Frequent engineering changes in manufacturing require worker instructions to be updated quickly and reliably. In many production environments, however, update handling still depends on manual comparison procedures, delayed communication, or repeated...
Detection of unknown malware and its variants remains both an operational and a research challenge in the Internet of Things (IoT). The Internet of Medical Things (IoMT) is a particular type of IoT network which deals with communication through smart...
Ensuring information integrity requires not only reducing decoding errors but also reducing the probability that corrupted data are accepted as valid. This research presents a hybrid integrity protection system that incorporates seeded universal hash...
As one of the important techniques for protecting the copyrights of digital images, content-based image copy detection has attracted a lot of attention in the past few decades. The traditional content-based copy detection methods usually extract loca...
Ship detection plays a crucial role in marine security in remote sensing imagery. This paper discusses about a deep learning approach to detect the ships from satellite imagery. The model developed in this work achieves integrity by the inclusion of...
Unsupervised machine learning and knowledge discovery from large-scale datasets have recently attracted a lot of research interest. The present paper proposes a distributed big data clustering approach-based on adaptive density estimation. The propos...
This paper presents a comparative study on the impact of robust hashing in enhancing image-based malware classification. While Convolutional Neural Networks (CNNs) have shown promise when working with image-based malware samples, their performance de...
Every day, hundreds of thousands of new malicious files are created. Existing pattern-based antivirus solutions have difficulty detecting these new malicious files. Artificial intelligence (AI)–based malware detection has been proposed to solve...
As the Internet of Vehicles (IoV) rapidly gains popularity, the Controller Area Network (CAN) faces increasingly severe security threats. Most of the existing research on protecting the CAN bus has been based on artificial intelligence models, which...
Edge computing offers low-latency and distributed processing for IoT applications but poses new security challenges, due to limited resources and decentralized data. Intrusion detection systems (IDSs) are essential for real-time threat monitoring, ye...
Ubiquitous nature of Internet services across the globe has undoubtedly expanded the strategies and operational mode being used by cybercriminals to perpetrate their unlawful activities through intrusion on various networks. Network intrusion has led...
Research has shown that counting WiFi packets called probe requests (PRs) implicitly provides a proxy for the number of people in an area. In this paper, we discuss a crowd counting system involving WiFi sensors detecting PRs over the air, then extra...
Whole-genome alignment (WGA) is a critical process in comparative genomics, facilitating the detection of genetic variants and aiding our understanding of evolution. This paper offers a detailed overview and categorization of WGA techniques, encompas...
Forensic watermarking is often used to enable the tracing of digital pirates that leak copyright-protected videos. However, existing watermarking methods have a limited robustness and may be vulnerable to targeted attacks. Our previous work proposed...
Digital image source identification primarily focuses on analyzing and detecting the machine imprints or camera fingerprints left by imaging devices during the imaging process to trace the origin of digital images. The development of a swift search a...
With the prevalence of telemedicine and digital diagnosis, the security and integrity of medical images transmitted over open networks have become critical issues. To effectively defend against malicious tampering and ensure the reliability of diagno...
As multimedia technology has advanced in recent years, the use of enormous image libraries has dramatically expanded. In applications for image processing, image retrieval has emerged as a crucial technique. Content-based face image retrieval is a we...
Wireless sensor networks (WSNs) are vulnerable to physical attacks in which adversaries gain partial or full control of sensor nodes, compromising the integrity of the network. Conventional security mechanisms impose excessive computational overhead...
Reversible data hiding (RDH) is a key technique in secure multimedia applications, enabling the exact recovery of both embedded data and the original cover content. To further enhance security and embedding capacity, this paper proposes a dual-image...
The rapid growth of sensitive labeled data in healthcare, finance, user profiling, and commercial databases has created increasing demand for privacy-preserving collaborative data validation across different organizations. Following prior cryptograph...
Large Language Model (LLM)-based agents automate complex tasks by integrating external tools such as web browsers, e-mail clients, file readers, and APIs, but this same integration exposes them to indirect prompt injection (IPI) attacks, in which mal...
Crypto-ransomware is a type of ransomware that encrypts the victim’s files and demands a ransom to return the files. This type of attack has been on the rise in recent years, as it offers a lucrative business model for threat actors. Research into de...
Covert channels enable stealthy communications over innocent appearing carriers. They are increasingly applied in the network context. However, little work is available that exploits cryptographic primitives in the networking context to establish suc...
Cryptography has become one of the vital disciplines for information technology such as IoT (Internet Of Things), IIoT (Industrial Internet Of Things), I4.0 (Industry 4.0), and automotive applications. Some fundamental characteristics required for th...
Hash functions are fundamental components in both cryptographic and non-cryptographic systems, supporting secure authentication, data integrity, fingerprinting, and indexing. While the Ascon family, selected by the National Institute of Standards and...
