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  • 1.
    Bera, Samaresh
    et al.
    Computer Science and Engineering Department, Indian Institute of Technology, Kharagpur, 721302, India..
    Misra, Sudip
    Computer Science and Engineering Department, Indian Institute of Technology, Kharagpur, 721302, India..
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Software-Defined Networking for Internet of Things: a Survey2017In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 4, no 6, p. 1994-2008Article in journal (Refereed)
    Abstract [en]

    Internet of things (IoT) facilitates billions of devices to be enabled with network connectivity to collect and exchange real-time information for providing intelligent services. Thus, IoT allows connected devices to be controlled and accessed remotely in the presence of adequate network infrastructure. Unfortunately, traditional network technologies such as enterprise networks and classic timeout-based transport protocols are not capable of handling such requirements of IoT in an efficient, scalable, seamless, and cost-effective manner. Besides, the advent of software-defined networking (SDN) introduces features that allow the network operators and users to control and access the network devices remotely, while leveraging the global view of the network. In this respect, we provide a comprehensive survey of different SDN-based technologies, which are useful to fulfill the requirements of IoT, from different networking aspects – edge, access, core, and data center networking. In these areas, the utility of SDN-based technologies is discussed, while presenting different challenges and requirements of the same in the context of IoT applications. We present a synthesized overview of the current state of IoT development. We also highlight some of the future research directions and open research issues based on the limitations of the existing SDN-based technologies.

  • 2.
    Cai, Hongming
    et al.
    School of Software, Shanghai Jiao Tong University.
    Xu, Boyi
    College of Economics and Management, Shanghai Jiao Tong University.
    Jiang, Lihong
    School of Software, Shanghai Jiao Tong University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    IoT-Based Big Data Storage Systems in Cloud Computing: Perspectives and Challenges2017In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 4, no 1, p. 75-87, article id 7600359Article in journal (Refereed)
    Abstract [en]

    Internet of Things (IoT) related applications have emerged as an important field for both engineers and researchers, reflecting the magnitude and impact of data-related problems to be solved in contemporary business organizations especially in cloud computing. This paper first provides a functional framework that identifies the acquisition, management, processing and mining areas of IoT big data, and several associated technical modules are defined and described in terms of their key characteristics and capabilities. Then current research in IoT application is analyzed, moreover, the challenges and opportunities associated with IoT big data research are identified. We also report a study of critical IoT application publications and research topics based on related academic and industry publications. Finally, some open issues and some typical examples are given under the proposed IoT-related research framework

  • 3.
    Chen, Jialu
    et al.
    Shanghai Key Laboratory of Trustworthy Computing, East China Normal University, Shanghai, China.
    Zhou, Jun
    Shanghai Key Laboratory of Trustworthy Computing, East China Normal University, Shanghai, China.
    Cao, Zhenfu
    Shanghai Key Laboratory of Trustworthy Computing, East China Normal University, Shanghai, China.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Computer Science and Technology, Fuzhou University, China.
    Dong, Xiaolei
    Shanghai Key Laboratory of Trustworthy Computing, East China Normal University, Shanghai, China..
    Choo, Kim-Kwang Raymond
    Department of Information Systems and Cyber Security, University of Texas at San Antonio, San Antonio, TX, USA.
    Lightweight Privacy-preserving Training and Evaluation for Discretized Neural Networks2019In: IEEE Internet of Things Journal, ISSN 2327-4662Article in journal (Refereed)
    Abstract [en]

