5G is expected to serve completely heterogeneous scenarios where devices with low or high software and hardware complexity will coexist. This entails a security challenge because low complexity devices such as IoT sensors must still have secrecy in their communications. This project proposes tools to maximize the secrecy rate in a scenario with legitimate users and eavesdroppers considering: i) the limitation that low complexity users have in computational power and ii) the eavesdroppers? unwillingness to provide their channel state information to the base station. The tools have been designed based on the physical layer security field and solve the resource allocation from two different approaches that are suitable in different use cases: i) using convex optimization theory or ii) using classification neural networks. Results show that, while the convex approach provides the best secrecy performance, the learning approach is a good alternative for dynamic scenarios or when wanting to save transmitting power.
5G is expected to serve completely heterogeneous scenarios where devices with low or high software and hardware complexity will coexist. This entails a security challenge because low complexity devices such as IoT sensors must still have secrecy in their communications. This project proposes tools to maximize the secrecy rate in a scenario with legitimate users and eavesdroppers considering: i) the limitation that low complexity users have in computational power and ii) the eavesdroppers? unwillingness to provide their channel state information to the base station. The tools have been designed based on the physical layer security field and solve the resource allocation from two different approaches that are suitable in different use cases: i) using convex optimization theory or ii) using classification neural networks. Results show that, while the convex approach provides the best secrecy performance, the learning approach is a good alternative for dynamic scenarios or when wanting to save transmitting power.
Information security is one of the most critical issues in wireless networks as the signals transmitted through wireless medium are more vulnerable for interception. Although the existing conventional security techniques are proven to be safe, the broadcast nature of wireless communications introduces different challenges in terms of key exchange and distributions. As a result, information theoretic physical layer security has been proposed to complement the conventional security techniques for enhancing security in wireless transmissions. On the other hand, the rapid growth of data rates introduces different challenges on power limited mobile devices in terms of energy requirements. Recently, research work on wireless power transfer claimed that it has been considered as a potential technique to extend the battery lifetime of wireless networks. However, the algorithms developed based on the conventional optimization approaches often require iterative techniques, which poses challenges for real-time processing. To meet the demanding requirements of future ultra-low latency and reliable networks, neural network (NN) based approach can be employed to determine the resource allocations in wireless communications. \n \nThis thesis developed different transmission strategies for secure transmission in wireless communications. Firstly, transmitter designs are focused in a multiple-input single-output simultaneous wireless information and power transfer system with unknown eavesdroppers. To improve the performance of physical layer security and the harvested energy, artificial noise is incorporated into the network to mask the secret information between the legitimate terminals. Then, different secrecy energy efficiency designs are considered for a MISO underlay cognitive radio network, in the presence of an energy harvesting receiver. In particular, these designs are developed with different channel state information assumptions at the transmitter. Finally, two different power allocation designs are investigated for a cognitive radio network to maximize the secrecy rate of the secondary receiver: conventional convex optimization framework and NN based algorithm.
