The COVID-19 epidemic has caused a large number of human losses and havoc in the economic, social, societal, and health systems around the world. Controlling such epidemic requires understanding its characteristics and behavior, which can be identified by collecting and analyzing the related big data. Big data analytics tools play a vital role in building knowledge required in making decisions and precautionary measures. However, due to the vast amount of data available on COVID-19 from various sources, there is a need to review the roles of big data analysis in controlling the spread of COVID-19, presenting the main challenges and directions of COVID-19 data analysis, as well as providing a framework on the related existing applications and studies to facilitate future research on COVID-19 analysis. Therefore, in this paper, we conduct a literature review to highlight the contributions of several studies in the domain of COVID-19-based big data analysis. The study presents as a taxonomy several applications used to manage and control the pandemic. Moreover, this study discusses several challenges encountered when analyzing COVID-19 data. The findings of this paper suggest valuable future directions to be considered for further research and applications.

In the medical fields, wearable body area sensors network (WBAN) is playing a major role in maintaining user health by providing convenience service for the patient and doctors. However, sensor data transmission in an insecure communication channel enables the attacker from tampering the sensor data, disguising as a legitimate user, or intercepting the forwarded packets from its unprotected sources. A wide variety of secure authentication schemes were proposed to improve the communicated channels' reliability in protecting the user data. Moreover, those schemes are lacking the guarding of nodes anonymity, key management, and size. Thence, we propose a lightweight WBAN authentication with two protocols P-I for authentication and P-II for re-authentication to protect the nodes anonymity and increase the efficiency. Furthermore, our scheme employed better key management with high randomness of the security parameters to provide higher protection as a trade-off between security and efficiency. The scheme formal proof for the key agreement and mutual authentication is conducted through (Burrows Abadi Nadeem) BAN logic.

Coughing is a common symptom of several respiratory diseases. The sound and type of cough are useful features to consider when diagnosing a disease. Respiratory infections pose a significant risk to human lives worldwide as well as a significant economic downturn, particularly in countries with limited therapeutic resources. In this study we reviewed the latest proposed technologies that were used to control the impact of respiratory diseases. Artificial Intelligence (AI) is a promising technology that aids in data analysis and prediction of results, thereby ensuring people's well-being. We conveyed that the cough symptom can be reliably used by AI algorithms to detect and diagnose different types of known diseases including pneumonia, pulmonary edema, asthma, tuberculosis (TB), COVID19, pertussis, and other respiratory diseases. We also identified different techniques that produced the best results for diagnosing respiratory disease using cough samples. This study presents the most recent challenges, solutions, and opportunities in respiratory disease detection and diagnosis, allowing practitioners and researchers to develop better techniques. INDEX TERMSArtificial intelligence (AI), cough detection, 2019 novel coronavirus disease (Covid-19), respiratory illness diagnosis, cough-based diagnosis.

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Wireless Healthcare Sensor Network (WHSN) is a benchmarking technology deployed to levitate the quality of lives for the patients and doctors. WHSN systems must fit IEEE 802.15.6 standard for specific application criteria, unlike some standard criteria that are difficult to meet. Therefore, many security models were suggested to enhance the security of the WHSN and promote system performance. Yu and Park proposed a three-factor authentication scheme based on the smart card, biometric, and password, and their scheme can be easily employed in three-tier WHSN architecture. Furthermore, they claimed that their scheme can withstand guessing attack and provide anonymity, although, after cryptanalysis, we found that their scheme lacks both. Accordingly, we suggested a three-factor authentication scheme with better system confusion due to multiplex parametric features, hash function, and higher key size to increase the security and achieve anonymity for the connected nodes. Moreover, the scheme included initialization, authentication, re-authentication, secure node addition, user revocation, and secure data transmission via blockchain technology. The formal analysis of the scheme was conducted by BAN logic (Burrows Abadi Nadeem) and the simulation was carried out by Tamarin prover to validate that the proposed scheme is resistant to replay, session hijacking, and guessing attacks, plus it provides anonymity, perfect forward secrecy, and authentication along with the key agreement.

Wearable body area network (WBAN) aids the communication between the health providers and patients by supporting health monitoring services. It assists the users to maintain their health status records by collecting the body signals and transmitting them for further processing measurements. However, sensor data are publicly transferred through insecure network that facilitates the attacker malicious acts like performing masquerading attack, man in the middle, and snooping. Several authentication techniques were suggested to levitate the security of the communication channels to preserve the user data from exposure. Moreover, authentication schemes aid plenty of security issues related to user and data privacy, anonymity, repudiation, confidentiality, and integrity, but they lack performance efficiency. On the other hand, it is very hard to find the balance between security and efficiency in most of the authentication schemes, especially for the WBAN platform that consists of memory and processing constraint devices. Therefore, this paper surveys and discusses the latest authentication schemes types, techniques, and system features. Also, it highlights their strengths and weaknesses towards common knowingly attacks and provides a comparison between the popular scheme validation proofs and simulation tools. Thence, this paper draws a path for the new direction of the authentication technologies, the authentication schemes open issues, and the potential future evolution in this area.

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