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Advancements in blockchain technology and network technology are bringing in a new era in electronic voting systems. These systems are characterized by enhanced security, efficiency, and accessibility. In this paper, we compose a comparative analysis of blockchain-based electronic voting (e-voting) systems using blockchain technology, cryptographic techniques, counting methods, and security requirements. The core of the analysis involves a detailed examination of blockchain-based electronic voting systems, focusing on the variations in architecture, cryptographic techniques, vote counting methods, and security. We also introduce a novel blockchain-based e-voting system, which integrates advanced methodologies, including the Borda count and Condorcet method, into e-voting systems for improved accuracy and representation in vote tallying. The system’s design features a flexible and amendable blockchain structure, ensuring robustness and security. Practical implementation on a Raspberry Pi 3 Model B+ demonstrates the system’s feasibility and adaptability in diverse environments. Our study of the evolution of e-voting systems and the incorporation of blockchain technology contributes to the development of secure, transparent, and efficient solutions for modern democratic governance. Full article

This paper tackles the challenge of secure and reliable data transmission in diamond network configurations featuring two untrusted relays with low-security clearance. We propose an innovative approach that employs lossy-decode and -forward relaying at these untrusted relays to boost transmission reliability while safeguarding the source information from potential eavesdroppers. An essential contribution of this work is the introduction of the reliable and secure probability (RSP) metric. This metric assesses the likelihood of the destination successfully retrieving the original information while maintaining its confidentiality from untrusted relays. Our analysis shows that the integration of cooperative jamming signals markedly enhances the RSP, resulting in superior security and reliability. Simulation results confirm that optimal power distribution among the source, relays, and destination further maximizes the RSP. These findings underscore the effectiveness of our proposed scheme in ensuring secure and reliable communication in environments with untrusted relays, suggesting its potential as a robust solution for secure communications in diamond network configurations. Full article

Internet of Vehicles applications are known to be critical and time-sensitive. The value proposition of edge computing comprises its lower latency, advantageous bandwidth consumption, privacy, management, efficiency of treatments, and mobility, which aim to improve vehicular and traffic services. Successful stories have been observed between IoV and edge computing to support smooth mobility and the use of local resources. However, vehicle travel, especially due to high-speed movement and intersections, can result in IoV devices losing connection and/or processing with high latency. This paper proposes a Cluster Collaboration Vehicular Edge Computing (CCVEC) framework that aims to guarantee and enhance the connectivity between vehicle sensors and the cloud by utilizing the edge computing paradigm in the middle. The objectives are achieved by utilizing the cluster management strategies deployed between cloud and edge computing servers. The framework is implemented in OpenStack cloud servers and evaluated by measuring the throughput, latency, and memory parameters in two different scenarios. The results obtained show promising indications in terms of latency (approximately 390 ms of the ideal status) and throughput (30 kB/s) values, and thus appears acceptable in terms of performance as well as memory. Full article

Ensuring high reliability and low latency poses challenges for numerous applications that require rigid performance guarantees, such as industrial automation and autonomous vehicles. Our research primarily concentrates on addressing the real-time requirements of ultra-reliable low-latency communication (URLLC). Specifically, we tackle the challenge of hard delay constraints in real-time transmission systems, overcoming this obstacle through a finite blocklength coding scheme. In the physical layer, we encode randomly arriving packets using a variable-length coding scheme and transmit the encoded symbols by truncated channel inversion over parallel channels. In the network layer, we model the encoding and transmission processes as tandem queues. These queues backlog the data bits waiting to be encoded and the encoded symbols to be transmitted, respectively. This way, we represent the system as a two-dimensional Markov chain. By focusing on instances when the symbol queue is empty, we simplify the Markov chain into a one-dimensional Markov chain, with the packet queue being the system state. This approach allows us to analytically express power consumption and formulate a power minimization problem under hard delay constraints. Finally, we propose a heuristic algorithm to solve the problem and provide an extensive evaluation of the trade-offs between the hard delay constraint and power consumption. Full article

The majority of local IPv6 networks continue to remain insecure and vulnerable to neighbor spoofing attacks. The Secure Neighbor Discovery (SEND) standard and its concomitant Cryptographically Generated Addressing (CGA) scheme were accepted by large standard bodies to codify practical mitigations. SEND and CGA have never seen widespread adoption due to their complexities, obscurity, costs, compatibility issues, and continued lack of mature implementations. In light of their poor adoption, research since their standardization has continued to find new perspectives and proffer new ideas. The orthodox solutions for securing Neighbor Discovery have historically struggled to successfully harmonize three core ideals: simplicity, flexibility, and privacy preservation. This research introduces Voucher-Based Addressing, a low-configuration, low-cost, and high-impact alternative to IPv6 address generation methods. It secures the Neighbor Discovery address resolution process while remaining simple, highly adaptable, indistinguishable, and privacy-focused. Applying a unique concoction of cryptographic key derivation functions, link-layer address binding, and neighbor consensus on the parameters of address generation, the resolved address bindings are verifiable without the need for complex techniques that have hindered the adoption of canonical specifications. Full article

