Research Publications (Engineering and Built Environment)
Permanent URI for this collectionhttp://ir-dev.dut.ac.za/handle/10321/215
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Item A taxonomy on smart healthcare technologies : security framework, case study, and future directions(Hindawi Limited, 2022-07-05) Chaudhary, Sachi; Kakkar, Riya; Jadav, Nilesh Kumar; Nair, Anuja; Gupta, Rajesh; Tanwar, Sudeep; Agrawal, Smita; Alshehri, Mohammad Dahman; Sharma, Ravi; Sharma, Gulshan; Davidson, Innocent E.There is a massive transformation in the traditional healthcare system from the specialist-centric approach to the patient-centric approach by adopting modern and intelligent healthcare solutions to build a smart healthcare system. It permits patients to directly share their medical data with the specialist for remote diagnosis without any human intervention. Furthermore, the remote monitoring of patients utilizing wearable sensors, Internet of Things (IoT) technologies, and artificial intelligence (AI) has made the treatment readily accessible and affordable. However, the advancement also brings several security and privacy concerns that poorly maneuvered the effective performance of the smart healthcare system. An attacker can exploit the IoT infrastructure, perform an adversarial attack on AI models, and proliferate resource starvation attacks in smart healthcare system. To overcome the aforementioned issues, in this survey, we extensively reviewed and created a comprehensive taxonomy of various smart healthcare technologies such as wearable devices, digital healthcare, and body area networks (BANs), along with their security aspects and solutions for the smart healthcare system. Moreover, we propose an AI-based architecture with the 6G network interface to secure the data exchange between patients and medical practitioners. We have examined our proposed architecture with the case study based on the COVID-19 pandemic by adopting unmanned aerial vehicles (UAVs) for data exchange. The performance of the proposed architecture is evaluated using various machine learning (ML) classification algorithms such as random forest (RF), naive Bayes (NB), logistic regression (LR), linear discriminant analysis (LDA), and perceptron. The RF classification algorithm outperforms the conventional algorithms in terms of accuracy, i.e., 98%. Finally, we present open issues and research challenges associated with smart healthcare technologiesItem Fusion in cryptocurrency price prediction: a decade survey on recent advancements, architecture, and potential future directions(Institute of Electrical and Electronics Engineers (IEEE), 2022) Patel, Nisarg P.; Parekh, Raj; Thakkar, Nihar; Gupta, Rajesh; Tanwar, Sudeep; Sharma, Gulshan; Davidson, Innocent E.; Sharma, RaviCryptographic forms of money are distributed peer-to-peer (P2P) computerized exchange mediums, where the exchanges or records are secured through a protected hash set of secure hash algorithm-256 (SHA-256) and message digest 5 (MD5) calculations. Since their initiation, the prices seem highly volatile and came to their amazing cutoff points during the COVID-19 pandemic. This factor makes them a popular choice for investors with an aim to get higher returns over a short span of time. The colossal high points and low points in digital forms of money costs have drawn in analysts from the scholarly community as well as ventures to foresee their costs. A few machines and deep learning algorithms like gated recurrent unit (GRU), long short-term memory (LSTM), autoregressive integrated moving average with explanatory variable (ARIMAX), and a lot more have been utilized to exactly predict and investigate the elements influencing cryptocurrency prices. The current literature is totally centered around the forecast of digital money costs disregarding its reliance on other cryptographic forms of money. However, Dash coin is an individual cryptocurrency, but it is derived from Bitcoin and Litecoin. The change in Bitcoin and Litecoin prices affects the Dash coin price. Motivated from these, we present a cryptocurrency price prediction framework in this paper. It acknowledges different cryptographic forms of money (which are subject to one another) as information and yields higher accuracy. To illustrate this concept, we have considered a price prediction of Dash coin through the past days’ prices of Dash, Litecoin, and Bitcoin as they have hierarchical dependency among them at the protocol level. We can portray the outcomes that the proposed scheme predicts the prices with low misfortune and high precision. The model can be applied to different digital money cost expectations.Item Coalition games for performance evaluation in 5G and beyond networks : a survey(Institute of Electrical and Electronics Engineers (IEEE), 2022) Singh, Upendra; Ramaswamy, Aditya; Dua, Amit; Kumar, Neeraj; Tanwar, Sudeep; Sharma, Gulshan; Davidson, Innocent E.; Sharma, RaviThe 5G network is an emerging field of the research community. 