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  • 1.
    Chen, Zhe
    et al.
    Univ Elect Sci & Technol China, Sch Informat & Commun Engn, Chengdu 611731, Sichuan, Peoples R China..
    Guo, Shize
    Univ Elect Sci & Technol China, Sch Informat & Commun Engn, Chengdu 611731, Sichuan, Peoples R China..
    Wang, Jian
    Univ Elect Sci & Technol China, Sch Informat & Commun Engn, Chengdu 611731, Sichuan, Peoples R China..
    Li, Yubai
    Univ Elect Sci & Technol China, Sch Informat & Commun Engn, Chengdu 611731, Sichuan, Peoples R China..
    Lu, Zhonghai
    KTH, School of Electrical Engineering and Computer Science (EECS), Electronics, Electronic and embedded systems.
    Toward FPGA Security in IoT: A New Detection Technique for Hardware Trojans2019In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 6, no 4, p. 7061-7068Article in journal (Refereed)
    Abstract [en]

    Nowadays, field programmable gate array (FPGA) has been widely used in Internet of Things (IoT) since it can provide flexible and scalable solutions to various IoT requirements. Meanwhile, hardware Trojan (HT), which may lead to undesired chip function or leak sensitive information, has become a great challenge for FPGA security. Therefore, distinguishing the Trojan-infected FPGAs is quite crucial for reinforcing the security of IoT. To achieve this goal, we propose a clock-tree-concerned technique to detect the HTs on FPGA. First, we present an experimental framework which helps us to collect the electromagnetic (EM) radiation emitted by FPGA clock tree. Then, we propose a Trojan identifying approach which extracts the mathematical feature of obtained EM traces, i.e., 2-D principal component analysis (2DPCA) in this paper, and automatically isolates the Trojan-infected FPGAs from the Trojan-free ones by using a BP neural network. Finally, we perform extensive experiments to evaluate the effectiveness of our method. The results reveal that our approach is valid in detecting HTs on FPGA. Specifically, for the trust-hub benchmarks, we can find out the FPGA with always on Trojans (100% detection rate) while identifying the triggered Trojans with high probability (by up to 92%). In addition, we give a thorough discussion on how the experimental setup, such as probe step size, scanning area, and chip ambient temperature, affects the Trojan detection rate.

  • 2.
    Gisdakis, Stylianos
    et al.
    KTH, School of Electrical Engineering (EES), Communication Networks. Networked Systems Security Group.
    Giannetsos, Thanassis
    KTH, School of Electrical Engineering (EES), Communication Networks. Networked Systems Security Group.
    Papadimitratos, Panagiotis
    KTH, School of Electrical Engineering (EES), Communication Networks. Networked Systems Security Group.
    Security, Privacy, and Incentive Provision for Mobile Crowd Sensing Systems2016In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 3, no 5, p. 839-853, article id 7463023Article in journal (Refereed)
    Abstract [en]

    Recent advances in sensing, computing, and networking have paved the way for the emerging paradigm of mobile crowd sensing (MCS). The openness of such systems and the richness of data MCS users are expected to contribute to them raise significant concerns for their security, privacy-preservation and resilience. Prior works addressed different aspects of the problem. But in order to reap the benefits of this new sensing paradigm, we need a holistic solution. That is, a secure and accountable MCS system that preserves user privacy, and enables the provision of incentives to the participants. At the same time, we are after an MCS architecture that is resilient to abusive users and guarantees privacy protection even against multiple misbehaving and intelligent MCS entities (servers). In this paper, we meet these challenges and propose a comprehensive security and privacy-preserving architecture. With a full blown implementation, on real mobile devices, and experimental evaluation we demonstrate our system's efficiency, practicality, and scalability. Last but not least, we formally assess the achieved security and privacy properties. Overall, our system offers strong security and privacy-preservation guarantees, thus, facilitating the deployment of trustworthy MCS applications.

