With the exponential increase of interconnected communicating devices which make up the Internet of Things (IoT), securing the network transmission and the fifth generation (5G) systems which is the bedrock for IoT concept actualization is becoming more and more challenging. One of the major attacks which poses a great risk to data transmission is the eavesdropper (Eve) attack which occurs in both single input, single output (SISO), multiple input and multiple output (MIMO) systems. Thus, in this study, our focus is to establish a secured connection in a multiple-antenna transmission when the channel state information (CSI) of Eve is unknown to the network users. Our model comprises a secure wireless communication standard where Eve performs either optimal matched filtering (OMF) or a basic matched filtering (BMF) while the transmitting IoT node employs smart jamming strategy in order to compromise the activities of Eve. With respect to this and in attempt to realize maximum privacy, we examined the design of optimal jamming parameters. In the end, the numerical analysis of our investigation indicates that a substantial privacy advantage is achievable while utilizing only full-duplex jamming against using artificial noise from the transmitter only. However, a joint performance of both results shows a higher privacy improvement.
With the exponential increase of interconnected communicating devices which make up the Internet of Things (IoT), securing the network transmission and the fifth generation (5G) systems which is the bedrock for IoT concept actualization is becoming more and more challenging. One of the major attacks which poses a great risk to data transmission is the eavesdropper (Eve) attack which occurs in both single input, single output (SISO), multiple input and multiple output (MIMO) systems. Thus, in this study, our focus is to establish a secured connection in a multiple-antenna transmission when the channel state information (CSI) of Eve is unknown to the network users. Our model comprises a secure wireless communication standard where Eve performs either optimal matched filtering (OMF) or a basic matched filtering (BMF) while the transmitting IoT node employs smart jamming strategy in order to compromise the activities of Eve. With respect to this and in attempt to realize maximum privacy, we examined the design of optimal jamming parameters. In the end, the numerical analysis of our investigation indicates that a substantial privacy advantage is achievable while utilizing only full-duplex jamming against using artificial noise from the transmitter only. However, a joint performance of both results shows a higher privacy improvement.
In recent times, security and privacy at the physical (PHY) layer has been a major issue of several communication technologies which comprise the internet of things (IoT) and mostly, the emerging fifth-generation (5G) cellular network. The most real-world PHY security challenge stems from the fact that the passive eavesdropper's information is unavailable to the genuine source and destination (transmitter/receiver) nodes in the network. Without this information, it is difficult to optimize the broadcasting parameters. Therefore, in this research, we propose an efficient sequential convex estimation optimization (SCEO) algorithm to mitigate this challenge and improve the security of physical layer (PHY) in a three-node wireless communication network. The results of our experiments indicate that by using the SCEO algorithm, an optimal performance and enhanced convergence is achieved in the transmission. However, considering possible security challenges envisaged when a multiple eavesdropper is active in a network, we expanded our research to develop a swift privacy rate optimization algorithm for a multiple-input, multiple-output, multiple-eavesdropper (MIMOME) scenario as it is applicable to security in IoT and 5G technologies. The result of the investigation show that the algorithm executes significantly with minimal complexity when compared with nonoptimal parameters. We further employed the use of rate constraint together with self-interference of the full-duplex transmission at the receiving node, which makes the performance of our technique outstanding when compared with previous studies.
The industrial Internet of Things (IIoTs) is a key component of the fourth industrial revolution (Industry 4.0) which is faced with privacy issues as the scale and sensitivity of user and system data constantly increases. Eavesdropping attack is one of such privacy issue of the IIoT system especially when the number of transmitting antennas is increased. Thus, the focus of this article is on establishing efficient privacy in an IIoT-multiple-input–multiple-output–multiple-antenna eavesdropping communications scenario. To achieve this, a closed-form derivation for asymptotic regularized prompt privacy rate is first formulated for IIoT network system. Then, the study further examines the design of optimal jamming parameters by proposing a model referred as optimal counter-eavesdropping channel approximation technique for tackling eavesdropping attack in IIoT. The simulated performance of the proposed model clearly shows that provided that the channel coherence time is less than two times the number of transmitting nodes, a high privacy precision is achieved even without deploying any artificial noise.
