The IoT technology allows many types of personal data to be measured by many kinds of devices and sensors, and to be sent over the Internet for various applications. However, this data transmission has to be secure and the privacy of the users should ideally be preserved. In this work, we propose a SRAM PUF-based privacy-preserving IoT protocol for cloud storage based on an existing protocol from the literature. Proposals are made to increase the supply chain security of the PUF construction used by a device, to extend the secure lifetime of this device by increasing the number of keys it may generate and avoiding reboot-based attacks, and to allow a PUF construction to be used for different applications. These proposals only require changes on the device enrollment and on the master key generation procedure, leaving the PUF construction, the fuzzy extractor construction and the cryptographic key derivation unchanged. Benefits and limitations of this new protocol are evaluated and security objectives achieved with these proposals are analyzed.

Physical-layer security (PLS) has the potential to strongly enhance the overall system security as an alternative to or in combination with conventional cryptographic primitives usually implemented at higher network layers. Secret-key generation relying on wireless channel reciprocity is an interesting solution as it can be efficiently implemented at the physical layer of emerging wireless communication networks, while providing information-theoretic security guarantees. In this article, we investigate and compare the secret-key capacity based on the sampling of the entire complex channel state information (CSI) or only its envelope, the received signal strength (RSS). Moreover, as opposed to previous works, we take into account the fact that the eavesdropper's observations might be correlated and we consider the high signal-to-noise ratio (SNR) regime where we can find simple analytical expressions for the secret-key capacity. As already found in previous works, we find that RSS-based secret-key generation is heavily penalized as compared to CSI-based systems. At high SNR, we are able to precisely and simply quantify this penalty: a halved pre-log factor and a constant penalty of about 0.69 bit, which disappears as Eve's channel gets highly correlated.

Currently the industry moves to smaller process nodes even if the cost for yielding large dies continues to increase, moving to the 5nm and even 3nm nodes. Hence a chiplet-based design has been initiated and quickly gain attention from industry, academia and government agencies. This cutting edge approach became advantageous to break down a large die into smaller chiplets in order to improve yield and binning. In order to exploit this new approach the interconnect fabric connecting the nodes of the entire system should be of high importance to enable the properly distribution of the data. Each individual chiplet may contain its own local Network on Chip (NoC), which operates for intra-chiplet traffic. However the communication over chiplet-based systems is complicated enough, due to various routing algorithms and NoC topologies and an alternative solution is needed. In this paper we introduce an SDNoC(Software Define Network on Chip)-based communication protocol for chiplet-based systems, called MicroLET, which consists of a flexible and modular SDNoC architecture and 3 main phases: Handshake, Network Monitoring, Routing. An implementation of the SDNoC architecture and an evaluation of the proposed routing algorithm compared to the XY and the Odd-Even algorithms within different traffic scenarios is presented. Through the evaluation of the MicroLET protocol, it is proven that it could be a good candidate for the future chiplet-based systems.

In this work, we implement an identity-based Transport Layer Security (ID-TLS) protocol and integrate it on scalable multiprocessor system-on-chip (MPSoC), namely Cloud-of-Chips (CoC), in order to secure the SDN communication on this platform. We select two identity-based encryption schemes that are more likely to meet the performance and resource constraints on the target platform. The schemes are Sakai-Kasahara's identity-based encryption (SK-IBE) and the optimized identity-based encryption (OIBE) for lightweight devices by Guo et al. The results assert that both the schemes have their computation vs storage trade-off. The SK-IBE algorithm is significantly more computationally efficient than its OIBE counterpart while SK-IBE uses around 30 percent more memory than OIBE. However, the performance results of ID-TLS favor SK-IBE over OIBE. Finally, ID-TLS is integrated in the existing Open Flow switch and controller implementations. This brings us to a fully functional and secure ID-TLS implementation on CoC, keeping the platform constraints in consideration.

In recent years, Multi-Processor System-on-Chips (MPSoCs) are widely deployed in safety-critical embedded systems. The Cloud-of-Chips (CoC) is a scalable MPSoC architecture comprised of a large number of interconnected Integrated Circuits (IC) and Processing Clusters (PC) destined for critical systems. While many researches have focused on addressing the hardware issues of MPSoCs, the communication over them has not been very well explored. Following the SDN concept, we propose a new protocol in order to secure the communication and efficiently manage the routing within the CoC. The SSPSoC includes a private key derivation phase, a group key agreement (GKA) phase, and a data exchange phase in order to ensure that basic security primitives are preserved and provide secure communication. Furthermore, a network of 1-30 nodes is set in order to validate the proposed protocol and measure the network performance and memory consumption of the proposed protocol.

A symmetric group key agreement protocol enables the group members to derive a shared session key for secure communication among them, while an asymmetric one facilitates security to any communication from outside, without adding outsiders into the group. In this paper, we propose a twofold group key agreement protocol which addresses the need of a shared symmetric key among insider members in a group and an asymmetric key pair for any unrestricted sender. In particular, we look forward for a solution to provide secure communication among multiple processing clusters (PCs) actively running on an integrated circuit (IC). The proposed protocol offers a lightweight symmetric encryption for intra zone communication and a public key encryption for inter zone communication taking most advanced security issues into account.

