Assistive robotic systems could be a suitable solution to support a variety of health and care services, help independent living, and even simulate affection, to reduce loneliness. However, adoption is limited by several issues, as well as user concerns about ethics, data security, and privacy. Other than the common threats related to internet connectivity, personal robotic systems have advanced interaction possibilities, such as audio, video, touch, and gestures, which could be exploited to gain access to private data that are stored in the robot. Therefore, novel, safer methods of interaction should be designed to safeguard users’ privacy. To solicit further research on secure and private multimodal interaction, this article presents a thorough study of the state-of-the-art literature on data security and user privacy in interactive social robotic systems for health and care. In our study, we focus on social robotics to assist older people, which is a global challenge that is receiving a great deal of attention from the robotics and social care communities. This application will have a significant positive impact on the economy and society, but poses various security and privacy issues. This article analyses the key vulnerable areas where data leakage could occur during a multimodal interaction with a personal assistive robotic system. Thus, blockchain with a resource-aware framework, along with a continuous multifactor authentication mechanism, are envisaged as a potential solution for making such systems secure by design; therefore, increasing trust, acceptability, and adoption. Among the key cybersecurity research challenges, it is crucial to create an intelligent mechanism that autonomously determines the right trade-off between continuous user prompts and system usability, according to data types and personal preferences.

Counterfeiting drugs has been a global concern for years. Considering the lack of transparency within the current pharmaceutical distribution system, research has shown that blockchain technology is a promising solution for an improved supply chain system. This study aims to explore the current solution proposals for distribution systems using blockchain technology. Based on a literature review on currently proposed solutions, it is identified that the secrecy of the data within the system and nodes’ reputation in decision making has not been considered. The proposed prototype uses a zero-knowledge proof protocol to ensure the integrity of the distributed data. It uses the Markov model to track each node’s ‘reputation score’ based on their interactions to predict the reliability of the nodes in consensus decision making. Analysis of the prototype demonstrates a reliable method in decision making, which concludes with overall improvements in the system’s confidentiality, integrity, and availability. The result indicates that the decision protocol must be significantly considered in a reliable distribution system. It is recommended that the pharmaceutical distribution systems adopt a relevant protocol to design their blockchain solution. Continuous research is required further to increase performance and reliability within blockchain distribution systems.

The healthcare sector has undergone a profound transformation, owing to the influential role played by Internet of Medical Things (IoMT) technology. However, there are substantial concerns over these devices’ security and privacy-preserving mechanisms. The current literature on IoMT tends to focus on specific security features, rather than wholistic security concerning Confidentiality, Integrity, and Availability (CIA Triad), and the solutions are generally simulated and not tested in a real-world network. The proposed innovative solution is known as Secure-by-Design Real-Time IoMT Architecture for e-Health Population Monitoring (RTPM) and it can manage keys at both ends (IoMT device and IoMT server) to maintain high privacy standards and trust during the monitoring process and enable the IoMT devices to run safely and independently even if the server is compromised. However, the session keys are controlled by the trusted IoMT server to lighten the IoMT devices’ overheads, and the session keys are securely exchanged between the client system and the monitoring server. The proposed RTPM focuses on addressing the major security requirements for an IoMT system, i.e., the CIA Triad, and conducts device authentication, protects from Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks, and prevents non-repudiation attacks in real time. A self-healing solution during the network failure of live e-health monitoring is also incorporated in RTPM. The robustness and stress of the system are tested with different data types and by capturing live network traffic. The system’s performance is analysed using different security algorithms with different key sizes of RSA (1024 to 8192 bits), AES (128 to 256 bits), and SHA (256 bits) to support a resource-constraint-powered system when integrating with resource-demanding secure parameters and features. In the future, other security features like intrusion detection and prevention and the user’s experience and trust level of such a system will be tested.

The World Health Organization (WHO) in 2016 considered m-health as: “the use of mobile wireless technologies including smart devices such as smartphones and smartwatches for public health”. WHO emphasizes the potential of this technology to increase its use in accessing health information and services as well as promoting positive changes in health behaviours and overall management of diseases. In this regard, the capability of smartphones and smartwatches for m-health monitoring through the collection of patient data remotely, has become an important component in m-health system. It is important that the integrity of the data collected is verified continuously through data authentication before storage. In this research work, we extracted heart rate variability (HRV) and decomposed the signals into sub-bands of detail and approximation coefficients. A comparison analysis is done after the classification of the extracted features to select the best sub-bands. An architectural framework and a used case for m-health data authentication is carried out using two sub-bands with the best performance from the HRV decomposition using 30 subjects’ data. The best sub-band achieved an equal error rate (EER) of 12.42%.

In Ad-hoc networks, resources in terms of bandwidth and battery life are limited; so using a fixed high transmission power limits the durability of a battery life and causes unnecessary high interference while communicating with closer nodes leading to lower overall network throughput. Thus, this paper proposes a new cross layer MAC called Dynamic Neighbour Aware Power-controlled MAC (Dynamic NA-PMAC) for multi-hop Ad-hoc networks that adjust the transmission power by estimating the communication distance based on the overheard signal strength. By dynamically controlling the transmission power based on the receivable signal strength, the probability of concurrent transmission, durability of battery life and bandwidth utilization increases. Moreover, in presence of multiple overlapping signals with different strengths, an optimal transmission power is estimated dynamically to maintain fairness and avoid hidden node issues at the same time. In a given area, since power is controlled, the chances of overlapping the sensing ranges of sources and next hop relay nodes or destination node decreases, so it enhances the probability of concurrent transmission and hence an increased overall throughput. In addition, this paper uses a variable backoff algorithm based on the number of active neighbours, which saves energy and increases throughput when the density of active neighbours is less. The designed mechanism is tested with various random network scenarios using different traffic including CBR, Exponential and TCP in both scenarios (stationary and mobile with high speed) for single as well as multi-hop. Moreover, the proposed model is benchmarked against two variants of power-controlled mechanisms namely Min NA-PMAC and MaxRC-MinDA NA-PMAC to prove that using a fixed minimum transmission power may lead to unfair channel access and using different transmission power for RTS/CTS and Data/ACK leads to lower probability of concurrent transmission respectively.