can better leverage its data assets to virtualize drug discovery through a collaborative machine learning platform. On the other hand, there are non-negligible risks stemming from the unintended leakage of…
We expect an increase in the frequency and severity of cyber-attacks that comes along with the need for efficient security countermeasures. The process of attributing a cyber-attack helps to construct efficient and targeted mitigating and…
Decision trees are interpretable models that are well-suited to non-linear learning problems. Much work has been done on extending decision tree learning algorithms with differential privacy, a system that guarantees the privacy of samples…
The frequency and harmfulness of cyber-attacks are increasing every day, and with them also the amount of data that the cyber-forensics analysts need to collect and analyze. In this paper, we propose a formal analysis process that allows an…
Owing to a number of reasons, the deployment of encryption solutions are beginning to be ubiquitous at both organizational and individual levels. The most emphasized reason is the necessity to ensure confidentiality of privileged…
The reliability of cyber forensic evidence acquisition is strongly influenced by the underlying operating systems, Windows, macOS, and Linux - due to inherent variations in file system structures, encryption protocols, and forensic tool…