The information theoretic description of secrecy capacities and secrecy capacity regions (Liang et al., 2009) is an important research area to support a better understanding of security on the physical layer. Based on the secrecy capacity expressions or achievable secrecy rates, the transmit strategies, including power allocation, beamforming and subcarrier allocation, are optimized in order to choose a certain operating point. In this chapter, we focus on the optimization of the physical layer transmit strategies for typical wireless communication scenarios. In single-user scenarios, the system design is more complicated with additional secrecy constraints, since the secrecy capacity expressions are in general not concave or convex in the transmit strategies. The secrecy rate terms usually consist of a difference of two parts. The first one corresponds to the amount of data that can be reliably transmitted to the intended user and it is therefore concave in the transmit strategies. The second one corresponds to the amount of data that is overheard by the eavesdropper and it is thus also concave in the transmit strategies. The resulting transmit optimization problems are non-convex optimization problems since the difference of two concave functions is not necessarily convex or concave. However, in the multi-carrier case, the problem can be reduced to a convex optimization problem that can be efficiently computed. We conjecture that also the multiple antenna (MIMO) scenario will be completely solved in the very next future. In multi-user scenarios, the secrecy rate regions of all four elements of network information theory, the broadcast, the multiple access, the relay, and the interference channel were recently studied. The attacker models of the MAC and the relay case are more difficult than the wellmotivated ones of the broadcast and the interference channel. Therefore, we focus on the broadcast and interference channel. The resource allocation for the parallel broadcast channel without secrecy is involved due to a hard combinatorial problem the matching of carriers to users. Interestingly, with secrecy constraints, the resulting programming problem is much simpler and the optimal power and resource allocation can be solved efficiently. A similar
The network security is becoming more and more important in the fifth-generation (5G) networks. Therefore, the physical layer security with power transfer in heterogeneous network is investigated in this paper. The co-channel interference in the system is exploited for both secure transmission and energy harvesting in two types of eavesdropping, i.e., non-colluding and colluding eavesdropping. As such, we propose a secure transmission scheme, which obtains the maximum secrecy rate, and at the same time satisfy the outage constraints of the users' QoS and the energy harvesting requirements. Assuming that the imperfect channel state information (CSI) follows Truncated Gauss distribution, we propose a novel method based on the expectation and variance of the CSI to transform the original complex problem into the convex optimization problem. Then the algorithms for two eavesdropping cases are provided. At last, numerical results are presented to show the robustness and effectiveness of the proposed algorithms.
In this paper, we investigate secure communication with the presence of multiple eavesdroppers (Eves) in a two-tier downlink dense heterogeneous network, wherein there is a macrocell base station (MBS) and multiple femtocell base stations (FBSs).Each base station (BS) has multiple users.And Eves attempt to wiretap a macrocell user (MU).To keep Eves ignorant of the confidential message, we propose a physical-layer security scheme based on cross-layer cooperation to exploit interference in the considered network.Under the constraints on the quality of service (QoS) of other legitimate users and transmit power, the secrecy rate of system can be maximized through jointly optimizing the beamforming vectors of MBS and cooperative FBSs.We explore the problem of maximizing secrecy rate in both non-colluding and colluding Eves scenarios, respectively.Firstly, in non-colluding Eves scenario, we approximate the original non-convex problem into a few semi-definite programs (SDPs) by employing the semi-definite relaxation (SDR) technique and conservative convex approximation under perfect channel state information (CSI) case.Furthermore, we extend the frame to imperfect CSI case and use the Lagrangian dual theory to cope with uncertain constraints on CSI.Secondly, in colluding Eves scenario, we transform the original problem into a two-tier optimization problem equivalently.Among them, the outer layer problem is a single variable optimization problem and can be solved by one-dimensional linear search.While the inner-layer optimization problem is transformed into a convex SDP problem with SDR technique and Charnes-Cooper transformation.In the perfect CSI case of both non-colluding and colluding Eves scenarios, we prove that the relaxation of SDR is tight and analyze the complexity of proposed algorithms.Finally, simulation results validate the effectiveness and robustness of proposed scheme.
In this dissertation, we present novel physical (PHY) and cross-layer design guidelines and resource adaptation algorithms to improve the security and user experience in the future wireless networks. Physical and cross-layer wireless security measures can provide stronger overall security with high efficiency and can also provide better flexibility in response to the typically time-varying wireless environment. To better utilize limited wireless resources, we present approaches and techniques based on new performance criteria for wireless system optimization by thoroughly exploiting user information including its Quality of Service (QoS) requests and channel state information (CSI) to improve network throughput and security.
