Blockchain Based Secure Interoperable Framework for the Internet of Medical Things

Internet of Medical Things (IoMT) has revolutionized the way medical infrastructure has been managed in the past. Multiple platforms in IoMT have disparate communication standards, data format requirements, and access policies, which produce immense overhead during data transfer among these platforms. In order to provide seamless healthcare services using IoMT, interoperability concerns of heterogeneous devices need to be addressed. Smart contracts using blockchain provide a secure communication for distributed objects to interact in a secure way. We propose a Blockchain-based Secure Interoperable Framework (BSIIoMT) using smart contracts for secure communication in IoMT. We present components, workflow, and design considerations of the BSIIoMT framework to show the feasibility of using edge-enabled blockchain for secure interoperability in IoMT. The BSIIoMT framework is an ongoing project where we present the framework and its components in this research where further results and evaluation will be presented in future

An offloading method using decentralized P2P-enabled mobile edge servers in edge computing

Edge computing has emerged as a promising infrastructure for providing elastic resources in the proximity of mobile users. Owing to resource limitations in mobile devices, offloading several computational tasks from mobile devices to mobile edge servers is the main means of improving the quality of experience of mobile users. In fact, because of the high speeds of moving vehicles on expressways, there would be numerous candidate mobile edge servers available for them to offload their computational workload. However, the selection of the mobile edge server to be utilized and how much computation should be offloaded to meet the corresponding task deadlines without large computing bills are topics that have not been discussed much. Furthermore, with the increasing deployment of mobile edge servers, their centralized management would cause certain performance issues. In order to address these challenges, we firstly apply peer-to-peer networks to manage geo-distributed mobile edge servers. Secondly, we propose a new deadline-aware and cost-effective offloading approach, which aims to improve the offloading efficiency for vehicles and allows additional tasks to meet their deadlines. The proposed approach was validated for its feasibility and efficiency by means of extensive experiments, which are presented in this paper

Developing smart city services using intent-aware recommendation systems: A survey

Smart cities could be defined as urban areas that use Information and Communication Technology (ICT) to solve city problems in efficient and sustainable ways. Intent-aware Recommender Systems (IARS) within ICT play a crucial role in filtering useless information according to user demands and assist in decision-making in various smart city platforms. In smart cities, the user traces on IoT, RFIDs, mobiles, and smart sensors capture actual user intent of performing an activity and enhance user satisfaction by proposing optimal services. This paper presents a detailed literature survey of the field of IARS and how it can be used for developing smart city services. First, we present the evolution of IARS with the development of computing technology. Then, we present case studies, synergies, advances, and a reference implementation architecture of IARS for smart cities. We discuss requirements for developing smart city services using IARS. Furthermore, we devise a comprehensive taxonomy of applications and techniques of IARS using different performance parameters. Finally, we elaborate on current issues, challenges, and future research directions in IARS; these directions we believe will pave the way for autonomous service provisioning in smart cities. 2023 John Wiley & Sons, Ltd.Qatar National Research Fund, Grant/Award Number: 13S-0206-200273 Funding informationScopu

Amplified locality‐sensitive hashing‐based recommender systems with privacy protection

With the advent of Internet of Things (IoT) age, the variety and volume of web services have been increasing at a fast speed. This often leads to users' selections for web services more complicated. Under the circumstance, a variety of methods such as collaborative filtering are adopted to deal with this challenging situation. While traditional collaborative filtering method has some shortcomings, one of which is that only centralized user‐service data are considered while distributed quality data from multiple platform are ignored. Generally, service recommendation across different platforms often involves data communication among multiple platforms, during which user privacy may be disclosed and much computational time is required. Considering these challenges, a unique amplified locality‐sensitive hashing (LSH)‐based service recommendation method, that is, SR Amplified‐LSH , is proposed in the article. SR Amplified‐LSH can guarantee a good balance between accuracy and efficiency of recommendation and user privacy information. Finally, extensive experiments deployed on WS‐DREAM dataset validate the feasibility of our proposed method

A study on securing software defined networks

Most of the IT infrastructure across the globe is virtualized and is backed by Software Defined Networks (SDN). Hence, any threat to SDN’s core components would potentially mean to harm today’s Internet and the very fabric of utility computing. After thorough analysis, this study identifies Crossfire link flooding technique as one of the lethal attacks that can potentially target the link connecting the control plane to the data plane in SDNs. In such a situation, the control plane may get disconnected, resulting in the degradation of the performance of the whole network and service disruption. In this work we present a detailed comparative analysis of the link flooding mitigation techniques and propose a framework for effective defense. It comprises of a separate controller consisting of a flood detection module, a link listener module and a flood detection module, which will work together to detect and mitigate attacks and facilitate the normal flow of traffic. This paper serves as a first effort towards identifying and mitigating the crossfire LFA on the channel that connects control plane to data plane in SDNs. We expect that further optimizations in the proposed solution can bring remarkable results

An application development framework for internet-of-things service orchestration

