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Internet-of-Things (IoT) and sensor technologies have enabled the collection of data in a distributed fashion for analysis and evidence-based decision making. However, security concerns regarding the source, confidentiality and integrity of the data arise. The most common method of protecting data transmission in sensor systems is Transport Layer Security (TLS) or its datagram counterpart (DTLS) today, but exist an alternative option based on Distributed Ledger Technology (DLT) that promise strong security, ease of use and potential for large scale integration of heterogeneous sensor systems. A DLT such as the IOTA Tangle offers great potential to improve sensor data exchange. This paper presents L2Sec, a cryptographic protocol which is able to secure data exchanged over the IOTA Tangle. This protocol is suitable for implementation on constrained devices, such as common IoT devices, leading to greater scalability. The first experimental results evidence the effectiveness of the approach and advocate for the integration of an hardware secure element to improve the overall security of the protocol. The L2Sec source code is released as open source repository on GitHub.

This paper presents a statistical analysis of the enhanced SDEx (Secure Data Exchange) encryption method, using a version that incorporates two session keys. This method has not previously been combined with the BLAKE3 hash function. The statistical analysis was conducted using the NIST Statistical Test Suite. Several real-world sample files were encrypted using the proposed method and then subjected to statistical analysis through selected tests from the NIST suite. These tests aimed to determine whether the resulting ciphertexts meet the criteria for pseudorandomness. Additionally, compression tests were performed using WinRAR, which confirmed that the ciphertexts are not compressible.

The Internet of Things (IoT) is a very abundant source of data, as well as a source of many vulnerabilities. A significant challenge is preparing security solutions to protect IoT nodes’ resources and the data exchanged. The difficulty usually stems from the insufficient resources of these nodes in terms of computing power, memory size, range energy resource, and wireless link performance. The paper presents the design and demonstrator of a system for symmetric cryptographic Key Generating, Renewing, and Distributing (KGRD). The system uses the TPM 2.0 hardware module to support cryptographic procedures, including creating trust structures, key generation, and securing the node’s exchange of data and resources. Clusters of sensor nodes and traditional systems can use the KGRD system to secure data exchange in the federated cooperation of systems with IoT-derived data sources. The transmission medium for exchanging data between KGRD system nodes is the Message Queuing Telemetry Transport (MQTT) service, which is commonly used in IoT networks.

The rapid adoption of the Internet of Things (IoT) in healthcare has revolutionized patient monitoring and real-time medical decision-making but also introduced significant security and privacy challenges. To address these issues, this paper proposes SecHealth, a lightweight trusted framework for secure data exchange and proactive threat mitigation in IoT-enabled healthcare systems. The framework integrates three core components: a multi-layered trust management mechanism, an advanced lightweight ECC-based encryption protocol (LECCEP-A), and a robust hybrid anomaly detection system (RHADS). Trust is computed using behavioral, communication, and contextual parameters, dynamically updated using feedback-based learning and anomaly filtering. LECCEP-A provides low-latency, secure data transfer from external attacks and entropy-augmented encryption based on elliptic curve cryptography. RHADS combines machine learning techniques (LSTM, VAE, SVM) and probabilistic reasoning to detect sophisticated attacks. The proposed system was evaluated in a MATLAB-based simulated healthcare IoT network consisting of 100–500 heterogeneous devices under mixed attack scenarios. The performance of suggested framework was measured using critical metrics such as latency, energy efficiency, throughput, detection accuracy, and false positive rate (FPR). It achieved anomaly detection accuracy of 98.1%, FPR of only 2.1%, latency of 85–95 ms, energy efficiency of 0.68–0.78 J/node, and throughput of 155–180 Kbps, outperforming two recent benchmark models 1 , 2 by 4–7% in accuracy and 20–40% in efficiency. The recommended framework effectively mitigates both internal and external malicious behaviours and threats while preserving data confidentiality, integrity, and trust. Its flexible and scalable architecture makes it deployable in real-world healthcare infrastructures with constrained devices.

The paper presents analysis of the possibility of using selected hash functions submitted for the SHA-3 competition in the SDEx encryption method. The group of these functions will include the finalists of the SHA-3 competition, i.e. BLAKE, Grøstl, JH, Keccak, Skein. The aim of the analysis is to develop more secure and faster cryptographic algorithm compared to the current version of the SDEx method with SHA- 512 and the AES algorithm. When considering the speed of algorithms, mainly the software implementation will be taken into account, as it is the most commonly used.