    Machine learning, particularly the neural network, is extensively exploited in dizzying applications. In order to reduce the burden of computing for resource-constrained clients, a large number of historical private datasets are required to be outsourced to the semi-trusted or malicious cloud for model training and evaluation. To achieve privacy preservation, most of the existing work either exploited the technique of public key fully homomorphic encryption (FHE) resulting in considerable computational cost and ciphertext expansion, or secure multiparty computation (SMC) requiring multiple rounds of interactions between user and cloud. To address these issues, in this paper, a lightweight privacy-preserving model training and evaluation scheme LPTE for discretized neural networks is proposed. Firstly, we put forward an efficient single key fully homomorphic data encapsulation mechanism (SFH-DEM) without exploiting public key FHE. Based on SFH-DEM, a series of atomic calculations over the encrypted domain including multivariate polynomial, nonlinear activation function, gradient function and maximum operations are devised as building blocks. Furthermore, a lightweight privacy-preserving model training and evaluation scheme LPTE for discretized neural networks is proposed, which can also be extended to convolutional neural network. Finally, we give the formal security proofs for dataset privacy, model training privacy and model evaluation privacy under the semi-honest environment and implement the experiment on real dataset MNIST for recognizing handwritten numbers in discretized neural network to demonstrate the high efficiency and accuracy of our proposed LPTE.

  • 4.
    Derhamy, Hasan
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Software Architectural Style for Industrial Internetof ThingsIn: IEEE Internet of Things Journal, ISSN 2327-4662Article in journal (Refereed)
    Abstract [en]

    As society has progressed through periods of evolutionand revolution, technology has played a key role as anenabler. In the same manner that mechanical machines of the1800’s drove the industrial revolution, now digitalized machinesare driving another industrial revolution. With the recognitionof a fourth industrial revolution the Industry 4.0 initiative wasfounded in Germany in 2011. One of the drivers of Industry4.0 is the Industrial Internet of Things. The Internet of Thingsis a natural step as computing ubiquity and interconnectednessbecome more widely present. Add to this intelligence, delegationand human orientation and the result is software intensiveengineering at almost all layers (excluding the physical andhuman layers). Software development is a competency in communications,information systems, computer science, softwareand computer systems engineering and electrical and electronicengineering. Software solutions are becoming more distributed,not only over processes, but over heterogeneous computing platformsand business domains. These platforms could be physicallyseparated over large distances, or highly mobile platforms withvarying security requirements. All these requirements introducecomplexity on a scale previously unseen in the software industry.

  • 5.
    Derhamy, Hasan
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Eliasson, Jens
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Delsing, Jerker
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    IoT Interoperability: On-demand and low latency Transparent Multi-protocol Translator2017In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 4, no 5, p. 1754-1763Article in journal (Refereed)
    Abstract [en]

    In the Industrial Internet of Things there is a clear need for a high level of interoperability between independently developedsystems, often from different vendors. Traditional methods of interoperability including protocol gateways and adapters, are often usedat the network layer. Recent work on application interoperability has emphasized the use of middleware or protocol proxy/gateway.However, middleware tends to move the interoperability problem rather than solving it, and there are scalability issues with increasingthe number of proxies; re-configuration effort, and required bandwidth and processing overheads.This paper proposes a secure, on-demand and transparent protocol translator for the Industrial Internet of Things. Targeting thechallenge of interoperability between IP-based communication protocols, the paper analyses current solutions and develops a set ofrequirements to be met by IoT protocol interoperability. The proposed protocol translator is not a middleware, it is a SOA-basedparticipant, it is used on-demand when needed, it does not introduce design time dependencies, it operates transparently, it supportslow-latency, and it is secured through the use of Arrowhead authorization and authentication.

  • 6.
    Esfahani, Alireza
    et al.
    Instituto de Telecomunicações-Pólo de Aveiro, Aveiro, Portugal.
    Mantas, Georgios
    Instituto de Telecomunicações-Pólo de Aveiro, Aveiro, Portugal.
    Matischek, Rainer
    Infineon Technologies Austria AG Graz, Austria.
    Saghezchi, Firooz B.
    University of Aveiro, Aveiro, Portugal.
    Rodriguez, Jonathan
    University of Aveiro, Aveiro, Portugal.
    Bicaku, Ani
    University of Applied Sciences, Burgenland, Eisenstadt, Austria.
    Maksuti, Silia
    University of Applied Sciences, Burgenland, Eisenstadt, Austria.
    Tauber, Markus
    University of Applied Sciences, Burgenland, Eisenstadt, Austria.
    Schmittner, Christoph
    Austrian Institute of Technology, Wien, Austria.
    Joaquim, Bastos
    Instituto de Telecomunicações-Pólo de Aveiro, Aveiro, Portugal.
    A Lightweight Authentication Mechanism for M2M Communications in Industrial IoT Environment2019In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 6, no 1, p. 288-296Article in journal (Refereed)
    Abstract [en]