Relaying with network coding forms a basis for a variety of collaborative communication systems. A linear block coding framework for multi-way relaying using network codes introduced in the literature shows great promise for understanding, analyzing, and designing such systems. So far, this technique has been used with low-density parity check (LDPC) codes and belief propagation (BP) decoding. Polar codes have drawn significant interest in recent years because of their low decoding complexity and good performance. Our paper considers the use of polar codes also as network codes with differential binary phase shift keying (DBPSK), bypassing the need for channel state estimation in multi-way selective detect-and-forward (DetF) cooperative relaying. We demonstrate that polar codes are suitable for such applications. The encoding and decoding complexity of such systems for linear block codes is analyzed using maximum likelihood (ML) decoding for LDPC codes with log-BP decoding and polar codes with successive cancellation (SC) as well as successive cancellation list (SCL) decoding. We present Monte-Carlo simulation results for the performance of such a multi-way relaying system, employing polar codes with different lengths and code rates. The results demonstrate a significant performance gain compared to an uncoded scheme. The simulation results show that the error performance of such a system employing polar codes is comparable to LDPC codes with log-BP decoding, while the decoding complexity is much lower. Furthermore, we consider a hard threshold technique at user terminals for determining whether a relay transmits or not. This technique makes the system practical without increasing the complexity and can significantly reduce the degradation from intermittent relay transmissions that is associated with such a multi-way relaying protocol. Full article

To enhance user experiences of reaching destinations in large, complex buildings, we have developed a indoor navigation system using Unity and a smartphone called INSUS. It can reset the user location using a quick response (QR) code to reduce the loss of direction of the user during navigation. However, this approach needs a number of QR code sheets to be prepared in the field, causing extra loads at implementation. In this paper, we propose another reset method to reduce loads by recognizing information of naturally installed signs in the field using object detection and Optical Character Recognition (OCR) technologies. A lot of signs exist in a building, containing texts such as room numbers, room names, and floor numbers. In the proposal, the Sign Image is taken with a smartphone, the sign is detected by YOLOv8, the text inside the sign is recognized by PaddleOCR, and it is compared with each record in the Room Database using Levenshtein distance. For evaluations, we applied the proposal in two buildings in Okayama University, Japan. The results show that YOLOv8 achieved [email protected] $0.995$ and [email protected]:0.95 $0.978$, and PaddleOCR could extract text in the sign image accurately with an averaged CER% lower than 10%. The combination of both YOLOv8 and PaddleOCR decreases the execution time by $6.71s$ compared to the previous method. The results confirmed the effectiveness of the proposal. Full article

Persistent security challenges in Industry 4.0 due to the limited resources of IoT devices necessitate innovative solutions. Addressing this, this study introduces the ASCON algorithm for lightweight authenticated encryption with associated data, enhancing confidentiality, integrity, and authenticity within IoT limitations. By integrating Digital Twins, the framework emphasizes the need for robust security in Industry 4.0, with ASCON ensuring secure data transmission and bolstering system resilience against cyber threats. Practical validation using the MQTT protocol confirms ASCON’s efficacy over AES-GCM, highlighting its potential for enhanced security in Industry 4.0. Future research should focus on optimizing ASCON for microprocessors and developing secure remote access tailored to resource-constrained devices, ensuring adaptability in the digital era. Full article

Delay and Disruption Tolerant Networking (DTN) is a network architecture created basically to overcome non-continuing connectivity. There has been a great deal of research on this topic, from space communication to terrestrial applications. Since there are still many places on earth where there is no means of communication, the focus of this work is on the latest. A systematic literature review (SLR) was performed to know the main issues and advances related to the implementation of DTN for terrestrial and TCP/IP applications, especially in places where telecommunication infrastructure is lacking. The result is a classification of papers based on key aspects, such as architecture, performance, routing, and applications. A matrix of all the papers about these aspects is included to help researchers find the missing piece and concrete terrestrial solutions. The matrix uses three colors, green, yellow, and red according to the focus, either high, medium, or low, so that it is easy to identify specific papers. Full article

