Related papers: Cyber Value At Risk Model for IoT Ecosystems

Academic and research cyberinfrastructures (AR-CIs) present unique security challenges due to their collaborative nature, heterogeneous components, and the lack of practical security assessment frameworks tailored to their needs. We propose…

Malware detection in IoT environments necessitates robust methodologies. This study introduces a CNN-LSTM hybrid model for IoT malware identification and evaluates its performance against established methods. Leveraging K-fold…

Internet of Things (IoT) is one of the emerging technologies of this century and its various aspects, such as the Infrastructure, Security, Architecture and Privacy, play an important role in shaping the future of the digitalised world.…

We introduce two quantum algorithms to compute the Value at Risk (VaR) and Conditional Value at Risk (CVaR) of financial derivatives using quantum computers: the first by applying existing ideas from quantum risk analysis to derivative…

IoT deployments have been growing manifold, encompassing sensors, networks, edge, fog and cloud resources. Despite the intense interest from researchers and practitioners, most do not have access to large-scale IoT testbeds for validation.…

The rapid expansion of the Internet of Things (IoT) in domains such as smart cities, transportation, and industrial systems has heightened the urgency of addressing their security vulnerabilities. IoT devices often operate under limited…

Cybersecurity concerns of Internet of Things (IoT) devices and infrastructure are growing each year. In response, organizations worldwide have published IoT security guidelines to protect their citizens and customers by providing…

IoT devices are present in many, especially corporate and sensitive, networks and regularly introduce security risks due to slow vendor responses to vulnerabilities and high difficulty of patching. In this paper, we want to evaluate to what…

This paper introduces a value-driven cybersecurity innovation framework for the transportation and infrastructure sectors, as opposed to the traditional market-centric approaches that have dominated the field. Recontextualizing innovation…

The Internet of things (IoT) is still in its infancy and has attracted much interest in many industrial sectors including medical fields, logistics tracking, smart cities and automobiles. However as a paradigm, it is susceptible to a range…

With the recent advances of IoT (Internet of Things) new and more robust security frameworks are needed to detect and mitigate new forms of cyber-attacks, which exploit complex and heterogeneity IoT networks, as well as, the existence of…

Smart healthcare industry is increasingly relying on Internet of Things (IoT) devices to improve patient care and operational efficiency. However, the cryptographic algorithms that enable fundamental security and are widely used in these…

Accurately defining, measuring and mitigating risk is a cornerstone of financial risk management, especially in the presence of financial contagion. Traditional correlation-based risk assessment methods often struggle under volatile market…

The Internet of Things (IoT) is a dynamic global information network consisting of Internet-connected objects, such as RFIDs, sensors, and actuators, as well as other instruments and smart appliances that are becoming an integral component…

A social approach can be exploited for the Internet of Things (IoT) to manage a large number of connected objects. These objects operate as autonomous agents to request and provide information and services to users. Establishing trustworthy…

Copula-based Conditional Value at Risk (CCVaR) is defined as an alternative version of the classical Conditional Value at Risk (CVaR) for multivariate random vectors intended to be real-valued. We aim to generalize CCVaR to several…

The escalating complexity of cybersecurity threats necessitates innovative approaches to safeguard digital assets and sensitive information. The Zero Trust paradigm offers a transformative solution by challenging conventional security…

This paper presents the detection of DDoS attacks in IoT networks using machine learning models. Their rapid growth has made them highly susceptible to various forms of cyberattacks, many of whose security procedures are implemented in an…

Machine learning finds rich applications in Internet of Things (IoT) networks such as information retrieval, traffic management, spectrum sensing, and signal authentication. While there is a surge of interest to understand the security…

IoT context-sharing platforms are an essential component of today's interconnected IoT deployments with their security affecting the entire deployment and the critical infrastructure adopting IoT. We report on a lack of systematic approach…