As the technology and computing power advance day by day, physical layer security in wireless communications gains more importance. It allows the security of wireless communications based on information theoretical guarantees without the need for cryptography. One important practical challenge for physical layer security arises from the fact that no information about the passive eavesdroppers is available to the legitimate nodes. Without such information, optimizing the transmission parameters has always been a difficult task. In this study we aim to address various challenging aspects about this issue and propose a new perspective into the analysis of secrecy with a focus on jamming. We start from the case of eavesdropper's channel state information (CSI) known to users in a three-node single-antenna multi-subcarrier network and present an improved optimization algorithm compared to previous methods. Then we expand our horizon to the case of multiple-antenna nodes with eavesdropper's CSI unknown to users. We investigate a secure wireless communication scheme which combines two of the most effective strategies to combat eavesdropping, namely mixing information with artificial noise at the transmitter and jamming from a full-duplex receiver. While such setup has been investigated in related works, new and important insights are revealed in this study. We investigate the design of optimal jamming parameters to achieve higher secrecy.We then derive a closed-form expression for asymptotic normalized instantaneous secrecy rate of our model. Based on the results of the asymptotic analysis, we propose an alternative less complex tractable optimization problem for the design of optimal transmission parameters to achieve higher secrecy. We show that even with the optimal parameters, secrecy is compromised if Eve is able to increase her number of antennas. To address this issue, we provide a comprehensive analysis of a new scheme called anti-eavesdropping channel estimation (ANECE) which prevents Eve from acquiring accurate channel estimations. We show that the usage of such scheme, makes it extremely hard for Eve to drive secrecy to zero. Numerical analyses and simulations are presented to support the arguments made in this study.We then derive a closed-form expression for asymptotic normalized instantaneous secrecy rate of our model. Based on the results of the asymptotic analysis, we propose an alternative less complex tractable optimization problem for the design of optimal transmission parameters to achieve higher secrecy. We show that even with the optimal parameters, secrecy is compromised if Eve is able to increase her number of antennas. To address this issue, we provide a comprehensive analysis of a new scheme called anti-eavesdropping channel estimation (ANECE) which prevents Eve from acquiring accurate channel estimations. We show that the usage of such scheme, makes it extremely hard for Eve to drive secrecy to zero. Numerical analyses and simulations are presented to support the arguments made in this study.We then derive a closed-form expression for asymptotic normalized instantaneous secrecy rate of our model. Based on the results of the asymptotic analysis, we propose an alternative less complex tractable optimization problem for the design of optimal transmission parameters to achieve higher secrecy. We show that even with the optimal parameters, secrecy is compromised if Eve is able to increase her number of antennas. To address this issue, we provide a comprehensive analysis of a new scheme called anti-eavesdropping channel estimation (ANECE) which prevents Eve from acquiring accurate channel estimations. We show that the usage of such scheme makes it extremely hard for Eve to drive secrecy to zero. Numerical analyses and simulations are presented to support the arguments made in this study.
Physical layer security is a promising way to secure the wireless communications in the Internet of Things (IoT). Motivated by the fact that the limited feedback resources in the IoT network would degrade the secrecy advantage of the multiple-antenna technique, we attempt to investigate the problem of how many transmit antennas should be utilized to perform secure communications. In particular, we consider the heterogeneous IoT downlink network and design a multiuser secure transmission scheme. In this scheme, the zero-forcing beamforming technique is adopted to serve the IoT legitimate users, and the remaining spatial freedoms are utilized to send artificial noise (AN) for confusing the passive eavesdroppers. Given the secrecy outage constraints, we derive the closed-form expression for the network secrecy throughput and formulate a non-convex optimization problem with multiple parameters, e.g., the number of transmit antennas, the wiretap codes, the feedback bits allocation strategy, and the power allocation ratio between the information bearing signal and the AN. To effectively tackle this problem, we develop an optimization framework involving the block coordinate descent algorithm and the 1-D search method. Simulation results validate the effectiveness of our proposed optimization framework and show that the optimal number of transmit antennas increases as the secrecy outage constraints become stricter, or the feedback resources become scarcer.