Radio Frequency Identification (RFID) technology plays a crucial role in various Internet of Things (IoT) applications, necessitating the integration of RFID systems into dense networks. However, the presence of numerous readers leads to collisions, degrading communication between readers and tags and compromising system performance. To tackle this challenge, researchers have proposed Medium Access Control (MAC) layer protocols employing different channel access methods. In this paper, we present a novel solution, the Distributed Time Slot Anti-Collision protocol (DTS-AC), which employs a new TDMA notification system to address Reader-to-Reader Interference (RRI), while incorporating FDMA-based frequency resource management to resolve Reader-to-Tag Interference (RTI) collision issues. Simulation results demonstrate that DTS-AC significantly improves performance in dense RFID networks by enhancing read rates, with scalability benefits based on the number of readers, channels, and Time Slots (TSs). Moreover, the cost-effectiveness of DTS-AC facilitates efficient deployment in RFID networks, emphasizing considerations of time delay and data sensitivity. Full article

Indoor location services often use Bluetooth low energy (BLE) devices for their low energy consumption and easy implementation. Applications like device monitoring, ranging, and asset tracking utilize the received signal strength (RSS) of the BLE signal to estimate the proximity of a device from the receiver. However, in multipath environments, RSS-based solutions may not provide an accurate estimation. In such environments, receivers with antenna arrays are used to calculate the difference in time of flight (ToF) and therefore calculate the direction of arrival (DoA) of the Bluetooth signal. Other techniques like triangulation have also been used, such as having multiple transmitters or receivers as a network of sensors. To find a lost item, devices like Tile^© use an onboard beeper to notify users of their presence. In this paper, we present a system that uses a single-measurement device and describe the method of measurement to estimate the location of a BLE device using RSS. A BLE device is configured as an Eddystone beacon for periodic transmission of advertising packets with RSS information. We developed a smartphone application to read RSS information from the beacon, designed an algorithm to estimate the DoA, and used the phone’s internal sensors to evaluate the DoA with respect to true north. The proposed measurement method allows for asset tracking by iterative measurements that provide the direction of the beacon and take the user closer at every step. The receiver application is easily deployable on a smartphone, and the algorithm provides direction of the beacon within a 30° range, as suggested by the provided results. Full article

The escalating demand for high-quality video streaming poses a major challenge for communication networks today. Catering to these bandwidth-hungry video streaming services places a huge burden on the limited spectral resources of communication networks, limiting the resources available for other services as well. Large volumes of video traffic can lead to severe network congestion, particularly during live streaming events, which require sending the same content to a large number of users simultaneously. For such applications, multicast transmission can effectively combat network congestion while meeting the demands of all the users by serving groups of users requesting the same content over shared spectral resources. Streaming services can further benefit from multi-connectivity, which allows users to receive content from multiple base stations simultaneously. Integrating multi-connectivity within multicast streaming can improve the system resource utilization while also providing seamless connectivity to multicast users. Toward this end, this work studied the impact of using multi-connectivity (MC) alongside wireless multicast for meeting the resource requirements of video streaming. Our findings show that MC substantially enhances the performance of multicast streaming, particularly benefiting cell-edge users who often experience poor channel conditions. We especially considered the number of users that can be simultaneously served by multi-connected multicast systems. It was observed that about $60\%$ of the users that are left unserved under single-connectivity multicast are successfully served using the same resources by employing multi-connectivity in multicast transmissions. We prove that the optimal resource allocation problem for MC multicast is NP-hard. As a solution, we present a greedy approximation algorithm with an approximation factor of $(1-1/e)$. Furthermore, we establish that no other polynomial-time algorithm can offer a superior approximation. To generate realistic video traffic patterns in our simulations, we made use of traces from actual videos. Our results clearly demonstrate that multi-connectivity leads to significant enhancements in the performance of multicast streaming. Full article

Fault tolerance is a critical aspect for any wireless sensor network (WSN), which can be defined in plain terms as the quality of being dependable or performing consistently well. In other words, it may be described as the effectiveness of fault tolerance in the event of crucial component failures in the network. As a WSN is composed of sensors with constrained energy resources, network disconnections and faults may occur because of a power failure or exhaustion of the battery. When such a network is used for precision agriculture, which needs periodic and timely readings from the agricultural field, necessary measures are needed to handle the effects of such faults in the network. As climate change is affecting many parts of the globe, WSN-based precision agriculture could provide timely and early warnings to the farmers about unpredictable weather events and they could take the necessary measures to save their crops or to lessen the potential damage. Considering this as a critical application area, in this paper, we propose a fault-tolerant scheme for WSNs deployed for precision agriculture. Along with the description of our mechanism, we provide a theoretical operational model, simulation, analysis, and a formal verification using the UPPAAL model checker. Full article