In this paper, it is proposed to use group communication cryptographic protocols as a new security paradigm. This new paradigm aims at redesigning the security of small cell communications over an insecure mobile backhaul. The Heterogeneous Networks are positioned and a review of the current security mechanisms and their flaws is provided. A security and performance comparison between the current mechanisms and our proposition is developed, and this comparison leads to new development opportunities to increase the security of the overall backhauling.

In this paper, an investigation of the security of the WLAN access points is conducted with a special focus on their integration into 4G LTE-Advanced networks. Indeed, the points of access will be physically accessible to the customers or the workers from enterprises and, thus, corruption is possible and will affect or compromise the underlying LAN architecture. For that reason, the paper will focus, through a threat analysis, on the possible attacks and manipulation that a corrupted base station could execute. The paper presents the foundation to counteract these threats.

Cognitive radios impose challenges on the design of efficient signal detectors, including wide bandwidth sensing and large dynamic range support. The recently considered compressed sensing theory helps in relaxing the constraints on the design of the analog front-end. The maximum likelihood method introduced here is computationally simple since it does not require a signal reconstruction, unlike most methods introduced in the current literature. Moreover, the metric is optimum, works for any modulation scheme and is independent of the emitted signal knowledge and the number of occupied bands. The results are supported with Matlab simulations, a statistical study is performed and the probabilities of misdetection and false alarm are plotted for different scenarios, proving the efficiency of the estimator in a range of plausible SNRs and subsampling factors.

In cognitive radios systems, the sparse assigned frequency bands are opened to secondary users, provided that the aggregated interferences induced by the secondary transmitters on the primary receivers are negligible. In this paper, a decentralized Q-learning power allocation algorithm is proposed to maximize the Signal on Interference-plus-Noise Ratio (SINR) at the secondary receivers while meeting the primary protection constraint. Numerical simulations allow to compare the performance of the proposed algorithm with the performance of the optimal centralized power allocation scheme in the scenario of multiple independent secondary cells located on the border of a primary network protection contour. The impact of the definition of the learning algorithm cost function on the secondary user fairness and the system performance is discussed. The optimal execution frequency of the algorithm is obtained and different strategies for the exploration of new solutions are compared.

We consider the sensing of the frequency spectrum for cognitive radios, based on energy detection. It has been shown that the sensing reliability can be improved by using several cooperating cognitive radios that exchange their individual sensing information to a coordinator node through specific control channels. The coordinator node then combines the received information in order to make a decision about the primary network presence. In this paper, we compute analytically the probability density functions of the noise coming from the two-bits non-uniform quantization of the energy measure at each node and from the non-uniform bit flipping on the control channel. The quantization step and the bit flipping probabilities are selected to reduce the impact of the error. A new optimal fusion rule is proposed that takes into account the control channel noise distribution. Numerical simulations show that this new scheme outperforms the Maximum Ratio Combining scheme when different false alarm probabilities are used by the nodes.

In cognitive radio systems, the sparse assigned frequency bands are opened to secondary users. We consider the sensing of the frequency spectrum for cognitive radios, based on energy detection. It has been shown that the sensing reliability can be improved in the presence of fading by using several cooperating cognitive radios that exchange their individual sensing information to a coordinator node. The coordinator node combines the received information in order to make a decision about the primary network presence. The primary network sensing times used by the cognitive nodes should be chosen high enough to ensure the correct detection of the primary emitter but low enough so that the nodes still have enough time to communicate. In this paper, we propose a decentralized Q-Learning algorithm to allocate the sensing times of the cognitive radios in a way that maximizes the throughputs of the radios. A rigorous proof of the convergence of the proposed algorithm is provided. Numerical results show that it converges faster to the same throughputs as those obtained with a reference algorithm.

Compared to classical spatial MIMO wireless systems, cross-polarized MIMO systems are an interesting way to reduce equipment size while still maintaining low inter-antenna correlation. In this paper, the time-variation of the polarization of the received waves is investigated. In this scenario, a theoretical formulation is proposed in order to obtain the parameters of the elliptical polarization, based on the signals received on three perpendicularly polarized antennas. A measurement campaign has been performed in an indoor-to-indoor scenario and at a frequency of 3.6 GHz. Different measurement positions are considered in a Line-Of-Sight (LOS) and a Non-Line-of-Sight (NLOS) scenario. Based on these measurements and the proposed theoretical formulation, the time-variation of the parameters describing the polarization ellipse is analyzed and a time-variant statistical model is proposed.

In cognitive radios systems, the sparse assigned frequency bands are opened to secondary users. We consider the sensing of the frequency spectrum for cognitive radios, based on energy detection. It has been shown that the sensing reliability can be improved by using several cooperating cognitive radios that exchange their individual sensing information to a coordinator node. The coordinator node combines the received information in order to make a decision about the primary network presence. In this paper, we propose a decentralized Q-learning algorithm to share the sensing time among the cognitive radios in a way that maximize the throughputs of the radios. Numerical results show the convergence of the proposed algorithm and allow to discuss the exploration strategy, the choice of the cost function and the frequency of execution of the algorithm.

