Tracking people’s behaviors is a main category of cyber physical social sensing (CPSS)-related people-centric applications. Most tracking methods utilize camera networks or sensors built into mobile devices such as global positioning system (GPS) and...
Anemia diagnosis is crucial for pediatric patients due to its impact on growth and development. Traditional methods, like blood tests, are effective but pose challenges, such as discomfort, infection risk, and frequent monitoring difficulties, unders...
29 March 2020
Most studies of stalking and other forms of intrusive behavior are conducted in the West. Little is known about the phenomenon in the African context. The present work represents the first dedicated stalking study conducted in Ghana. Based on a sampl...
An intrusion behavior recognition method based on deep learning is proposed in this paper in order to improve the recognition accuracy of raster perimeter intrusion behavior. The Mach–Zehnder fiber optic interferometer was used to collect the e...
30 May 2022
Many studies of stalking and intrusive behaviors are conducted with samples from individualist Western cultures, and limited information is available on such behavior in collectivist cultures. By using a sample of 1143 adults (440 males and 703 femal...
The high number of annual safety accidents and casualties reflects the problems of slow detection of safety accidents and untimely early warnings in current construction safety management, and China urgently needs new methods and technologies to impr...
This paper proposes a structured design framework and system architecture for a non-intrusive spatial system aimed at supporting child behavior in everyday domestic environments. Rooted in ethical considerations, our approach defines four core behavi...
Zero-day cyberattacks remain difficult to detect because their behavioral characteristics are not represented in the data available during model training. In addition, intrusion detection models operating in dynamic environments are vulnerable to con...
Electric vehicle (EV) chargers are often deployed in public spaces, making them easily accessible targets for cyber attackers. Moreover, EV chargers are components of EV charging infrastructure in which IT and OT domains coexist; thus, if they are co...
Unmanned aerial vehicles (UAVs), commonly known as drones, have found extensive applications across diverse sectors, such as agriculture, delivery, surveillance, and military. In recent times, drone swarming has emerged as a novel field of research,...
The growing integration of Internet of Things (IoT) devices into various sectors like healthcare, transportation, and agriculture has dramatically increased their presence in everyday life. However, this rapid expansion has exposed new vulnerabilitie...
Digital infrastructures are increasingly exposed to diverse and evolving cyber threats, highlighting the need for robust intrusion detection systems (IDSs). Although machine learning (ML)-based IDSs have achieved strong performance, most existing fra...
15 July 2025
Background. Cognitive-behavioral theories suggest that obsessions in obsessive-compulsive disorder (OCD) develop from maladaptive misinterpretations and coping strategies of unwanted intrusive thoughts (UITs). Models of Body Dysmorphic Disorder (BDD)...
This study investigates residential electricity consumption behaviors in the Moldova region of Romania, with a focus on identifying consumption patterns through a non-invasive, survey-based approach. Unlike intrusive monitoring or smart metering meth...
Malicious activity detection in honeypot environments remains challenging due to the volume and heterogeneity of captured data, as well as the sequential nature of attacker behavior. This study proposes an integrated framework combining a Cowrie-base...
Mobile cloud computing (MCC) is a technological paradigm for providing services to mobile device (MD) users. A compromised MD may cause harm to both its user and to other MCC customers. This study explores the use of machine learning (ML) models and...
Food noise refers to persistent and intrusive thoughts about food that may interfere with daily functioning, emotional well-being, and eating behaviors. Although the construct has gained increasing attention in clinical and research contexts, no psyc...
Internet of Things (IoT) malware and intrusions generate network-observable flow patterns, but high benchmark accuracy does not by itself establish transfer to new environments. This study presents Protocol-conditioned Analysis with Behavioral Threat...
Phishing websites continue to evolve in sophistication, making them increasingly difficult to distinguish from legitimate platforms and challenging the effectiveness of current detection systems. In this study, we investigate the role of subtle decep...
This study investigates how Moroccan users experience and interpret digital content that seems tailored to their personal profiles. While many participants recognize the relevance of such content, their willingness to engage depends less on accuracy...
Integrating Wire Arc Additive Manufacturing (WAAM) into the Selective Paste Intrusion (SPI) process represents a groundbreaking approach for fabricating reinforced concrete structures with complex geometries. This study investigates the bond strength...
The number of security breaches in the cyberspace is on the rise. This threat is met with intensive work in the intrusion detection research community. To keep the defensive mechanisms up to date and relevant, realistic network traffic datasets are n...
Changes in the physiological and behavioral states of fish are affected by foreign substances. Therefore, fish need a certain adaptation period to eliminate the stress response. Herein, in order to determine the adaptation period, the bionic robot fi...
Cyber security has recently received enormous attention in today’s security concerns, due to the popularity of the Internet-of-Things (IoT), the tremendous growth of computer networks, and the huge number of relevant applications. Thus, detecti...