5G is a multi-disciplinary network that aims to support a wide range of services. 5G network has an objective to support a massive number of connected devices. Game theory has an extensive role in wireless network management. Game theory is an approach to analyzing and modeling the system where multiple actors have a role in decisionmaking with independent objectives and actions. The game theory is an exciting methodology to control the strategic behavior of players and generate an efficient outcome. Coalition game theory can play a crucial role in ensuring cooperation among a massive number of devices. This article provides insight into the current research trends in 5G using coalition games. The work presented in the survey is divided into three categories, namely resource management, interference management, and miscellaneous. This article also provides the foundation about 5G and coalition games highlight the scope of future research.Item Quantum cryptography-as-a-service for secure UAV communication : applications, challenges, and case study(Institute of Electrical and Electronics Engineers (IEEE), 2021) Ralegankar, Vishakha K.; Bagul, Jagruti; Thakkar, Bhaumikkumar; Gupta, Rajesh; Tanwar, Sudeep; Sharma, Gulshan; Davidson, Innocent EwaenThe sudden demand rises in security made researchers come up with solutions that provide instantaneous safety better than the state of the art solutions. The quest for securing data began in the Spartan era. People are now looking to expand this field of research by attacking the existing paradigms and inventing new algorithms that prove to be better than their vulnerable counterparts. Unmanned aerial vehicles (UAVs) are very much prevailing due to their sleek design and flexible mobility in many sectors such as agriculture, army, healthcare, monitoring and surveillance, and many more. We discuss the growth and demand of drone technology along with its importance in this article. The paper also throws some light on the ongoing security issues in real-time scenarios and the role of quantum cryptography in securing the information over the traditional solutions. Motivated by this, we present a survey on quantum cryptography’s importance, role, and benefits in securing UAV communications underlying beyond 5G networks. A novel quantum cryptography-based layered architectural solution is also proposed to achieve high data security and efficient transmission. This paper also present a case study on the battlefield application on the Internet of military things. The performance of the proposed case study system is evaluated by considering the latency, security, and reliabilityItem Ransomware detection, avoidance, and mitigation scheme : a review and future directions(MDPI AG, 2021) Kapoor, Adhirath; Gupta, Ankur; Gupta, Rajesh; Tanwar, Sudeep; Sharma, Gulshan; Davidson, Innocent E.Ransomware attacks have emerged as a major cyber-security threat wherein user data is encrypted upon system infection. Latest Ransomware strands using advanced obfuscation techniques along with offline C2 Server capabilities are hitting Individual users and big corporations alike. This problem has caused business disruption and, of course, financial loss. Since there is no such consolidated framework that can classify, detect and mitigate Ransomware attacks in one go, we are motivated to present Detection Avoidance Mitigation (DAM), a theoretical framework to review and classify techniques, tools, and strategies to detect, avoid and mitigate Ransomware. We have thoroughly investigated different scenarios and compared already existing state of the art review research against ours. The case study of the infamous Djvu Ransomware is incorporated to illustrate the modus-operandi of the latest Ransomware strands, including some suggestions to contain its spread.Item Coalition of 6G and blockchain in AR/VR space : challenges and future directions(Institute of Electrical and Electronics Engineers (IEEE), 2021) Bhattacharya, Pronaya; Saraswat, Deepti; Dave, Amit; Acharya, Mohak; Tanwar, Sudeep; Sharma, Gulshan; Davison, I. E.The digital content wave has proliferated the financial and industrial sectors. Moreover, with the rise of massive internet-of-things, and automation, technologies like augmented reality (AR) and virtual reality (VR) have emerged as prominent players to drive a range of applications. Currently, sixth-generation (6G) networks support enhanced holographic projection through terahertz (THz) bandwidths, ultra-low latency, and massive device connectivity. However, the data is exchanged between autonomous networks over untrusted channels. Thus, to ensure data security, privacy, and trust among stakeholders, blockchain (BC) opens new dimensions towards intelligent resource management, user access control, audibility, and chronology