To improve the performance of a DVB-S2 communication channel, it is necessary to remove the non-linear interferences induced by the power amplifier. Due to the presence of filters in the channel, this non-linear interference is also interference with memory. One of the most used techniques to cancel out the interferences in this case is the order p compensation. The order p compensation can be mathematically described as a recursive algorithm. The non- linear interference is supposed to be smaller after each step of the algorithm. However this is not always the case and it is necessary to define upper bounds on the system to ensure convergence of the algorithm. Upper bounds were already defined for general nonlinear systems, but are however very inaccurate for the case of a DVB-S2 communication channel. In this paper, we will present two new methods to refine these upper bounds.

Cognitive radios have been introduced as a dynamic way to share the frequency spectrum within wireless networks. After sensing its environment to discover the available frequency resources, a cognitive network allocates the locally available carriers among its nodes, under the constraint of negligible interference on licensed operators. The allocation, based on partial knowledge of the network parameters, must be optimized in order to provide maximum rates in the cognitive network. In addition, having a stable allocation reduces the control traffic inherent in dynamic networks. This paper presents a new and fast iterative way to allocate the available carriers, that reduces the control traffic and provides fairness at the same time. Using the properties of a proportionally fair objective function, we fasten the optimum search in the space of possible allocations, and reach that optimum with no approximation. Numerical results show that the proposed iterative algorithm is less complex than an analytical solution in usual dynamic carrier allocation scenarios.

Polarized MIMO systems are an efficient solution for reducing inter-antenna correlation while maintaining compact terminal size. In this paper, a time-variant statistical channel model is proposed for tri-polarized antenna systems. The model is based on a coherent and a scattered component, where each component includes inter-channel correlation and cross-polar discriminations. The temporal variations of the channel are separated in slow and fast channel variations. A measurement campaign has been performed at 3.6 GHz to parameterize the model, in both static and mobile cases. A variant of the variogram technique has been adopted for extracting the slow-varying channel parameters. Experimental results are investigated and presented. The Doppler spectrum of the fast channel variations show fundamental differences between the static case and the mobile case. Finally, it is explained how the proposed model can be generated.

We consider the sensing of the frequency spectrum based on energy detection for cognitive radios. It has been shown that the reliability of the sensing can be improved by using several cooperating cognitive radios. In such a network, the cognitive nodes exchange their individual sensing information to a coordinator node through specific control channels. The coordinator node then combines the received sensing informations in order to make a decision about the primary network presence. In this paper, we assess the impact of the noise coming from the quantization of the energy measure at each node and from the imperfect communication on the control channels. We also propose two complementary approaches to compensate for the noise: the system designer can firstly reduce the noise impact by using an energy coding technique that smartly shares out the bit error probabilities and secondly compensate for the remaining noise by designing a new soft metric fusion rule at the coordinator node. Numerical simulations show that this new scheme significantly improves the performance compared to the MRC scheme in the presence of control transmission noise.

Compared to classical spatial MIMO wireless systems, cross-polarized MIMO systems are an interesting way to reduce equipment size while reducing the inter-antenna correlation. Cross-Polar Discrimination (XPD) and Co-Polar Ratio (CPR) are two important parameters describing multi-polarized channels. In this paper, the behavior of these parameters is investigated for different observation scales. A measurement campaign has been performed in both Outdoor-to-Indoor and Indoor-to-Indoor scenarios, at a frequency of 3.5GHz. Small-scale variations of XPD and CPR are analyzed in different spatial positions. The distance-related and large-scale variations of XPD and CPR are also investigated and a model is deduced.

Cognitive radios are devices capable of sensing a large range of frequencies in order to detect the presence of primary networks and reuse their bands when they are not occupied. Due to the large spectrum to be sensed and the high power signal dynamics, low-cost implementations of the analog front-ends leads to imperfections. Two of them are studied in this paper: IQ imbalance and sampling clock offset (SCO). Based on a mathematical system model, we study analytically the impact of the two imperfections on the sensing performance of the energy detector and of the cyclostationarity detector. We show that the IQ imbalance does not impact the performance of the two detectors, and that the SCO only impacts significantly the performance of the cyclostationarity detector.

The latest developments and experimentation in wireless ad-hoc networks show that their use might provide a reliable coverage extension to cellular networks. The integration between 3rd Generation/4th Generation (3G/4G) and ad-hoc networks may offer a great number of benefits in term of deployment cost, accessibility, peer-to-peer (P2P) traffic redirection, etc. While the Open Systems Interconnection (OSI) reference model advocates for a clear separation of routing, transmission and physical layers, in this paper we show that an effective routing algorithm requires knowledge and constructive interaction between these layers. More precisely, we propose the use of a new routing algorithm, derived from the Ad-Hoc On-Demand Distance Vector (AODV) algorithm, based on the physical aspects of the wireless medium and optimized for indoor transmissions. Our results emphasize the possibility of a reliable cellular coverage extension in indoor environments, on the basis of a beneficial cross-layer interaction between routing, power control, transmission, and propagation.

info:eu-repo/semantics/published