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. Full article

Optical backbone networks, characterized by using optical fibers as a transmission medium, constitute the fundamental infrastructure employed today by network operators to deliver services to users. As network capacity is one of the key factors influencing optical network performance, it is important to comprehend its limitations and have the capability to estimate its value. In this context, we revisit the concept of capacity from various perspectives, including channel capacity, link capacity, and network capacity, thus providing an integrated view of the problem within the framework of the backbone tier. Hence, we review the fundamental concepts behind optical networks, along with the basic physical phenomena present in optical fiber transmission, and provide methodologies for estimating the different types of capacities, mainly using simple formulations. In particular, we propose a method to evaluate the network capacity that relies on the optical reach to account for physical layer aspects, in conjunction with capacitated routing techniques for traffic routing. We apply this method to three reference networks and obtain capacities ranging from tens to hundreds of terabits/s. Whenever possible, we also compare our results with published experimental data to understand how they relate. Full article

Data protection issues stemming from the use of machine learning algorithms that are used in automated decision-making systems are discussed in this paper. More precisely, the main challenges in this area are presented, putting emphasis on how important it is to simultaneously ensure the accuracy of the algorithms as well as privacy and personal data protection for the individuals whose data are used for training the corresponding models. In this respect, we also discuss how specific well-known data protection attacks that can be mounted in processes based on such algorithms are associated with a lack of specific legal safeguards; to this end, the General Data Protection Regulation (GDPR) is used as the basis for our evaluation. In relation to these attacks, some important privacy-enhancing techniques in this field are also surveyed. Moreover, focusing explicitly on deep learning algorithms as a type of machine learning algorithm, we further elaborate on one such privacy-enhancing technique, namely, the application of differential privacy to the training dataset. In this respect, we present, through an extensive set of experiments, the main difficulties that occur if one needs to demonstrate that such a privacy-enhancing technique is, indeed, sufficient to mitigate all the risks for the fundamental rights of individuals. More precisely, although we manage—by the proper configuration of several algorithms’ parameters—to achieve accuracy at about 90% for specific privacy thresholds, it becomes evident that even these values for accuracy and privacy may be unacceptable if a deep learning algorithm is to be used for making decisions concerning individuals. The paper concludes with a discussion of the current challenges and future steps, both from a legal as well as from a technical perspective. Full article

An intrusion detection system (IDS) perform postcompromise detection of security breaches whenever preventive measures such as firewalls do not avert an attack. However, these systems raise a vast number of alerts that must be analyzed and triaged by security analysts. This process is largely manual, tedious, and time-consuming. Alert correlation is a technique that reduces the number of intrusion alerts by aggregating alerts that are similar in some way. However, the correlation is performed outside the IDS through third-party systems and tools, after the IDS has already generated a high volume of alerts. These third-party systems add to the complexity of security operations. In this paper, we build on the highly researched area of alert and event correlation by developing a novel hierarchical event correlation model that promises to reduce the number of alerts issued by an intrusion detection system. This is achieved by correlating the events before the IDS classifies them. The proposed model takes the best features from similarity and graph-based correlation techniques to deliver an ensemble capability not possible by either approach separately. Further, we propose a correlation process for events rather than alerts as is the case in the current art. We further develop our own correlation and clustering algorithm which is tailor-made to the correlation and clustering of network event data. The model is implemented as a proof of concept with experiments run on standard intrusion detection sets. The correlation achieves an 87% data reduction through aggregation, producing nearly 21,000 clusters in about 30 s. Full article

With the surge in cyber attacks, there is a pressing need for more robust network intrusion detection systems (IDSs). These IDSs perform at their best when they can monitor all the traffic coursing through the network, especially within a software-defined network (SDN). In an SDN configuration, the control plane and data plane operate independently, facilitating dynamic control over network flows. Typically, an IDS application resides in the control plane, or a centrally located network IDS transmits security reports to the controller. However, the controller, equipped with various control applications, may encounter challenges when analyzing substantial data, especially in the face of high traffic volumes. To enhance the processing power, detection rates, and alleviate the controller’s burden, deploying multiple instances of IDS across the data plane is recommended. While deploying IDS on individual switches within the data plane undoubtedly enhances detection rates, the associated costs of installing one at each switch raise concerns. To address this challenge, this paper proposes the deployment of IDS chains across the data plane to boost detection rates while preventing controller overload. The controller directs incoming traffic through alternative paths, incorporating IDS chains; however, potential delays from retransmitting traffic through an IDS chain could extend the journey to the destination. To address these delays and optimize flow distribution, our study proposes a method to balance flow assignments to specific IDS chains with minimal delay. Our approach is validated through comprehensive testing and evaluation using a test bed and trace-based simulation, demonstrating its effectiveness in reducing delays and hop counts across various traffic scenarios. Full article