Cloud-native architecture is becoming increasingly popular in today’s digital environment, driving the demand for robust security precautions to protect infrastructure and applications. This paper examines a variety of privacy-enhancing and tru...
Long-Term Evolution (LTE) is a fourth-generation mobile communication technology implemented throughout the world. It is the communication means of smartphones that send and receive all of the private date of individuals. M2M, IOT, etc., are the base...
The Internet of Things (IoT) is a technology that can connect billions of devices or “things” to other devices (machine to machine) or even to people via an existing infrastructure. IoT applications in real-world scenarios include smart c...
Advancements in wearable medical devices using the IoT technology are shaping the modern healthcare system. With the emergence of the Internet of Healthcare Things (IoHT), efficient healthcare services can be provided to patients. Healthcare professi...
Generative AI, including large language models (LLMs), has transformed the paradigm of data generation and creative content, but this progress raises critical privacy concerns, especially when models are trained on sensitive data. This review provide...
Focusing on the diversified demands of location privacy in mobile social networks (MSNs), we propose a privacy-enhancing k-nearest neighbors search scheme over MSNs. First, we construct a dual-server architecture that incorporates location privacy an...
Interrupting, altering, or stealing autism-related sensitive data by cyber attackers is a lucrative business which is increasing in prevalence on a daily basis. Enhancing the security and privacy of autism data while adhering to the symmetric encrypt...
This article speculates on the future of privacy and electronic identities on the Internet. Based on a short review of security models and the development of privacy-enhancing technology, privacy and electronic identities will be discussed as parts...
The growing digitization of healthcare has amplified concerns about the privacy and security of medical images, as conventional encryption methods often fail to provide sufficient protection. To address this gap, we propose a privacy-enhancing image...
Privacy enhancement technologies are significant in the development of digital payment systems. At present, multiple innovative digital payment solutions have been introduced and may be implemented globally soon. As cyber threats continue to increase...
The paper introduces a novel consensus algorithm named MRPBFT, which is derived from the HotStuff consensus protocol and improved upon to address security deficiencies in traditional consensus algorithms within the domain of digital asset transaction...
With the digitization of healthcare, an immense amount of sensitive medical data are generated and shared between various healthcare stakeholders—however, traditional health data management mechanisms present interoperability, security, and pri...
Nowadays, blockchain is developing as a secure and trustworthy platform for secure information sharing in areas of application like banking, supply chain management, food industry, energy, the Internet, and medical services. Besides, the blockchain c...
Privacy and security require not only strong algorithms but also reliable and readily available sources of randomness. To tackle this problem, one of the causes of single-event upsets is the utilization of a non-deterministic entropy source, specific...
Brain tumor segmentation in medical imaging is a critical task for diagnosis and treatment while preserving patient data privacy and security. Traditional centralized approaches often encounter obstacles in data sharing due to privacy regulations and...
The rapid advancements in artificial intelligence (AI) have significantly transformed various domains, including education, by introducing innovative tools that reshape teaching and learning processes. This research investigates the perceptions and a...
Resource-constrained Internet of Things (IoT) devices are increasingly deployed in critical domains but remain vulnerable to stealthy attacks that can bypass conventional defenses. At the same time, privacy constraints limit centralized data collecti...
Managing and analyzing data in data lakes for big data environments requires robust protocols to ensure security, scalability, and compliance with privacy regulations. The increasing need to process sensitive data emphasizes the relevance of secure-b...
Over-the-air (OTA) updating is a critical mechanism for secure internet of things (IoT) systems for remotely updating the firmware (or keys) of IoT devices. Message queue telemetry transport (MQTT) is a very popular internet of things (IoT) communica...
The Industrial Internet of Things (IIoT) has revolutionized smart manufacturing by enhancing automation, operational efficiency, and data-driven decision making. However, the interconnected nature of IIoT devices raises significant concerns about sec...
Exploiting Radio Frequency Identification (RFID) technology in healthcare systems has become a common practice, as it ensures better patient care and safety. However, these systems are prone to security vulnerabilities that can jeopardize patient pri...
Multi-access edge computing (MEC) is an emerging technology of 5G that brings cloud computing benefits closer to the user. The current specifications of MEC describe the connectivity of mobile users and the MEC host, but they have issues with applica...
This study investigated the potential of blockchain technology to transform Electronic Health Record (EHR) administration, integrity, and security. EHRs store vital health information such as medical history, diagnosis, prescriptions, and imaging fin...
Blockchain technology has been widely advocated for security and privacy in IoT systems. However, a major impediment to its successful implementation is the lack of privacy protection regarding user access policy while accessing personal data in the...
An Identity Management System (IDMS) is responsible for managing and organizing identities and credentials exchanged between users, Identity Providers (IDPs), and Service Providers (SPs). The primary goal of IDMS is to ensure the confidentiality and...