    In the emerging Industrial IoT era, Machine-to-Machine (M2M) communication technology is considered as a key underlying technology for building Industrial IoT environments where devices (e.g., sensors, actuators, gateways) are enabled to exchange information with each other in an autonomous way without human intervention. However, most of the existing M2M protocols that can be also used in the Industrial IoT domain provide security mechanisms based on asymmetric cryptography resulting in high computational cost. As a consequence, the resource-constrained IoT devices are not able to support them appropriately and thus, many security issues arise for the Industrial IoT environment. Therefore, lightweight security mechanisms are required for M2M communications in Industrial IoT in order to reach its full potential. As a step towards this direction, in this paper, we propose a lightweight authentication mechanism, based only on hash and XOR operations, for M2M communications in Industrial IoT environment. The proposed mechanism is characterized by low computational cost, communication and storage overhead, while achieving mutual authentication, session key agreement, device’s identity confidentiality, and resistance against the following attacks: replay attack, man-in-the-middle attack, impersonation attack, and modification attack.

  • 7.
    Kumar Das, Ashok
    et al.
    Center for Security, Theory and Algorithmic Research, International Institute of Information Technology, Hyderabad, India.
    Wazid, Mohammad
    Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Karnataka, India.
    Kumar, Neeraj
    Department of Computer Science and Engineering, Thapar University, Patiala, India.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Rodrigues, Joel J. P. C.
    National Institute of Telecommunications (Inatel), Brazil; Instituto de Telecomunicações, Portugal; University of Fortaleza (UNIFOR), Brazil..
    Biometrics-Based Privacy-Preserving User Authentication Scheme for Cloud-Based Industrial Internet of Things Deployment2018In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 5, no 6, p. 4900-4913Article in journal (Refereed)
    Abstract [en]

    Due to the widespread popularity of Internet-enabled devices, Industrial Internet of Things (IIoT) becomes popular in recent years. However, as the smart devices share the information with each other using an open channel, i.e., Internet, so security and privacy of the shared information remains a paramount concern. There exist some solutions in the literature for preserving security and privacy in IIoT environment. However, due to their heavy computation and communication overheads, these solutions may not be applicable to wide category of applications in IIoT environment. Hence, in this paper, we propose a new Biometric-based Privacy Preserving User Authentication (BP2UA) scheme for cloud-based IIoT deployment. BP2UA consists of strong authentication between users and smart devices using pre-established key agreement between smart devices and the gateway node. The formal security analysis of BP2UA using the well-known ROR model is provided to prove its session key security. Moreover, an informal security analysis of BP2UA is also given to show its robustness against various types of known attacks. The computation and communication costs of BP2UA in comparison to the other existing schemes of its category demonstrate its effectiveness in the IIoT environment. Finally, the practical demonstration of BP2UA is also done using the NS2 simulation.

  • 8.
    Lin, Di
    et al.
    School of Information and Software Engineering, University of Electronic Science and Technology of China.
    Tang, Yu
    School of Information and Software Engineering, University of Electronic Science and Technology of China.
    Yao, Yuanzhe
    School of Information and Software Engineering, University of Electronic Science and Technology of China.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    User-priority based power control over the D2D assisted Internet of vehicles for mobile health2017In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 4, no 3, p. 824-831, article id 7858717Article in journal (Refereed)
    Abstract [en]