In light of the rapid advancement of information technology, data privacy and security have emerged as critical societal concerns. There is an urgent need for the effective implementation of data access control and traceability mechanisms regarding the management of sensitive information.To address this issue, this paper presents an efficient traceable Oblivious Transfer with Access Control (AC-TOT) scheme that integrates traceability and access control mechanisms, with its core design rooted in cryptographic symmetry principles—specifically leveraging the symmetric properties of bilinear pairings to achieve consistent bidirectional verification of security parameters between protocol participants. Our scheme could ensure that only authorized users can access services from the server in a privacy-preserving manner, with the server being aware solely of the number of accessible services while remaining oblivious to their specific content. Furthermore, the scheme permits recipients to access services without undergoing identity verification, thereby mitigating the risk of personal information disclosure. The security analysis demonstrates that the proposed scheme effectively prevents user abuse and enables the sender to trace improper behaviors.

Designers and users of the Internet of Things (IoT) are devoting more and more attention to the issues of security and privacy as well as the integration of data coming from various areas. A critical element of cooperation is building mutual trust and secure data exchange. Because IoT devices usually have small memory resources, limited computing power, and limited energy resources, it is often impossible to effectively use a well-known solution based on the Certification Authority. This article describes the concept of the system for a cryptographic Key Generating and Renewing system (KGR). The concept of the solution is based on the use of the hardware Trusted Platform Module (TPM) v2.0 to support the procedures of creating trust structures, generating keys, protecting stored data, and securing data exchange between system nodes. The main tasks of the system are the secure distribution of a new symmetric key and renewal of an expired key for data exchange parties. The KGR system is especially designed for clusters of the IoT nodes but can also be used by other systems. A service based on the Message Queuing Telemetry Transport (MQTT) protocol will be used to exchange data between nodes of the KGR system.

Wireless Body Area Networks (WBANs), low power, and short-range wireless communication in a near-body area provide advantages, particularly in the medical and healthcare sector: (i) they enable continuous monitoring of patients and (ii) the recording and correlation of physical and biological information. Along with the utilization and integration of these (sensitive) private and personal data, there are substantial requirements concerning security and privacy, as well as protection during processing and transmission. Contrary to the star topology frequently used in various standards, the overall concept of a novel low-data rate token-based WBAN framework is proposed. This work further comprises the evaluation of strategies for handling medical data with WBANs and emphasizes the importance and necessity of encryption and security strategies in the context of sensitive information. Furthermore, this work considers the recent advancements in Artificial Intelligence (AI), which are opening up opportunities for enhancing cyber resilience, but on the other hand, also new attack vectors. Moreover, the implications of targeted regulatory measures, such as the European AI Act, are considered. In contrast to, for instance, the proposed star network topologies of the IEEE 802.15.6 WBAN standard or the Technical Committee (TC) SmartBAN of the European Telecommunication Standards Institute (ETSI), the concept of a ring topology is proposed which concatenates information in the form of a ‘data train’ and thus results in faster and more efficient communication. Beyond that, the conductivity of human skin is included in the approach presented to incorporate a supplementary channel. This direct contact requirement not only fortifies the security of the system but also facilitates a reliable means of secure communication, pivotal in maintaining the integrity of sensitive health data. The work identifies different threat models associated with the WBAN system and evaluates potential data vulnerabilities and risks to maximize security. It highlights the crucial balance between security and efficiency in WBANs, using the token-based approach as a case study. Further, it sets a foundation for future healthcare technology advancements, aiming to ensure the secure and efficient integration of patient data.

Cloud computing technology offers the possibility of inter-organizational medical data sharing at a larger scale. The different organizations can maintain their own cloud environment while exchanging healthcare data among them in a peer-to-peer(P2P) fashion according to some defined polices. However, there are many security and privacy challenges that hamper the adoption of cloud computing solutions in healthcare domain. Besides, due to the privacy sensitivity of healthcare data, an organization may not wish to disclose its identity to others when exchanging data in the network to avoid different attacks by the intruders. Hence, anonymously authenticated data exchange is essential between the different peer organizations. In this paper we propose an anonymous on-the-fly secure data exchange protocol for such environment based on pairing-based cryptography. Our proposed solution allows cloud peers to dynamically generate temporary identities that are used to produce a session key for each session of data exchange. The proposed protocol is robust against different attacks, such as target-oriented, man-in-the middle, masquerade, and message manipulation attacks.

Blockchain is evolving to be a secure and reliable platform for secure data sharing in application areas such as the financial sector, supply chain management, food industry, energy sector, internet of things and healthcare. In this paper, we review existing literature and applications available for the healthcare system using blockchain technology. Besides, this work also proposes multiple workflows involved in the healthcare ecosystem using blockchain technology for better data management. Different medical workflows have been designed and implemented using the ethereum blockchain platform which involves complex medical procedures like surgery and clinical trials. This also includes accessing and managing a large amount of medical data. Within the implementation of the workflows of the medical smart contract system for healthcare management, the associated cost has been estimated for this system in terms of a feasibility study which has been comprehensively presented in this paper. This work would facilitate multiple stakeholders who are involved within the medical system to deliver better healthcare services and optimize cost.