Cloud multi-factor authentication is a critical security measure that helps strengthen cloud security from unauthorized access and data breaches. Multi-factor authentication verifies that authentic cloud users are only authorized to access cloud apps...
Early detection of network traffic anomalies is critical for cybersecurity, as a single compromised host can cause data breaches, reputational damage, and operational disruptions. However, traditional systems based on signatures and static rules are...
Recently, various strategies for energy management have been proposed to improve energy efficiency in smart grids. One key aspect of this is the use of microgrids. To effectively manage energy in a residential microgrid, advanced computational tools...
Rapid growth in IoT devices has led to the creation of crucial cybersecurity threats since existing methods of malware detection which use signature matching and numerical feature analysis are incapable of capturing the contextual behavioral semantic...
Network intrusion behaviors exhibit high concealment and diversity, making intrusion detection methods based on single-behavior modeling unable to accurately characterize such activities. To overcome this limitation, we propose SGMT-IDS, a dual-branc...
Due to the insidious characteristics of network intrusion behaviors, developing an efficient intrusion detection system is still a big challenge, especially in the era of big data where the number of traffic and the dimension of each traffic feature...
High-pressure intrusion of water and LiCl aqueous solutions at different concentrations in hydrophobic STT-type zeosil was studied for possible applications in absorption and storage of mechanical energy. The water is intruded at a pressure of 35 MPa...
As attack techniques become more sophisticated, detecting new and advanced cyberattacks with traditional intrusion detection techniques based on signature and anomaly is becoming challenging. In signature-based detection, not only do attackers bypass...
Web3.0, as the link between the physical and digital domains, faces increasing security threats due to its inherent complexity and openness. Traditional intrusion detection systems (IDSs) encounter formidable challenges in grappling with the multidim...
The Internet of Vehicles (IoV) is a network system that enables wireless communication and information exchange between vehicles and other traffic participants. Intrusion detection plays a very important role in the IoV. However, with the development...
The amount of road accidents caused by driver drowsiness is one of the world’s major challenges. These accidents lead to numerous fatal and non-fatal injuries which impose substantial financial strain on individuals and governments every year....
The threat of cyber-attacks is ever increasing in today’s society. There is a clear need for better and more effective defensive tools. Intrusion detection can be defined as the detection of anomalous behavior either in the host or in the netwo...
In this work, an intrusion detection system (IDS) framework based on multi-level clustering for hierarchical wireless sensor networks is proposed. The framework employs two types of intrusion detection approaches: (1) “downward-IDS (D-IDS)” to detect...
30 June 2017
Suicide and suicidal behavior are major public health concerns, and affect 3–9% of the population worldwide. Despite increased efforts for national suicide prevention strategies, there are still few effective interventions available for reducing suic...
Intrusion detection systems have proliferated with varying capabilities for data generation and learning towards detecting abnormal behavior. The goal of green intrusion detection systems is to design intrusion detection systems for energy efficiency...
In spite of excellent performance of deep learning-based computer vision algorithms, they are not suitable for real-time surveillance to detect abnormal behavior because of very high computational complexity. In this paper, we propose a real-time sur...
An overview of all the studies on high-pressure intrusion—extrusion of LiCl aqueous solutions in hydrophobic pure silica zeolites (zeosils) for absorption and storage of mechanical energy is presented. Operational principles of heterogeneous ly...
In computer networks, Network Intrusion Detection System (NIDS) plays a very important role in identifying intrusion behaviors. NIDS can identify abnormal behaviors by analyzing network traffic. However, the performance of classifier is not very good...
Biobehavioral synchrony, the coordination of physiological and behavioral signals between mother and infant during social contact, tunes the child’s brain to the social world. Probing this mechanism from a two-brain perspective, we examine the...
Anomaly-based intrusion detection systems use profiles to characterize expected behavior of network users. Most of these systems characterize the entire network traffic within a single profile. This work proposes a user-level anomaly-based intrusion...
Improving the risk models to include the possible infection risk linked to pathogen intrusion into distribution systems during pressure-deficient conditions (PDCs) is essential. The objective of the present study was to assess the public health impac...
The challenging issues of computer networks and databases are not only the intrusion detection but also the reduction of false positives and increase of detection rate. In any intrusion detection system, anomaly detection mainly focuses on modeling t...
Social network sites (SNSs) have brought about profound changes in the way people relate to others, including their romantic partners. Despite the advantages SNSs may have for building and managing romantic relationships, their use can be linked to r...
Most of the existing research works on the intrusion detection problem in a wireless sensor network (WSN) assume linear or random mobility patterns in abstracting intruders’ models in traversing the WSN field. However, in real-life WSN applications,...
The traditional inference of thermal comfort relies mainly on either questionnaire surveys or invasive physiological signal monitoring. However, the use of these methods in real time is limited and they have a low accuracy; furthermore, they can caus...
In the current electric vehicles, the purpose of the traction battery is to store energy. When designing this battery, different parameters are considered to arrange the battery/module/cells in the mechanically and thermally safest configuration. Mor...
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