In recent years, there has been a growing research interest in wireless system security from PHY layer perspective. In a wiretap channel model introduced in the seminal work by Wyner, a sender “Alice” wishes to transmit a secret message to the intended receiver “Bob” in presence of a passive eavesdropper “Eve”. Existing works have characterized maximum achievable secrecy rate or secrecy capacity for single- and multiple-antenna systems by applying Gaussian signaling and secrecy code. Despite the impracticality of Gaussian input, its compact closed-form expression of mutual information motivated the wide use of Gaussian input assumption in theoretical analysis. In contrast to the Gaussian codebook, practical wiretap codes must consist of finite-alphabet symbols. Because of this constraint, the achievable secrecy rate for a finite-alphabet input scenario would differ from the secrecy rate achievable by a Gaussian codebook. In this thesis, we quantify the effect of finite discrete-constellation on instantaneous and ergodic secrecy rate of multiple-antenna wire-tap channels. Our results demonstrate substantial performance difference between systems involving finite-alphabet inputs and systems with Gaussian inputs. In addition, we investigate the secrecy performance of multi-terminal wiretap systems when a codebook based transmission beamforming is implemented. We characterize the secrecy outage probability of a communication link under eavesdropping. We consider a limited feedback scenario where the transmitter uses a pre-defined codebook known to both the transmitter and the receiver for beamforming, and analyze the secrecy outage probability of the link when it being eavesdropped.
Next, we consider the security of wireless multi-hop networks. Certainly, network security is an overarching issue that transcends all layers of communication protocol stack. Therefore, we tackle the problem of network security by proper user scheduling, routing, and resource management. Our approach of secrecy is complementary to the traditional cryptography based techniques. Together, they can provide stronger overall security and flexibility in selecting the desired solution and can reduce bandwidth and energy overhead as much as possible. Multi-hop wireless networks frequently employ the traditional routing and resource allocation strategies. Such strategies often fail to take into account the additional need for protection against security vulnerabilities due to the wireless medium. Thus, to address security concerns, we investigate the problem of eavesdropping control by proposing security-aware power allocation strategies and routing algorithms for multi-hop networks.
The future wireless infrastructure will consists of a plethora of heterogeneous collections of applications and services. A differentiated service structure would therefore be an essential part of the future wireless infrastructure. In addition to the security consideration of wireless network, we focus on the heterogeneous structure of the network. We study the problem of cross-layer resource allocation and admission control in a multiuser heterogeneous OFDMA network providing both QoS-constrained user servicesand best-effort services. Such heterogeneous networks provide service to both High-Priority (HP) users and Best-Effort (BE) users. By clustering subcarriers, efficient algorithms for cluster and power allocation have been proposed. Our strategy maximizes the total network utility of the BE users while satisfying the QoS request for maximum number of HP users. The feasibility of the resource allocation problem depends on the number of HP users in the network. Since a large number of demanding HP users would render the resource allocation problem infeasible, a joint admission control and resource allocation scheme could be an efficient way of tackling both problems with less overhead. By incorporating admission control, we propose an efficient and optimal joint admission control and resource allocation algorithm.
One benefit of 5G network deployment relates to the smaller size of cells allowing low latency and increased users capacity. The downside is that the potential eavesdroppers could be closer to the victim making the security more challenging. So it is clear the need for enhanced privacy protection in the next generation communications systems even for low power/low complexity IoT devices. The last few years there are numerous research efforts to enhance transmitted information security with complementary techniques that operate in physical layer. In this paper we propose a physical layer scheme that complements the security schemes implemented in the upper layers or/and in the physical layer. The proposed scheme takes advantage of the pilot subcarriers that are part of an OFDM transmission. Pilot subcarriers are essential for the pilot channel estimation process performed at the receiver. In conventional OFDM systems the positions of pilot subcarriers are known. In this paper we propose the positions of the subcarriers to change on every OFDM symbol following a probability distribution known only to the legitimate transmitter and legitimate receiver. This puts a passive eavesdropper at a relative disadvantage compared to a legitimate receiver, because it does not know the position of the pilot subcarriers. To evaluate the security performance of the proposed scheme the secrecy capacity and the outage probability are used as metrics.