    A device-to-device (D2D) assisted cellular network is pervasive to support ubiquitous healthcare applications, since it is expected to bring the significant benefits of improving user throughput, extending the battery life of mobiles, etc. However, D2D and cellular communications in the same network may cause cross-tier interference (CTI) to each other. Also a critical issue of using D2D assisted cellular networks under a healthcare scenario is the electromagnetic interference (EMI) caused by RF transmission, and a high level of EMI may lead to a critical malfunction of medical equipments. In consideration of CTI and EMI, we study the problem of optimizing individual channel rates of the mobile users in different priorities (different levels of emergency) within the Internet of vehicles for mobile health, and propose an algorithm of controlling the transmit power to solve the above-mentioned problem under a gametheoretical framework. Numerical results show that the proposed algorithm can converge linearly to the optimum, while ensuring an allowable level of EMI on medical equipments.

  • 9.
    Paniagua, Cristina
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Eliasson, Jens
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Delsing, Jerker
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Efficient Device-to-Device Service Invocation Using Arrowhead Orchestration2019In: IEEE Internet of Things Journal, ISSN 2327-4662Article in journal (Refereed)
    Abstract [en]

    The Internet of Things (IoT) enables interaction from real-world physical objects using sensors to the virtual world of computers and the Internet. The use of service-oriented architecture (SOA) is one step in the creation of basic and complex interactions between several sensors and actuators. However, the use of SOA-enabled technologies alone does not meet all requirements of how sensor and actuator systems could be integrated to create distributed monitoring and control applications. The centralized, traditional method of communication in wireless sensor networks via a gateway presents drawbacks that have to be addressed; device-to-cloud communication adds higher latency and higher power consumption and is less robust than the device-to-device communication approach. Moreover, all these characteristics reduce the scalability of the network, thus limiting the use of IoT in the industry. In this paper, the proposed method utilizes the Arrowhead framework orchestration system to generate service composition within a (wireless) network formed by IoT devices. The aim is to achieve efficient device-to-device service invocation to reduce the drawbacks of today's widely used device-to-cloud approach. The method in this paper performs efficient service composition for industrial IoT, including mapping SOA service composition in very small resource-constrained devices using the Arrowhead orchestration. The results presented in this paper at the service level can increase performance and robustness in fog computing on resource-constrained devices.

  • 10.
    Sun, Gang
    et al.
    Key Lab of Optical Fiber Sensing and Communications (Ministry of Education), University of Electronic Science and Technology of China, Chengdu, China.
    Xu, Zhu
    Key Lab of Optical Fiber Sensing and Communications (Ministry of Education), University of Electronic Science and Technology of China, Chengdu, China.
    Yu, Hongfang
    Key Lab of Optical Fiber Sensing and Communications (Ministry of Education), University of Electronic Science and Technology of China, Chengdu, China.
    Chen, Xi
    School of Computer Science and Technology, Southwest Minzu University, Chengdu, China.
    Chang, Victor
    School of Computing & Digital Technologies, Teesside University, Middlesbrough, UK.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Low-latency and Resource-efficient Service Function Chaining Orchestration in Network Function Virtualization2019In: IEEE Internet of Things Journal, ISSN 2327-4662Article in journal (Refereed)
    Abstract [en]

    Recently, network function virtualization (NFV) has been proposed to solve the dilemma faced by traditional networks and to improve network performance through hardware and software decoupling. The deployment of the service function chain (SFC) is a key technology that affects the performance of virtual network function (VNF). The key issue in the deployment of SFCs is proposing effective algorithms to achieve efficient use of resources. In this paper, we propose a service function chain deployment optimization (SFCDO) algorithm based on a breadth-first search (BFS). The algorithm first uses a BFS based algorithm to find the shortest path between the source node and the destination node. Then, based on the shortest path, the path with the fewest hops is preferentially chosen to implement the SFC deployment. Finally, we compare the performances with the greedy and simulated annealing (G-SA) algorithm. The experiment results show that the proposed algorithm is optimized in terms of end-to-end delay and bandwidth resource consumption. In addition, we also consider the load rate of the nodes to achieve network load balancing.