The Wireless Medium Access Control (WMAC) protocol functions by handling various data frames in order to forward them to neighbor sensor nodes. Under this circumstance, WMAC policies need secure data communication rules and intrusion detection proced...
Aiming at the deficiency that blockchain technology is too sensitive to the binary-level changes of high resolution remote sensing (HRRS) images, we propose a new subject-sensitive hashing algorithm specially for HRRS image blockchains. To implement...
Attacks on embedded devices are becoming more and more prevalent, primarily due to the extensively increasing plethora of software vulnerabilities. One of the most dangerous types of these attacks targets application code at run-time. Techniques to d...
In the current landscape where quantum algorithms pose a significant threat to conventional digital signature algorithms, code-based digital signature algorithms have emerged as the primary focus of ongoing research in post-quantum cryptography. Digi...
High resolution remote sensing (HRRS) images are widely used in many sensitive fields, and their security should be protected thoroughly. Integrity authentication is one of their major security problems, while the traditional techniques cannot fully...
Ascon is a family of lightweight cryptographic algorithms designed for Authenticated Encryption with Associated Data (AEAD), hashing, and Extendable Output Functions (XOFs) in resource-constrained environments. While the AEAD variants of Ascon provid...
Pattern matching is a key technique in the physical verification of integrated circuit designs and is widely used in lithographic hotspot detection. Existing pattern-matching algorithms face challenges in effectiveness and robustness, especially when...
Reconfigurable processor-based acceleration of deep convolutional neural network (DCNN) algorithms has emerged as a widely adopted technique, with particular attention on sparse neural network acceleration as an active research area. However, many co...
Data security technology is of great significance for the effective use of high-resolution remote sensing (HRRS) images in GIS field. Integrity authentication technology is an important technology to ensure the security of HRRS images. Traditional au...
Every second, millions of data are being generated due to the use of emerging technologies. It is very challenging to store and handle such a large amount of data. Data deduplication is a solution for this problem. It is a new technique that eliminat...
Blockchain introduces challenges related to the reliability of user identity and identity management systems; this includes detecting unfalsified identities linked to IoT applications. This study focuses on optimizing user identity verification time...
High-resolution three-dimensional data from sensors such as LiDAR are sufficient to find power line towers and poles but do not reliably map relatively thin power lines. In addition, repeated detections of the same object can lead to confusion while...
Cloud-integrated sensor and Internet of Things (IoT) systems enable scalable data storage, processing, and intelligent monitoring, but their distributed nature exposes network-flow and host-level data to unauthorized access, tampering, and cyberattac...
Automotive cyber-physical systems are in transition from the closed-systems to open-networking systems. As a result, in-vehicle networks such as the controller area network (CAN) have become essential to connect to inter-vehicle networks through the...
Blockchain technology has rapidly evolved beyond cryptocurrencies, underpinning diverse applications such as supply chains, healthcare, and finances, yet its security vulnerabilities remain a critical barrier to safe adoption. However, attackers incr...
The fast-paced progress in quantum computing introduces significant new challenges for digital forensics by undermining classical cryptographic mechanisms that protect digital evidence. Algorithms such as Shor’s and Grover’s threaten the...
Non-intrusive load monitoring (NILM) is a fast developing technique for appliances operation recognition in power system monitoring. At present, most NILM algorithms rely on the assumption that all fluctuations in the data stream are triggered by ide...
Detecting persistent items that recur across multiple time windows is essential for identifying anomalies in high-speed data streams. However, performing such detection under tight memory constraints and high-speed data streams remains a challenge. E...
Malicious domains are part of the landscape of the internet but are becoming more prevalent and more dangerous both to companies and to individuals. They can be hosted on various technologies and serve an array of content, including malware, command...
The security of web applications in an enterprise is of paramount importance. To strengthen the security of applications, the identification and mitigation of vulnerabilities through appropriate countermeasures becomes imperative. The Open Web Applic...
Amid the rapid proliferation of thousands of new websites daily, distinguishing safe ones from potentially harmful ones has become an increasingly complex task. These websites often collect user data, and, without adequate cybersecurity measures such...
Knowledge base (KB) is an important aspect in artificial intelligence. One significant challenge faced by KB construction is that it contains many noises, which prevent its effective usage. Even though some KB cleansing algorithms have been proposed,...
Near-duplicate diagram detection in electronic documents is challenging because diagram identity depends on graphical structure, spatial composition, and textual labels, while reused images may undergo compression, cropping, rotation, photometric cha...
This paper presents HV-LIOM (Adaptive Hash-Voxel LiDAR–Inertial Odometry and Mapping), a unified LiDAR–inertial SLAM and autonomous exploration framework for real-time 3D mapping in dynamic, GNSS-denied environments. We propose an adaptiv...
This study explored how the Lombard effect, a natural or artificial increase in speech loudness in noisy environments, can improve speech-in-noise communication. This study consisted of several experiments that measured the impact of different types...
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