Application development for the Internet of Things (IoT) poses immense challenges due to the lack of standard development frameworks, tools, and techniques to assist end users in dealing with the complexity of IoT systems during application development. These challenges invoke the use of model-driven development (MDD) along with the representational state transfer (REST) architecture to develop IoT applications, supporting model generation at different abstraction levels while generating software implementation artifacts for heterogeneous platforms and ensuring loose coupling in complex IoT systems. This article proposes an IoT application development framework, named IADev, which uses attribute-driven design and MDD to address the above-mentioned challenges. This framework is composed of two major steps, including iterative architecture development using attribute-driven design and generating models to guide the transformation using MDD. IADev uses attribute-driven design to transform the requirements into a solution architecture by considering the concerns of all involved stakeholders, and then, MDD metamodels are generated to hierarchically transform the design components into the software artifacts. We evaluate IADev for a smart vehicle scenario in an intelligent transportation system to generate an executable implementation code for a real-world system. The case study experiments proclaim that IADev achieves higher satisfaction of the participants for the IoT application development and service orchestration, as compared to conventional approaches. Finally, we propose an architecture that uses IADev with the Siemens IoT cloud platform for service orchestration in industrial IoT. © 2014 IEEE

Complementing IoT services through software defined networking and edge computing : a comprehensive survey

Millions of sensors continuously produce and transmit data to control real-world infrastructures using complex networks in the Internet of Things (IoT). However, IoT devices are limited in computational power, including storage, processing, and communication resources, to effectively perform compute-intensive tasks locally. Edge computing resolves the resource limitation problems by bringing computation closer to the edge of IoT devices. Providing distributed edge nodes across the network reduces the stress of centralized computation and overcomes latency challenges in the IoT. Therefore, edge computing presents low-cost solutions for compute-intensive tasks. Software-Defined Networking (SDN) enables effective network management by presenting a global perspective of the network. While SDN was not explicitly developed for IoT challenges, it can, however, provide impetus to solve the complexity issues and help in efficient IoT service orchestration. The current IoT paradigm of massive data generation, complex infrastructures, security vulnerabilities, and requirements from the newly developed technologies make IoT realization a challenging issue. In this research, we provide an extensive survey on SDN and the edge computing ecosystem to solve the challenge of complex IoT management. We present the latest research on Software-Defined Internet of Things orchestration using Edge (SDIoT-Edge) and highlight key requirements and standardization efforts in integrating these diverse architectures. An extensive discussion on different case studies using SDIoT-Edge computing is presented to envision the underlying concept. Furthermore, we classify state-of-the-art research in the SDIoT-Edge ecosystem based on multiple performance parameters. We comprehensively present security and privacy vulnerabilities in the SDIoT-Edge computing and provide detailed taxonomies of multiple attack possibilities in this paradigm. We highlight the lessons learned based on our findings at the end of each section. Finally, we discuss critical insights toward current research issues, challenges, and further research directions to efficiently provide IoT services in the SDIoT-Edge paradigm. © 1998-2012 IEEE

Security and privacy of internet of medical things: A contemporary review in the age of surveillance, botnets, and adversarial ML

Internet of Medical Things (IoMT) supports traditional healthcare systems by providing enhanced scalability, efficiency, reliability, and accuracy of healthcare services. It enables the development of smart hardware as well as software platforms that operate on the basis of communication systems and the algorithms that process the data collected by the sensors to support decision-making. Although IoMT is involved in large-scale services provisioning in the medical paradigm; however, the resource-constrained nature of these devices makes them vulnerable to immense security and privacy issues. These vulnerabilities are not only disastrous for IoMT but threaten the whole healthcare ecosystem, which can in turn bring human lives in danger. During the past few years, threat vectors against IoMT have been evolved in terms of scalability, complexity, and diversity, which makes it challenging to detect and provide stringent defense solutions against these attacks. In this paper, we classify security and privacy challenges against different IoMT variants based on their actual usage in the healthcare domain. We provide a comprehensive attack taxonomy on the overall IoMT infrastructure comprising different device variants as well as elaborate taxonomies of security protocols to mitigate attacks against different devices, algorithms and describe their strengths and weaknesses. We also outline the security and privacy requirements for the development of novel security solutions for all the attack types against IoMT. Finally, we provide a comprehensive list of current challenges and future research directions that must be considered while developing sustainable security solutions for the IoMT infrastructure. 2022 The Author(s)Junaid Qadir is a Professor at the Qatar University in Doha, Qatar, and the Information Technology University (ITU) of Punjab in Lahore, Pakistan. He directs the IHSAN Research Lab. His primary research interests are in the areas of computer systems and networking, applied machine learning, using ICT for development (ICT4D); human-beneficial artificial intelligence; ethics of technology, artificial intelligence, and data science; and engineering education. He has published more than 150 peer-reviewed articles at various high-quality research venues including publications at top international research journals including IEEE Communication Magazine, IEEE Journal on Selected Areas in Communication (JSAC), IEEE Communications Surveys and Tutorials (CST), and IEEE Transactions on Mobile Computing (TMC). He was awarded the highest national teaching award in Pakistan-the higher education commission's (HEC) best university teacher award-for the year 2012-2013. He has obtained research grants from Facebook Research, Qatar National Research Fund, and the HEC, Pakistan. He has been appointed as ACM Distinguished Speaker for a three-year term starting from 2020. He is a senior member of IEEE and ACM.Scopu