A Review of Physical Layer Security Techniques for Internet of Things: Challenges and Solutions.

With the uninterrupted revolution of communications technologies and the great-leap-forward development of emerging applications, the ubiquitous deployment of Internet of Things (IoT) is imperative to accommodate constantly growing user demands and market scales. Communication security is critically important for the operations of IoT. Among the communication security provisioning techniques, physical layer security (PLS), which can provide unbreakable, provable, and quantifiable secrecy from an information-theoretical point of view, has drawn considerable attention from both the academia and the industries. However, the unique features of IoT, such as low-cost, wide-range coverage, massive connection, and diversified services, impose great challenges for the PLS protocol design in IoT. In this article, we present a comprehensive review of the PLS techniques toward IoT applications. The basic principle of PLS is first briefly introduced, followed by the survey of the existing PLS techniques. Afterwards, the characteristics of IoT are identified, based on which the challenges faced by PLS protocol design are summarized. Then, three newly-proposed PLS solutions are highlighted, which match the features of IoT well and are expected to be applied in the near future. Finally, we conclude the paper and point out some further research directions.

Secure transmission for mixed FSO-RF relay networks with physical-layer key encryption and wiretap coding.

In this paper, we propose a secure transmission scheme to protect the confidential messages in a mixed free space optical-radio frequency (FSO-RF) relay network against malicious eavesdroppers. In the proposed scheme, the physical-layer key generation, encryption method and physical-layer wiretap coding are exploited to protect the FSO and RF links. Specifically, the overall transmission is divided into two time slots. In the first time slot, the transmitter and relay of the FSO link utilize the channel reciprocity of the FSO link to generate key packets. In the second time slot, the confidential messages will be securely transmitted from the transmitter to the receiver assisted by the relay over two phases. In the first phase, the transmitter sends the confidential messages to the relay through the FSO link encrypted by the generated key packets. In the second phase, the relay will forward these confidential messages to the receiver through the RF link protected by the physical-layer wiretap coding. For the proposed scheme, the key generation rate can be obtained. In addition, we analyze the performance of the connection outage probability and the secrecy outage probability, and optimally design the target transmission rate and secrecy rate such that the average secrecy rate is maximized. Numerical results are presented to demonstrate the performance superiority of the proposed scheme in terms of the average secrecy rate.

Reciprocally-Benefited Secure Transmission for Spectrum Sensing-Based Cognitive Radio Sensor Networks.

The rapid proliferation of independently-designed and -deployed wireless sensor networks extremely crowds the wireless spectrum and promotes the emergence of cognitive radio sensor networks (CRSN). In CRSN, the sensor node (SN) can make full use of the unutilized licensed spectrum, and the spectrum efficiency is greatly improved. However, inevitable spectrum sensing errors will adversely interfere with the primary transmission, which may result in primary transmission outage. To compensate the adverse effect of spectrum sensing errors, we propose a reciprocally-benefited secure transmission strategy, in which SN's interference to the eavesdropper is employed to protect the primary confidential messages while the CRSN is also rewarded with a loose spectrum sensing error probability constraint. Specifically, according to the spectrum sensing results and primary users' activities, there are four system states in this strategy. For each state, we analyze the primary secrecy rate and the SN's transmission rate by taking into account the spectrum sensing errors. Then, the SN's transmit power is optimally allocated for each state so that the average transmission rate of CRSN is maximized under the constraint of the primary maximum permitted secrecy outage probability. In addition, the performance tradeoff between the transmission rate of CRSN and the primary secrecy outage probability is investigated. Moreover, we analyze the primary secrecy rate for the asymptotic scenarios and derive the closed-form expression of the SN's transmission outage probability. Simulation results show that: (1) the performance of the SN's average throughput in the proposed strategy outperforms the conventional overlay strategy; (2) both the primary network and CRSN benefit from the proposed strategy.

Dynamic RACH Partition for Massive Access of Differentiated M2M Services.

In machine-to-machine (M2M) networks, a key challenge is to overcome the overload problem caused by random access requests from massive machine-type communication (MTC) devices. When differentiated services coexist, such as delay-sensitive and delay-tolerant services, the problem becomes more complicated and challenging. This is because delay-sensitive services often use more aggressive policies, and thus, delay-tolerant services get much fewer chances to access the network. To conquer the problem, we propose an efficient mechanism for massive access control over differentiated M2M services, including delay-sensitive and delay-tolerant services. Specifically, based on the traffic loads of the two types of services, the proposed scheme dynamically partitions and allocates the random access channel (RACH) resource to each type of services. The RACH partition strategy is thoroughly optimized to increase the access performances of M2M networks. Analyses and simulation demonstrate the effectiveness of our design. The proposed scheme can outperform the baseline access class barring (ACB) scheme, which ignores service types in access control, in terms of access success probability and the average access delay.

Massive Access Control Aided by Knowledge-Extraction for Co-Existing Periodic and Random Services over Wireless Clinical Networks.

The prosperity of e-health is boosted by fast development of medical devices with wireless communications capability such as wearable devices, tiny sensors, monitoring equipments, etc., which are randomly distributed in clinic environments. The drastically-increasing population of such devices imposes new challenges on the limited wireless resources. To relieve this problem, key knowledge needs to be extracted from massive connection attempts dispersed in the air towards efficient access control. In this paper, a hybrid periodic-random massive access (HPRMA) scheme for wireless clinical networks employing ultra-narrow band (UNB) techniques is proposed. In particular, the proposed scheme towards accommodating a large population of devices include the following new features. On one hand, it can dynamically adjust the resource allocated for coexisting periodic and random services based on the traffic load learned from signal collision status. On the other hand, the resource allocation within periodic services is thoroughly designed to simultaneously align with the timing requests of differentiated services. Abundant simulation results are also presented to demonstrate the superiority of the proposed HPRMA scheme over baseline schemes including time-division multiple access (TDMA) and random access approach, in terms of channel utilization efficiency, packet drop ratio, etc., for the support of massive devices' services.