  • 3.
    Hossain, Mohammad Istiak
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).
    Kumar, Niroop
    KTH.
    Markendahl, Jan
    KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).
    Techno-Economic Framework for IoT Service Platform:: A Cost-Structure Aspects of IoT Service ProvisioningIn: IEEE Internet of Things Journal, ISSN 2327-4662Article in journal (Refereed)
    Abstract [en]

    A plethora of Internet of Things (IoT) platforms are available in the market today. Most of the IoT platforms are used mainly for service prototyping. Cost-efficient service scalability on any platform is still an unresolved concern that, so far, has been addressed qualitatively. A quantitative method for IoT platform economics is missing in the literature. In this paper, we propose a generic framework to address this gap. Our proposed framework covers the dimensioning of the platform's software and hardware to envisage the design, deployment, and operation cost of platform services. Then, we use the framework to perform a quantitative study of platform rollout in three platform business contexts. Our analysis shows the applicability of different deployment and platform integration choices. Our results suggest that storage and energy are the main cost drivers for platforms' hardware scalability, where the main cost driver is the intensity of the sensors' message transmission rate. Additionally, our use-case based study suggests that platform as a service (PaaS) is only beneficial for actors who have limited scale or niche market need.

  • 4.
    Li, Nan
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Xiao, Ming
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Rasmussen, Lars Kildehöj
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Spectrum Sharing With Network Coding for Multiple Cognitive Users2019In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 6, no 1, p. 230-238Article in journal (Refereed)
    Abstract [en]

    In this paper, an intelligently cooperative communication network with cognitive users is considered, where in a primary system and a secondary system, respectively, a message is communicated to their respective receiver over a packet-based wireless link. The secondary system assists in the transmission of the primary message employing network coding, on the condition of maintaining or improving the primary performance, and is granted limited access to the transmission resources as a reward. The users in both systems exploit their previously received information in encoding and decoding the binary combined packets. Considering the priority of legitimate users, a selective cooperation mechanism is investigated and the system performance based on an optimization problem is analyzed. Both the analytical and numerical results show that the condition for the secondary system accessing the licensed spectrum resource is when the relay link performs better than the direct link of the primary transmission. We also extend the system model into a network with multiple secondary users and propose two relay selection algorithms. Jointly considering the related link qualities, a best relay selection and a best relay group selection algorithm are discussed. Overall, it is found that the throughput performance can be improved with multiple secondary users, especially with more potential users cooperating in the best relay group selection algorithm.

  • 5.
    Mahmood, Aamir
    et al.
    Mid Sweden Univ, Dept Informat Syst & Technol, S-85170 Sundsvall, Sweden..
    Hossain, Aftab M M
    KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS.
    Cavdar, Cicek
    KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Radio Systems Laboratory (RS Lab).
    Gidlund, Mikael
    Mid Sweden Univ, Dept Informat Syst & Technol, S-85170 Sundsvall, Sweden..
    Energy-Reliability Aware Link Optimization for Battery-Powered IoT Devices With Nonideal Power Amplifiers2019In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 6, no 3, p. 5058-5067Article in journal (Refereed)
    Abstract [en]

    In this paper, we study cross-layer optimization of low-power wireless links for reliability-aware applications while considering both the constraints and the nonideal characteristics of the hardware in Internet-of-Things (IoT) devices. Specifically, we define an energy consumption (EC) model that captures the energy cost-of transceiver circuitry, power amplifier (PA), packet error statistics, packet overhead, etc.-in delivering a useful data bit. We derive the EC models for an ideal and two realistic nonlinear PA models. To incorporate packet error statistics, we develop a simple, in the form of elementary functions, and accurate closed-form packet error rate approximation in Rayleigh block-fading. Using the EC models, we derive energy-optimal yet reliability and hardware compliant conditions for limiting unconstrained optimal signal-to-noise ratio (SNR), and payload size. Together with these conditions, we develop a semianalytic algorithm for resource-constrained IoT devices to jointly optimize parameters on physical (modulation size, SNR) and medium access control (payload size and the number of retransmissions) layers in relation to link distance. Our results show that despite reliability constraints, the common notion-higherorder M-ary modulations are energy optimal for short-range communication-prevails, and can provide up to 180% lifetime extension as compared to often used OQPSK modulation in IoT devices. However, the reliability constraints reduce both their range and the energy efficiency, while nonideal traditional PA reduces the range further by 50% and diminishes the energy gains unless a better PA is used.

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