Related papers: Contrasting global approaches for identifying and …
Machine learning models have made many decision support systems to be faster, more accurate, and more efficient. However, applications of machine learning in network security face a more disproportionate threat of active adversarial attacks…
This report presents a taxonomy of vulnerabilities created as a part of an effort to develop a framework for deriving verification and validation strategies to assess software security. This taxonomy is grounded in a theoretical model of…
In the realm of cybersecurity, phishing stands as a prevalent cyber attack, where attackers employ various tactics to deceive users into gathering their sensitive information, potentially leading to identity theft or financial gain.…
Advanced software supply chain (SSC) attacks are increasingly runtime-only and leave fragmented evidence across hosts, services, and build/dependency layers, so any single telemetry stream is inherently insufficient to reconstruct full…
Developing intelligent, interoperable Cyber Threat Information (CTI) sharing technologies can help build strong defences against modern cyber threats. CTIs allow the community to share information about cybercriminals' threats and…
The purpose of the study is to supplement and update the list of threats to the confidentiality and integrity of the system. The article focuses on the already compiled list of threats and a model of system, but also considers new threats…
Machine learning is gaining popularity in the network security domain as many more network-enabled devices get connected, as malicious activities become stealthier, and as new technologies like Software Defined Networking emerge.…
Differential Privacy (DP) is a mathematical framework that is increasingly deployed to mitigate privacy risks associated with machine learning and statistical analyses. Despite the growing adoption of DP, its technical privacy parameters do…
Globalization has introduced many new challenges making Supply chain management (SCM) complex and huge, for which improvement is needed in many industries. The Internet of Things (IoT) has solved many problems by providing security and…
We use a methodology based on a machine learning algorithm to quantify firms' cyber risks based on their disclosures and a dedicated cyber corpus. The model can identify paragraphs related to determined cyber-threat types and accordingly…
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…
Traditional Cyber-physical Systems(CPSs) were not built with cybersecurity in mind. They operated on separate Operational Technology (OT) networks. As these systems now become more integrated with Information Technology (IT) networks based…
Software supply chains, while providing immense economic and software development value, are only as strong as their weakest link. Over the past several years, there has been an exponential increase in cyberattacks specifically targeting…
With the proliferation of digitization and its usage in critical sectors, it is necessary to include information about the occurrence and assessment of cyber threats in an organization's threat mitigation strategy. This Cyber Threat…
This paper describes how NIST Special Publications (SP) 800-171r2 (Protecting Controlled but Unclassified Information in Nonfederal Systems and Organizations), SP.800-172 (Enhanced Security Requirements for Protecting Controlled…
The cybersecurity of modern systems has dramatically increased attention from both industrial and academia perspectives. In the recent era, the popularity of the blockchain-based system has traditionally been emergent among various…
Threat hunting is a proactive methodology for exploring, detecting and mitigating cyberattacks within complex environments. As opposed to conventional detection systems, threat hunting strategies assume adversaries have infiltrated the…
As artificial intelligence (AI) becomes deeply embedded in critical services and everyday products, it is increasingly exposed to security threats which traditional cyber defenses were not designed to handle. In this paper, we investigate…
Identification of cyber threats is one of the essential tasks for security teams. Currently, cyber threats can be identified using knowledge organized into various formats, enumerations, and knowledge bases. This paper studies the current…
As machine learning systems grow in scale, so do their training data requirements, forcing practitioners to automate and outsource the curation of training data in order to achieve state-of-the-art performance. The absence of trustworthy…