相关论文: HealthGuard: A Machine Learning-Based Security Fra…

Modern smart home control systems utilize real-time occupancy and activity monitoring to ensure control efficiency, occupants' comfort, and optimal energy consumption. Moreover, adopting machine learning-based anomaly detection models…

In smart grid, malicious customers may compromise their smart meters (SMs) to report false readings to achieve financial gains illegally. Reporting false readings not only causes hefty financial losses to the utility but may also degrade…

As digital threats continue to grow, organizations must find ways to enhance security while protecting user privacy. This paper explores how artificial intelligence (AI) plays a crucial role in achieving this balance. AI technologies can…

Structural Health Monitoring (SHM) plays a crucial role in maintaining aging and critical infrastructure, supporting applications such as smart cities and digital twinning. These applications demand machine learning models capable of…

Smart grid systems are critical to the power industry, however their sophisticated architectural design and operations expose them to a number of cybersecurity threats, such as data tampering, data eavesdropping, and Denial of Service,…

The Internet has become a prime subject to security attacks and intrusions by attackers. These attacks can lead to system malfunction, network breakdown, data corruption or theft. A network intrusion detection system (IDS) is a tool used…

This article analyzes the mobile medical diagnostic systems and compare them with the proposed HealthTracker system based on smartwatch Apple Watch. Before the development of the system HealthTracker, there was conducted a review and…

An ideal safe workplace is described as a place where staffs fulfill responsibilities in a well-organized order, potential hazardous events are being monitored in real-time, as well as the number of accidents and relevant damages are…

Repetitive laboratory testing unlikely to yield clinically useful information is a common practice that burdens patients and increases healthcare costs. Education and feedback interventions have limited success, while general test ordering…

The threat of attack faced by cyber-physical systems (CPSs), especially when they play a critical role in automating public infrastructure, has motivated research into a wide variety of attack defence mechanisms. Assessing their…

The impact of new technologies in the field of healthcare has been proven to be satisfactory in improving the quality of care and services for patients. The hospital environment is undoubtedly one of the environments where human or hardware…

The increasing integration of the Internet of Medical Things (IoMT) into healthcare systems has significantly enhanced patient care but has also introduced critical cybersecurity challenges. This paper presents a novel approach based on…

Internet of Things is rapidly spreading across several fields, including healthcare, posing relevant questions related to communication capabilities, energy efficiency and sensors unobtrusiveness. Particularly, in the context of recognition…

In an era of escalating cyber threats, malware poses significant risks to individuals and organizations, potentially leading to data breaches, system failures, and substantial financial losses. This study addresses the urgent need for…

The growing popularity of Internet-of-Things (IoT) has created the need for network-based traffic anomaly detection systems that could identify misbehaving devices. In this work, we propose a lightweight technique, IoT-guard, for…

Internet of Things (IoT) devices are capable of allowing for far-reaching access to and evaluation of patient data to monitor health and diagnose from a distance. An electronic healthcare system that checks patient data, prepares medicines…

With the proliferation of wireless networks, mobile devices and medical devices are increasingly being equipped with wireless interfaces, such as Bluetooth and WiFi to allow easy access to and control of the medical devices. Unfortunately,…

Recently, web-based Large Language Model (LLM) agents autonomously perform increasingly complex tasks, thereby bringing significant convenience. However, they also amplify the risks of malicious misuse cases such as unauthorized collection…

Machine learning methods provide a methodological innovation that can help screen for cardiovascular disease through noninvasive and readily available measurement modalities. Recent investments in using electrocardiogram (ECG) data to…

To cope with the increasing variability and sophistication of modern attacks, machine learning has been widely adopted as a statistically-sound tool for malware detection. However, its security against well-crafted attacks has not only been…