Blockchain technology provides a data structure with inherent security properties that include cryptography, decentralization, and consensus, which ensure trust in transactions. It covers widely applicable usages, such as in intelligent manufacturing, finance, the Internet of things (IoT), medicine and health, and many different areas, especially in medical health data security and privacy protection areas. Its natural attributes, such as contracts and consensus mechanisms, have leading-edge advantages in protecting data confidentiality, integrity, and availability. The security issues are gradually revealed with in-depth research and vigorous development. Unlike traditional paper storage methods, modern medical records are stored electronically. Blockchain technology provided a decentralized solution to the trust-less issues between distrusting parties without third-party guarantees, but the “trust-less” security through technology was easily misunderstood and hindered the security differences between public and private blockchains appropriately. The mentioned advantages and disadvantages motivated us to provide an advancement and comprehensive study regarding the applicability of blockchain technology. This paper focuses on the healthcare security issues in blockchain and sorts out the security risks in six layers of blockchain technology by comparing and analyzing existing security measures. It also explores and defines the different security attacks and challenges when applying blockchain technology, which promotes theoretical research and robust security protocol development in the current and future distributed work environment.

The emergence of Beyond 5G (B5G) networks introduces novel challenges related to interference management, particularly within the context of Multiple-Input, Multiple-Output (MIMO) and Code Division Multiple Access (CDMA) technologies. In this comprehensive review paper, we delve into the intricacies of interference mitigation techniques within the B5G framework, with a specific focus on MIMO and CDMA systems. Firstly, we provide a brief overview of MIMO and CDMA principles, emphasizing their significance in B5G networks. MIMO leverages spatial diversity by employing multiple antennas in both the transmitter and the receiver, thereby enhancing capacity and reliability. CDMA, on the other hand, enables multiple users to share the same frequency band by assigning unique codes to each user. Next, we categorize the various types of interference encountered in MIMO and CDMA systems. These include co-channel interference, adjacent-channel interference, and multiuser interference. Understanding these interference sources is crucial for designing effective mitigation strategies. Our exploration of interference mitigation techniques covers state-of-the-art approaches tailored for MIMO and CDMA scenarios. Lastly, we discuss future research directions in interference mitigation for B5G networks. This review paper provides valuable insights for researchers, practitioners, and network designers seeking to enhance the robustness and efficiency of B5G communication systems by effectively mitigating interference in MIMO and CDMA contexts.

Elements in massive narrowband Internet of Things (NB-IoT) for 5G networks suffer severely from packet drops due to queue overflow. Active Queue Management (AQM) techniques help in maintaining queue length by dropping packets early, based on certain defined parameters. In this paper, we have proposed an AQM technique, called Aggressive Random Early Detection (AgRED) which, in comparison to previously used Random Early Detection (RED) and exponential RED technique, improves the overall end-to-end delay, throughput, and packet delivery ratio of the massive NB-IoT 5G network while using UDP. This improvement has been achieved due to a sigmoid function used by the AgRED technique, which aggressively and randomly drops the incoming packets preventing them from filling the queue. Because of the incorporation of the AgRED technique, the queue at different nodes will remain available throughout the operation of the network and the probability of delivering the packets will increase. We have analyzed and compared the performance of our proposed AgRED technique and have found that the performance gain for the proposed technique is higher than other techniques (RED and exponential RED) and passive queue management techniques (drop-tail and drop-head). The improvement in results is most significant in congested network deployment scenarios and provides improvements in massive Machine Type Communication, while also supporting ultra-low latency and reliable communication for 5G applications.

Various routing protocols have been developed for wireless ad hoc networks to shift from infrastructure-based networks to self-controlling and self-configurable networks. These ad hoc networks are easy to implement and have plenty of application in the fields of healthcare, transportation, smart cities, etc. Although almost all of the routing protocols work on the Open Systems Interconnection (OSI) model’s network layer, a few routing protocols support routing on the data link layer of the OSI model rather than the conventional one. One of these routing protocols include the Better Approach To Mobile Ad Hoc Networking (BATMAN). Though BATMAN is a comparably new routing protocol and included in the Linux kernel, it suffers from performance deterioration and latency issues that need to be addressed especially in the Internet of Things (IoT). This paper presents a symmetry-based split hop penalty for BATMAN version 4 to improve the network’s performance in multi-hop scenarios. Split hop penalty defines two different sets of penalties to accommodate the routing protocol metric based on the interface media type. The experiments were conducted within the campus building of the university with physical nodes, and the obtained results highlight that overall performance is improved in terms of throughput, latency, and jitter while no performance gain is measured in packet loss and routing loops that are still present.

IEEE defines the standard 802.15.4 for Low Data Rate Wireless Personal Area Networks (LR-WPAN) to be used with Internet of Things (IoT) sensor devices. IoT devices utilizing this standard suffer from traffic congestion on a node level in dense network scenarios in real time applications. Active queue management (AQM) schemes can optimize the queues of the nodes in order to relive nodes from congestion and improve performance. This paper investigates the impact of Aggressive Random Early Detection (AgRED) AQM in dense network configuration with larger payload and higher service rate for LR-WPAN. The findings indicate better delay, throughput and packet delivery ratio when using AgRED as compared to RED.