Academic Articles & Research Papers

Deep Learning and Autonomous Vehicles: Strategic Themes, Applications, and Research Agenda Using SciMAT and Content-Centric Analysis, a Systematic Review

Applications of deep learning (DL) in autonomous vehicle (AV) projects have gained increasing interest from both researchers and companies. This has caused a rapid expansion of scientific production on DL-AV in recent years, encouraging res...

Experiential Learning: Innovative Approaches to Post-Secondary Cybersecurity Education

The cybersecurity profession continues to face a significant shortfall of qualified professionals despite steady growth in degree programs. Employers consistently cite experience as the main barrier for entry-level cybersecurity hires. This...

DELP-Net: A Differentiable Entropy Layer Pyramid Network for End-to-End Low-Rate DoS Detection

Low-rate Denial-of-Service (LDoS) attacks exploit periodic traffic pulses to trigger congestion while maintaining a low average rate, making them highly stealthy and difficult to distinguish from legitimate bursty traffic using threshold-ba...

A Unified Transformer–BDI Architecture for Financial Fraud Detection: Distributed Knowledge Transfer Across Diverse Datasets

Financial fraud detection is a critical application area within the broader domains of cybersecurity and intelligent financial analytics. With the growing volume and complexity of digital transactions, the traditional rule-based and shallow...

European Ai-Policy Space

Artificial Intelligence (AI) is one of the central technologies of the fourth industrial revolution. A significant part of the production of surplus value in the XXI century is associated with the mastery and widespread introduction of tech...

The impact of corporate social responsibility on cybersecurity behavior: The crucial role of organizationally-prescribed perfectionism

Abstract This study delves into the ways in which corporate social responsibility (CSR) affects cybersecurity behavior among employees. It specifically examines the mediating effects of psychological safety and job stress, as well as the mo...

Do Risk Disclosure and Firm Value Drive Indonesian Bank Stock Returns?

Investors are increasingly concerned about risk transparency and cybersecurity disclosure as the banking sector becomes more digitalized. The purpose of this study is to look at how firm value, required risk disclosure, and cyber risk discl...

Adversarial XAI Methods in Cybersecurity

Machine Learning methods are playing a vital role in combating ever-evolving threats in the cybersecurity domain. Explanation methods that shed light on the decision process of black-box classifiers are one of the biggest drivers in the suc...

SecureBERT: A Domain-Specific Language Model for Cybersecurity

Recent Advances on Federated Learning for Cybersecurity and Cybersecurity for Federated Learning for Internet of Things

Decentralized paradigm in the field of cybersecurity and machine learning (ML) for the emerging Internet of Things (IoT) has gained a lot of attention from the government, academia, and industries in recent years. Federated cybersecurity (F...

A Survey on Explainable Artificial Intelligence for Cybersecurity

The “black-box” nature of artificial intelligence (AI) models has been the source of many concerns in their use for critical applications. Explainable Artificial Intelligence (XAI) is a rapidly growing research field that aims to create mac...

Automated monitoring innovations for efficient and safe construction practices

As construction projects increase in complexity, there are growing challenges with conventional monitoring methods in terms of efficiency, safety, and competitiveness. Traditional supervision techniques are labour-intensive, intermittent, a...

Decentralized intelligence in smart grids: a comprehensive survey of edge computing and federated learning

Modern power grids are becoming more distributed and data-intensive, while centralized, cloud-based analytics struggle to keep pace. Routing everything through a central system introduces delays, strains network capacity, complicates compli...

Robustness of Short-Term Wind Power Forecasting against False Data Injection Attacks

The accuracy of wind power forecasting depends a great deal on the data quality, which is so susceptible to cybersecurity attacks. In this paper, we study the cybersecurity issue of short-term wind power forecasting. We present one class of...

Nieuwe perspectieven in onrustige tijden

Het is niet nodig om in dit voorwoord te vermelden dat de wereld sterk in beweging is. Als MAB-lezer heeft u genoeg informatiebronnen tot uw beschikking, en uiteraard uw eigen observaties, die de enorme veranderlijkheid en soms schokkende a...

Deep hybrid neural net (DHN-Net) for minute-level day-ahead solar and wind power forecast in a decarbonized power system

The need to reduce global carbon emissions has led to a significant increase in clean energy globally. While renewable energy penetration into energy grids and power systems is increasing in many countries, the intermittency and stochastic ...

Hardware-Anchored ES-SPA: A Dynamic Zero-Trust Architecture for Secure eSIM Provisioning in 6G IoT via Moving Target Defense

The rapid evolution of 6G networks and large-scale Internet of Things (IoT) deployments intensifies security and privacy challenges in embedded SIM (eSIM) Remote SIM Provisioning (RSP), particularly during the bootstrap and profile delivery...

Enhanced Intrusion Detection in Drone Networks: A Cross-Layer Convolutional Attention Approach for Drone-to-Drone and Drone-to-Base Station Communications

Due to Internet of Drones (IoD) technology, drone networks have proliferated, transforming surveillance, logistics, and disaster management. Distributed Denial of Service (DDoS) attacks, malware infections, and communication abnormalities i...

Security evaluation framework for cloud ERP systems using NIST and ISO standards

Abstract Enterprise Resource Planning (ERP) systems serve as critical infrastructure for modern organizations, yet their security assessment lacks standardized evaluation frameworks. This study develops and applies a structured Security Mat...

A Cooperative Learning Approach for Decentralized Peer-to-Peer Energy Trading Markets and its Structural Robustness Against Cyberattacks

Peer-to-peer (P2P) energy trading has recently emerged as a promising paradigm for integrating renewable and distributed energy resources into local energy grids with the presence of active prosumers. However, prosumers often have different...