Dynamic consent management allows a data subject to dynamically govern her consent to access her data. Clearly, security and privacy guarantees are vital for the adoption of dynamic consent management systems. In particular, specific data protection...
To address the complexities, inflexibility, and security concerns in traditional data sharing models of the Industrial Internet of Things (IIoT), we propose a blockchain-based data sharing and privacy protection (BBDSPP) scheme for IIoT. Initially, w...
Improvements in technology have led to further enhancements in cyber security threats. Additionally, the mass application of IoT technology and networks has made the ecosystem vulnerable to cyber-attacks. Thus, this study focuses on analysing methods...
This paper addresses the critical challenge of secure computing in the context of deep learning, focusing on the pressing need for effective data privacy protection during transmission and storage, particularly in sensitive fields such as finance and...
Automated negotiation in multi-agent electronic commerce environments relies heavily on efficient and reliable matching mechanisms to connect negotiation participants. However, existing matching protocols often fail to ensure transaction security and...
The Internet of things (IoT) presents unique challenges for the deployment of machine learning (ML) models, particularly due to constraints on computational resources, the necessity for decentralized processing, and concerns regarding security and pr...
Bluetooth low energy devices are very popular in wireless personal area networks. According to the Bluetooth standard specifications, the low energy secure simple pairing (LESSP) protocol is the process by which the pairing devices negotiate the auth...
Federated learning has emerged as a promising technique for the Internet of Things (IoT) in various domains, including supply chain management. It enables IoT devices to collaboratively learn without exposing their raw data, ensuring data privacy. Ho...
This paper explicitly focuses on utilizing blockchain technology in dynamic consent management systems with privacy considerations. While blockchain offers improved security, the potential impact on entities’ privacy must be considered. Through...
A national population census is instrumental in offering a holistic view of a country’s progress, directly influencing policy formulation and strategic planning. Potential flaws in the census system can have detrimental impacts on national deve...
The rapid expansion of IoT in smart cities has improved traffic management but increased security risks. Traditional IDS struggle with advanced threats, prompting adaptive solutions. This work proposes a framework combining machine learning (ML), Zer...
Singular value decomposition (SVD) is a fundamental technique widely used in various applications, such as recommendation systems and principal component analyses. In recent years, the need for privacy-preserving computations has been increasing cons...
The growing influence of technology in the healthcare industry has led to the creation of innovative applications that improve convenience, accessibility, and diagnostic accuracy. However, health applications face significant challenges concerning us...
The rapid digitization of library resources has intensified the need for robust digital-rights management (DRM) mechanisms to safeguard copyright, control access, and preserve user privacy. Conventional DRM approaches are often centralized, prone to...
Privacy-preserving secure multi-party computation protocols are known to face scalability and efficiency challenges in environments where participants hold distinct attributes of the same records (vertical partitioning) or controls a subset of comple...
Vehicle Ad Hoc Networks (VANETs) face critical challenges in trust management, privacy preservation, and scalability, particularly with the integration of 5G networks in Intelligent Transportation Systems (ITS). Traditional centralized trust models p...
Trajectory data contain numerous sensitive attributes. Unauthorized disclosure of precise user trajectory information generates persistent privacy and security concerns that significantly impact daily life. Most existing trajectory privacy protection...
Chatbots have become increasingly popular in recent years, but they also present security risks and vulnerabilities that need to be addressed. This systematic literature review examines the existing research relating to information security in chatbo...
Federated learning (FL) has emerged as an efficient machine learning (ML) method with crucial privacy protection features. It is adapted for training models in Internet of Things (IoT)-related domains, including smart healthcare systems (SHSs), where...
In an era of increasing reliance on digital health solutions, safeguarding user privacy has emerged as a paramount concern. Health applications often need to balance advanced AI functionalities with sufficient privacy measures to ensure user engageme...
The proliferation of cloud computing has amplified the need for robust privacy-preserving technologies, particularly when dealing with sensitive financial and human resources (HR) data. However, traditional differential privacy methods often struggle...
Adaptor signature is a variant of digital signatures and useful for fair excheng in financial applications such as cryptocurrencies, to name a few, off-chain transaction protocols, atomic swaps and other privacy-enhancing mechanisms. However, similar...
The rapid advancements in technology have given rise to groundbreaking solutions and practical applications in the field of the Industrial Internet of Things (IIoT). These advancements have had a profound impact on the structures of numerous industri...
Permissionless blockchains have evolved beyond cryptocurrency into foundations for Web3 applications, decentralized finance (DeFi), and digital asset ownership, yet this rapid expansion has intensified privacy vulnerabilities. This study provides a c...
Although federated learning is gaining prevalence in smart sensor networks, substantial risks to data privacy and security persist. An improper application of federated learning techniques can lead to critical privacy breaches. Practical and effectiv...
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