  • 11.
    Wazid, Mohammad
    et al.
    Center for Security, Theory and Algorithmic Research, International Institute of Information Technology, Hyderabad.
    Das, Ashok Kumar
    Center for Security, Theory and Algorithmic Research, International Institute of Information Technology, Hyderabad.
    Khan, Muhammad Khurram
    Center of Excellence in Information Assurance, King Saud University, Riyadh.
    Al-Dhawailie Al-Ghaiheb, Abdulatif
    Clinical Pharmacy Department, College of Pharmacy, King Saud University, Riyad.
    Kumar, Neeraj
    Department of Computer Science and Engineering, Thapar University.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Secure Authentication Scheme for Medicine Anti-Counterfeiting System in IoT Environment2017In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 4, no 5, p. 1634-1646Article in journal (Refereed)
    Abstract [en]

    A counterfeit drug is a medication or pharmaceutical product which is manufactured and made available on the market to deceptively represent its origin, authenticity and effectiveness, etc., and causes serious threats to the health of a patient. Counterfeited medicines have an adverse effect on the public health and cause revenue loss to the legitimate manufacturing organizations. In this paper, we propose a new authentication scheme for medicine anti-counterfeiting system in the Internet of Things environment which is used for checking the authenticity of pharmaceutical products (dosage forms). The proposed scheme utilizes the near field communication (NFC) and is suitable for mobile environment, which also provides efficient NFC update phase. The security analysis using the widely accepted real-or-random model proves that the proposed scheme provides the session key security. The proposed scheme also protects other known attacks which are analyzed informally. Furthermore, the formal security verification using the broadly accepted automated validation of Internet security protocols and applications tool shows that the proposed scheme is secure. The scheme is efficient with respect to computation and communication costs, and also it provides additional functionality features when compared to other existing schemes. Finally, for demonstration of the practicality of the scheme, we evaluate it using the broadly accepted NS2 simulation

  • 12.
    Wazid, Mohammad
    et al.
    Cyber Security and Networks Lab, Innopolis University, Innopolis, Russian Federation.
    Kumar Das, Ashok
    Center for Security, Theory and Algorithmic Research, International Institute of Information Technology, Hyderabad, India.
    Kumar, Neeraj
    Department of Computer Science and Engineering, Thapar University, Patiala, India.
    Vasilakos, Athanasios
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Rodrigues, Joel J. P. C.
    National Institute of Telecommunications (Inatel), Brazil; Instituto de Telecomunicações, Portugal; University of Fortaleza (UNIFOR), Brazil.
    Design and Analysis of Secure Lightweight Remote User Authentication and Key Agreement Scheme in Internet of Drones Deployment2019In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 6, no 2, p. 3572-3584, article id 8581510Article in journal (Refereed)
    Abstract [en]

    The Internet of Drones (IoD) provides a coordinated access to Unmanned Aerial Vehicles (UAVs) that are referred as drones. The on-going miniaturization of sensors, actuators, and processors with ubiquitous wireless connectivity makes drones to be used in a wide range of applications ranging from military to civilian. Since most of the applications involved in the IoD are real-time based, the users are generally interested in accessing real-time information from drones belonging to a particular fly zone. This happens if we allow users to directly access real-time data from flying drones inside IoD environment and not from the server. This is a serious security breach which may deteriorate performance of any implemented solution in this IoD environment. To address this important issue in IoD, we propose a novel lightweight user authentication scheme in which a user in the IoD environment needs to access data directly from a drone provided that the user is authorized to access the data from that drone. The formal security verification using the broadly-accepted Automated Validation of Internet Security Protocols and Applications (AVISPA) tool along with informal security analysis show that our scheme is secure against several known attacks. The performance comparison demonstrates that our scheme is efficient with respect to various parameters, and it provides better security as compared to those for the related existing schemes. Finally, the practical demonstration of our scheme is done using the widely-accepted NS2 simulation.

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