in stored transactions. Thus, the BC and 6G coalition in future AR/VR applications is an emerging investigative topic. To date, authors have proposed surveys that study the integration of BC and 6G in AR/VR in isolation, and hence a coherent survey is required. Thus, to address the gap, the survey is the first-of-its-kind to investigate and study the coalition of BC and 6G in AR/VR space. Based on the proposed research questions in the survey, a solution taxonomy is presented, and different verticals are studied in detail. Furthermore, an integrative architecture is proposed, and open issues and challenges are presented. Finally, a case study, BvTours, is presented that presents a unique survey on BC-based 6G-assisted AR/VR virtual home tour service. The survey intends to propose future resilient frameworks and architectures for different industry 4.0 verticals and would serve as starting directions for academia, industry stakeholders, and research organizations to study the coalition of BC and 6G in AR/VR in industrial applications, gaming, digital content manufacturing, and digital assets protection in greater detail.Item Intercloud resource discovery using Blockchain(Institute of Electrical and Electronics Engineers (IEEE), 2021) Sharma, Mekhla; Singh, Jaiteg; Gupta, Ankur; Tanwar, Sudeep; Sharma, Gulshan; Davidson, I. E.The intercloud represents a logical evolution of cloud computing that extends its computational scale and geographic footprint by collaborating with disparate cloud service providers (CSPs) for resource sharing. Discovering resources belonging to heterogeneous CSPs is not only the primary but critical operation for the intercloud. However, achieving resource discovery in a deterministic manner within this global distributed environment is non-trivial. The literature has proposed several resource discovery approaches for the federated intercloud based on trusted and centralized thirdparty entities. Few approaches, however, exist for the non-federated intercloud, which by definition has no central entity to enable the resource discovery process. Some P2P-based resource discovery techniques have been proposed by researchers, industry players and standardization bodies like Global InterCloud Technology Forum (GICTF). However, existing P2P-based approaches in the non-federated intercloud do not adequately address authentication, non-repudiation of resource information, secure storage and management of transactional records, management of trust/reputation and optimal resource selection and provisioning. This research paper presents BIRD, a Blockchain-based Intercloud Resource Discovery framework that involves participating CSPs connected in a P2P network using blockchain to manage resource information and maintain transactional records. The BIRD framework alleviates the requirement of a trusted third party for discovering and managing resources. The main features involved in the BIRD framework are i) latency optimization, ii) fine-grained control mechanism, and iii) Quality-of Service, Trust and Reputation (QTR) indices. Latency optimization achieves faster resource discovery, fine-grained control mechanism for intercloud resource discovery, and QTR is for quality CSP or resource selection. BIRD uses blockchain to maintain transactions between CSPs securely.Item Deep learning-based cryptocurrency price prediction scheme with inter-dependent relations(Institute of Electrical and Electronics Engineers (IEEE), 2021) Tanwar, Sudeep; Patel, Nisarg P.; Patel, Smit N.; Patel, Jil R.; Sharma, Gulshan; Davidson, Innocent EwaenBlockchain technology is becoming increasingly popular because of its applications in various fields. It gives an edge over the traditional centralized methods as it provides decentralization, immutability, integrity, and anonymity. The most popular application of this technology is cryptocurrencies, which showed a massive rise in their popularity and market capitalization in recent years. Individual investors, big institutions, and corporate firms are investing heavily in it. However, the crypto market is less stable than traditional commodity markets. It can be affected by many technical, sentimental, and legal factors, so it is highly volatile, uncertain, and unpredictable. Plenty of research has been done on various cryptocurrencies to forecast accurate prices, but the majority of these approaches can not be applied in real-time. Motivated from the aforementioned discussion, in this paper, we propose a deep-learning-based hybrid model (includes Gated Recurrent Units (GRU) and Long Short Term Memory (LSTM)) to predict the price of Litecoin and Zcash with inter-dependency of the parent coin. The proposed model can be used in real-time scenarios and it is well trained and evaluated using standard data sets. Results illustrate that the proposed model forecasts the prices with high accuracy compared to existing models