Face morphing poses a serious threat to Automatic Border Control (ABC) and Face Recognition Systems (FRS) in general. The aim of this paper is to present a qualitative assessment of the morphing attack issue, and the challenges it entails, highlighti...
Face morphing and related morphing attacks have emerged as a serious security threat for automatic face recognition systems and a challenging research field. Therefore, the availability of effective and reliable morphing attack detectors is strongly...
Deep neural networks have been widely used in detection tasks based on optical remote sensing images. However, in recent studies, deep neural networks have been shown to be vulnerable to adversarial examples. Adversarial examples are threatening in b...
Although face recognition systems have wide application, they are vulnerable to presentation attack samples (fake samples). Therefore, a presentation attack detection (PAD) method is required to enhance the security level of face recognition systems....
The persistent increase in forest pest outbreaks requires timely detection methods to monitor the disaster precisely. However, early detection is challenging due to insufficient temporal observation and subtle tree changes. This article proposed a no...
Face liveness detection is a critical preprocessing step in face recognition for avoiding face spoofing attacks, where an impostor can impersonate a valid user for authentication. While considerable research has been recently done in improving the ac...
Background and objectives: Cranial magnetic resonance imaging findings of patients considered to be cryptogenic stroke may be useful in determining the clinical and prognostic significance of arrhythmias, such as atrial premature beats and atrial run...
In open-network environments of smart buildings and urban infrastructure, abnormal traffic from security and energy monitoring systems is critical for operational safety and decision reliability. We can develop malware that exploits building automati...
Over recent years, there are an increasing number of incidents in which archival images have been ripped. Leak tracking is one of the key problems for anti-screenshot digital watermarking of archival images. Most of the existing algorithms suffer fro...
With the advancement in information technology, digital data stealing and duplication have become easier. Over a trillion bytes of data are generated and shared on social media through the internet in a single day, and the authenticity of digital dat...
In our research, we propose a novel asymmetric multiple-image encryption method using a conjugate Dammann grating (CDG), which is based on the coherent beam combining (CBC) principle. The phase generated by the Dammann grating (DG) beam splitting sys...
With the widespread deployment of deep neural networks in real-world physical environments, assessing their robustness against adversarial attacks has become a central issue in AI safety. However, the existing two-dimensional adversarial methods ofte...
This paper presents HE-DMDeception, a novel adversarial attack network that integrates human visual deception with deep model deception to enhance the security of 3D object detection. Existing patch-based and camouflage methods can mislead deep learn...
Automation of complex social behavior analysis of experimental animals would allow for faster, more accurate and reliable research results in many biological, pharmacological, and medical fields. However, there are behaviors that are not only difficu...
Despite the remarkable success of Deep Neural Networks (DNNs) in Remote Sensing Image (RSI) object detection, they remain vulnerable to adversarial attacks. Numerous adversarial attack methods have been proposed for RSI; however, adding a single larg...
27 November 2023
Deep Learning has enabled significant progress towards more accurate predictions and is increasingly integrated into our everyday lives in real-world applications; this is true especially for Convolutional Neural Networks (CNNs) in the field of image...
Automatic recognition systems (ARS) have been proposed in scientific and technological research for the care and preservation of endangered species; these systems, consisting of Internet of Things (IoT) devices and object-recognition techniques with...
Nowadays, faces in videos can be easily replaced with the development of deep learning, and these manipulated videos are realistic and cannot be distinguished by human eyes. Some people maliciously use the technology to attack others, especially cele...
Intrusion and malware detection tasks on a host level are a critical part of the overall information security infrastructure of a modern enterprise. While classical host-based intrusion detection systems (HIDS) and antivirus (AV) approaches are based...
This hypothesis proposal addresses three major questions: (1) Why do we need imaging biomarkers for assessing the efficacy of immune system participation in glioblastoma therapy response? (2) Why are they not available yet? and (3) How can we produce...