Traditional approaches for providing confidentiality of wirelessly transmitted signals are often based on cryptographic techniques. While these techniques ensure that messages are encrypted and secured against eavesdropping, they are not sufficient to protect important transmission attributes at the physical (PHY) layer. Specifically, several elds in the headers of PHY and medium access control (MAC) frames are typically sent unencrypted to maintain proper protocol functionality (e.g., sender/receiver identification). As a result, they leak side-channel information (SCI), including payload size, frequency and phase oset, modulation and coding scheme, identities of communication nodes, frame type, transmission rate, etc. These SCI can be exploited by an adversary to launch various passive (eavesdropping) and active (jamming) attacks. To complement cryptographic techniques used at upper layers and prevent the leakage of SCI at the PHY/MAC layers, PHY-layer security techniques have been introduced. These techniques exploit the characteristics of the wireless channel along with multiple-input multiple-output (MIMO) technologies, in which multiple transmitting and receiving antennas are utilized to prevent information leakage to eavesdroppers and/or avoid jamming attacks. In particular, if the signal-to-interference-plus-noise ratio (SINR) at an adversary is lower than the one at a legitimate receiver, secure communication can be achieved through the so-called wiretap coding. MIMO systems enable the transmitter and/or the receiver to generate artificial noise, called friendly jamming (FJ), so as to reduce the SINR at the adversary without impacting the SINR at the legitimate receiver. In this dissertation, we focus on exploring the security threats to next-generation wireless systems. We develop MIMO-based PHY-layer security methods to achieve reliable and secret communications in these systems. First, we consider a broadcast channel, in which a multi-antenna transmitter (Alice) sends K confidential information signals to K legitimate receivers (Bobs) in the presence of L eavesdropping devices (Eves). Alice uses MIMO precoding to generate the information signals along with her own Tx-based friendly jamming (TxFJ). Interference at each Bob is removed via a technique called MIMO zero-forcing. This TxFJ, however, leaves an eavesdropping \vulnerability region" in the proximity of each Bob, which can be exploited by a nearby Eve. Specically, because of the high correlation in the channel state information (CSI) at a Bob and nearby Eves, the TxFJ becomes less effective in preventing eavesdropping at these Eves. We address this problem by augmenting TxFJ with receiver-based friendly jamming (RxFJ), generated by each Bob. Specifically, we allow each Bob to use self-interference suppression (SIS) techniques to transmit a friendly jamming signal while simultaneously receiving an information signal over the same channel. These SIS techniques exploit circulators to attenuate the self-interference power of RxFJ at Bobs and utilize analog/digital cancellation methods to clean out any remaining residual self-interference. Considering the resulting broadcast channel, we rst study a two-user scenario and develop a secrecy encoding scheme for constructing the signals intended to two Bobs. We characterize the corresponding achievable secrecy sum-rate and formulate an optimization problem to maximize this metric. We then extend our approach to K-user scenarios and study a power minimization problem. Particularly, in our analysis we minimize the powers allocated to information and friendly jamming signals (both TxFJ and RxFJ) while guaranteeing individual secrecy rates for various Bobs. The problem is solved for the cases when the eavesdropper's CSI (ECSI) is known or unknown (but with a known distribution). Simulations show the effectiveness of the proposed solutions. Furthermore, we discuss how to schedule transmissions when the rate requirements need to be satised on average rather than instantaneously. In low and high power regime, a scheduling algorithm that serves only the strongest receivers is shown to outperform the one that schedules all receivers. Next, we consider a single-cell massive MIMO system in which a base station (BS) with a large number of antennas transmits simultaneously to several single antenna users. The BS acquires the CSI for various receivers using uplink pilot transmissions. We demonstrate the vulnerability of the CSI estimation process to a pilot-contamination (PC) attack that aims at minimizing the sum-rate of downlink transmissions by contaminating uplink pilots. We rst study PC attacks for two downlink power allocation strategies under the assumption that the attacker knows the locations of the BS and its users. Later on, we relax this assumption and consider the case when such knowledge is probabilistic. The formulated problems are solved using stochastic optimization, Lagrangian minimization, and game-theoretic methods. A closed-form solution for a special case of the problem is obtained. Furthermore, we analyze the \achievable individual secrecy rates" under PC attacks, and provide an upper-bound on these rates. We also study this scenario without a priori knowledge of user locations at the attacker by introducing chance constraints. Another attack model is considered, where the attacker generates jamming signals in both the CSI estimation and data transmission phases by exploiting inband full-duplex techniques. Our results indicate that such attacks can degrade the throughput of a massive MIMO system by more than 50%, and reduce fairness among users significantly.
The Internet of Things (IoT) is expected to provide ubiquitous wireless machine-type communication devices and extensive information collection, resulting in an unprecedented amount of privacy and secrets exposed to the radio space. Security issues become a major restriction on the further development of IoT. However, secure transmissions in IoT are challenged by low complexity limitation and massive connectivity demand, especially by the use of short packets, which are expected to satisfy the delay requirement in ultra-reliable low-latency communications. Physical layer security can be employed without the constraints of packet length and number of connections. Nevertheless, due to the limitations of complexity, not all existing PLS techniques can be adopted in IoT. Non-orthogonal multiple access (NOMA) is a promising technique for increasing connectivity and reducing delay. Assuming an eavesdropper (Eve) is capable of the same detection capability as legitimate users, this article further exploits the inherent characteristics of NOMA to secure short-packet communications in IoT networks without introducing extra security mechanisms. Both downlink and uplink NOMA schemes are introduced to secure transmission by deliberately increasing the co-channel interference at Eve, which can be viewed as a special cooperative jamming strategy. Simulations show that in both uplink and downlink, although secrecy performance deteriorates in short-packet communications, the performance gains of NOMA over traditional orthogonal multiple access are significant. Finally, we analyze the challenges and future trends in this emerging area.