The new ‘normal’ defined during the COVID-19 pandemic has forced us to re-assess how people with special needs thrive in these unprecedented conditions, such as those with Autism Spectrum Disorder (ASD). These changing/challenging conditions have instigated us to revisit the usage of telehealth services to improve the quality of life for people with ASD. This study aims to identify mobile applications that suit the needs of such individuals. This work focuses on identifying features of a number of highly-rated mobile applications (apps) that are designed to assist people with ASD, specifically those features that use Artificial Intelligence (AI) technologies. In this study, 250 mobile apps have been retrieved using keywords such as autism, autism AI, and autistic. Among 250 apps, 46 were identified after filtering out irrelevant apps based on defined elimination criteria such as ASD common users, medical staff, and non-medically trained people interacting with people with ASD. In order to review common functionalities and features, 25 apps were downloaded and analysed based on eye tracking, facial expression analysis, use of 3D cartoons, haptic feedback, engaging interface, text-to-speech, use of Applied Behaviour Analysis therapy, Augmentative and Alternative Communication techniques, among others were also deconstructed. As a result, software developers and healthcare professionals can consider the identified features in designing future support tools for autistic people. This study hypothesises that by studying these current features, further recommendations of how existing applications for ASD people could be enhanced using AI for (1) progress tracking, (2) personalised content delivery, (3) automated reasoning, (4) image recognition, and (5) Natural Language Processing (NLP). This paper follows the PRISMA methodology, which involves a set of recommendations for reporting systematic reviews and meta-analyses.

Recently, there has been increasing interest in employing blockchain in different applications, other than crypto-currencies. Blockchains allow a peer to peer distributed network where different nodes communicate with each other, in a trustless manner. Long Range Wide Area Network (LoRaWAN) is an Internet of Things (IoT) technology, which enables long range communication. Although LoRaWAN networks are secure, the LoRaWAN join procedure is susceptible to replay and jamming attacks. Moreover, trust between network server and LoRa end device is the basic foundation of LoRaWAN network however, the centralized nature of network servers raise trust issues between network operators and customers. To solve this problem, we propose a lightweight two factor authentication mechanism for LoRaWAN join procedure, based on blockchain technology. The proposed blockchain based framework provides an extra layer of security for LoRaWAN join procedure and build trust among LoRaWAN network components. The proposed framework is validated using the Ethereum blockchain. The results demonstrate that the proposed framework provides efficient system performance in terms of throughput and latency. The proposed blockchain architecture is a cost effective solution, which can be utilized in the LoRaWAN network with few network servers and LoRa end device, having no strict requirement of throughput and latency.

In the recent past, few works have been done by combining attribute-based access control with multi-user PEKS, i.e., public key encryption with keyword search. Such attribute enabled searchable encryption is most suitable for applications where the changing of privileges is done once in a while. However, to date, no efficient and secure scheme is available in the literature that is suitable for these applications where changing privileges are done frequently. In this paper our contributions are twofold. Firstly, we propose a new PEKS scheme for string search, which, unlike the previous constructions, is free from bi-linear mapping and is efficient by 97% compared to PEKS for string search proposed by Ray et.al in TrustCom 2017. Secondly, we introduce role based access control (RBAC) to multi-user PEKS, where an arbitrary group of users can search and access the encrypted files depending upon roles. We termed this integrated scheme as R-PEKS. The efficiency of R-PEKS over the PEKS scheme is up to 90%. We provide formal security proofs for the different components of R-PEKS and validate these schemes using a commercial dataset.