With the rapid growth of fingerprint-based biometric systems, it is essential to ensure the security and reliability of the deployed algorithms. Indeed, the security vulnerability of these systems has been widely recognized. Thus, it is critical to e...
Deep neural networks (DNNs) have been widely utilized in automatic visual navigation and recognition on modern unmanned aerial vehicles (UAVs), achieving state-of-the-art performances. However, DNN-based visual recognition systems on UAVs show seriou...
Citizen science reinforces the development of emergent tools for the surveillance, monitoring, and early detection of biological invasions, enhancing biosecurity resilience. The contribution of farmers and farm citizens is vital, as volunteers can st...
Deepfakes and adjacent synthetic-media capabilities have become a systemic challenge for information integrity, security, and digital trust. Countermeasures now span passive detection methods that infer manipulation from content traces, active proven...
Grapevines are subjected to many physiological and environmental stresses that influence their vegetative and reproductive growth. Water stress, cold damage, and pathogen attacks are highly relevant stresses in many grape-growing regions. Precision v...
This paper presents a novel material spectroscopy approach to facial presentation–attack–defense (PAD). Best-in-class PAD methods typically detect artifacts in the 3D space. This paper proposes similar features can be achieved in a monocu...
Scrap steel inspection is a critical entry point for connecting the smelting process to the industrial internet, with its security and privacy being of vital importance. Current advancements in scrap steel inspection involve collecting scattered data...
Phishing, especially brand impersonation attacks, is a critical cybersecurity threat that harms user trust and organization security. This paper establishes a lightweight model for real-time detection that relies on URL-only sequences, addressing lim...
COVID-19-like pandemics are a major threat to the global health system have the potential to cause high mortality across age groups. The advance of the Internet of Medical Things (IoMT) technologies paves the way toward developing reliable solutions...
In image splicing tamper detection, forgery operations simultaneously introduce macroscopic semantic inconsistencies and microscopic tampering artifacts. Conventional methods often treat semantic understanding and low-level artifact perception as sep...
The occurrence of extreme windstorms and increasing heat and drought events induced by climate change leads to severe damage and stress in coniferous forests, making trees more vulnerable to spruce bark beetle infestations. The combination of abiotic...
Dynamic heterogeneous redundancy (DHR) architectures combine heterogeneity, redundancy, and dynamism to create security-centric frameworks that can be used to mitigate network attacks that exploit unknown vulnerabilities. However, conventional DHR ar...
Bark beetle outbreaks are responsible for the loss of large areas of forests and in recent years they appear to be increasing in frequency and magnitude as a result of climate change. The aim of this study is to develop a new standardized methodology...
Although fingerprint-based systems are the commonly used biometric systems, they suffer from a critical vulnerability to a presentation attack (PA). Therefore, several approaches based on a fingerprint biometrics have been developed to increase the r...
Objectives: The need for routine brain magnetic resonance imaging (MRI) for patients presenting with unilateral facial palsy in the emergency department (ED) is a subject of ongoing debate. This study aimed to evaluate the diagnostic yield of MRI in...
Cardiovascular diseases have been reported to be the leading cause of mortality across the globe. Among such diseases, Myocardial Infarction (MI), also known as “heart attack”, is of main interest among researchers, as its early diagnosis...
Multi-UAV target localization relies on cooperative fusion of local, perception-derived geometric measurements over an edge network. While distributed fusion improves scalability and robustness compared with a centralized architecture, the iterative...
Background: Intracranial arterial calcification (IAC), commonly detected on CT/CTA during ischemic stroke work-up, may reflect atherosclerotic burden relevant to recurrence. We evaluated whether CTA-detected IAC was associated with subsequent ischemi...
Cementitious materials are susceptible to damage not only from mechanical loading, but also from environmental (physical, chemical, and biological) factors. For Textile-Reinforced Cementitious (TRC) composites, durability poses a significant challeng...
Background: Moyamoya syndrome is a moyamoya-like cerebrovascular condition associated with an identifiable underlying condition. Although head trauma has historically been considered a possible contributing factor, it is currently excluded from the J...