IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)
Physical-Layer Cooperative Key Generation with Correlated Eavesdropping Channels in IoT
With a massive amount of wireless sensor nodes in Internet of Things (IoT), it is difficult to establish key distribution and management mechanism for traditional encryption technology. Alternatively, the physical layer key generation technology is promising to implement in IoT, since it is based on the principle of information-theoretical security and has the advantage of low complexity. Most existing key generation schemes assume that eavesdropping channels are independent of legitimate channels, which may not be practical especially when eavesdropper nodes are near to legitimate nodes. However, this paper investigates key generation problems for a multi-relay wireless network in IoT, where the correlation between eavesdropping and legitimate channels are considered. Key generation schemes are proposed for both non-colluding and partially colluding eavesdroppers situations. The main idea is to divide the key agreement process into three phases: 1) we first generate a secret key by exploiting the difference between the random channels associated with each relay node and the eavesdropping channels; 2) another key is generated by integrating the residual common randomness associated with each relay pair; 3) the two keys generated in the first two phases are concatenated into the final key. The secrecy key performance of the proposed key generation schemes is also derived with closed-forms.
With a massive amount of wireless sensor nodes in Internet of Things (IoT), it is difficult to establish key distribution and management mechanism for traditional encryption technology. Alternatively, the physical layer key generation technology is promising to implement in IoT, since it is based on the principle of information-theoretical security and has the advantage of low complexity. Most existing key generation schemes assume that eavesdropping channels are independent of legitimate channels, which may not be practical especially when eavesdropper nodes are near to legitimate nodes. However, this paper investigates key generation problems for a multi-relay wireless network in IoT, where the correlation between eavesdropping and legitimate channels are considered. Key generation schemes are proposed for both non-colluding and partially colluding eavesdroppers situations. The main idea is to divide the key agreement process into three phases: 1) we first generate a secret key by exploiting the difference between the random channels associated with each relay node and the eavesdropping channels; 2) another key is generated by integrating the residual common randomness associated with each relay pair; 3) the two keys generated in the first two phases are concatenated into the final key. The secrecy key performance of the proposed key generation schemes is also derived with closed-forms.
Internet-of-Things (IoT) networks generally contain resource-constrained devices that require an energy-efficient key generation procedure to producing secure keys at a faster rate. The physical characteristics of the wireless channel can be exploited to secure communication within IoT networks. In particular, secret keys can be generated by leveraging on the randomness of the wireless physical channel between two communicating parties. The conventional mechanism of generating keys at the physical layer, i.e., using channel probing, quantization, information reconciliation, and privacy amplification, may not be preferable for IoT devices. In addition, in some cases IoT devices may be deployed in static environments, wherein the channel coherence time is too high to generate keys at a faster rate and with the desired randomness. This study proposes a mapping table-based key distribution scheme for IoT environments, wherein multiple characteristics of the random channel are combined to improve not only the key generation rate (KGR) but also the key agreement rate (KAR) and bit error rate (BER). In the proposed scheme, both the channel magnitude and the phase are exploited in the key generation process. The proposed scheme is immune to channel estimation errors while providing sufficient randomness in the static environment. Additionally, the scheme is thoroughly investigated for different scenarios including the case of a smarter eavesdropper, which attempts to estimate the channel between the legitimate nodes. This case verifies the robustness of the proposed scheme in different settings and attack models.
Devices in the Internet of Things (IoT) are usually limited in computing resources and energy capacity, which means that encryption schemes with higher complexity are not suitable for them to ensure secure communication. As a promising solution to this problem, physical layer key generation suggests that shared secret keys can be generated from noisy wireless channel measurements to enhance the security of wireless communications. In this article, we propose a key generation scheme with extremely low implementation complexity, which allows physical layer key generation to be implemented on IoT nodes. First, we preprocess the channel measurements with simple moving average filtering before quantization to improve channel reciprocity. Next, a bidirectional difference quantization scheme is proposed to realize reliable quantization of channel measurements, which is ingenious in that the quantization process does not depend on quantization thresholds, and thus, the mismatched key bits caused by measurements close to quantization thresholds can be effectively avoided. Then, we propose an improved Cascade protocol to achieve lightweight and efficient information reconciliation. The simulation results show that our scheme can well balance the reliability and efficiency of key generation, and has excellent performance in terms of implementation complexity and key randomness.
Physical layer encryption is a promising solution to provide transmission security for Internet-of-Things (IoT). To realize physical layer encryption, channel state information (CSI) as a random source to generate secret keys should be exploited. The reciprocity of wireless channel between legitimate communication nodes which is typically assumed for time division duplex (TDD) systems, is of critical importance to ensure the consistency in generated keys at two nodes. However, in practical TDD systems, due to the asynchronous measurement of CSI, the receiver noise and the the difference in hardware, etc., the reciprocity of channel measurements between legitimate parties is hard to be guaranteed, which makes physical layer key generation approach infeasible. To address this issue, we propose a wireless key generation scheme based on deep learning techniques. Firstly, a feature extraction network, which consists of two auto-encoders trained jointly, is developed to extract the common feature from the different yet correlated channel observations at two legitimate nodes, which will be used as the source to generate keys. Then a quantizer with an adaptive guard band width is devised to output a binary secret-key sequence from the feature vector. Numerical results show that the proposed scheme achieves remarkable improvement in terms of key disagreement rate (KDR) and key generation rate (KGR) compared existing counterparts in the literature.
With the increasing demands for sharing confidential information among massive Internet of Things (IoT) devices in 5G and beyond wireless networks, many applications require the common secret key generation for a group of IoT devices. However, most of the existing works on physical layer secret key generation (PLKG) only focus on the pairwise key generation between two users, which is a low efficient and high cost to be extended to the scenarios of group key generation. In this work, we propose a new efficient multiple-input–multiple-output (MIMO) physical layer group secret key generation scheme to reduce the consumption of channel probing and improve the efficiency for group key generation. Different from current schemes, in the proposed scheme, the transmitter randomly generates the group secret key and directly broadcasts the downlink data symbols to the group users. At the receiver end, each group user can efficiently “observe” the common group key through the downlink broadcasting data symbols, while keeping perfect secrecy of the shared group key against eavesdroppers. The performance of reliability, security, and the group key generation rate is fully investigated, which shows the advantages of high efficiency, low consumption, and strong robustness of the proposed scheme. Extensive simulations are conducted to validate the effectiveness of the proposed scheme.
There is growing interest in wireless security methods that provide strong or even perfect secrecy by taking advantage of features of the physical propagation channel. In advantage-based methods, high channel quality in an average or opportunistic sense is exploited between two legitimate nodes, such that nonzero secrecy capacity can be achieved. Since such methods require bounds on the quality of the eavesdropper channel, they are somewhat impractical. Secret key generation based on tracking channel evolution in time division duplex systems is a more attractive option, where two nodes generate secret key bits based on a mutually known random channel. Since the eavesdropper channel is typically independent of the legitimate channel, the key can only be broken by brute force attacks, which are difficult when new keys are continuously generated. In this paper, the information theoretic limits of key generation schemes are investigated, based on the level of estimation error, temporal correlation, and dependence of the eavesdropper and legitimate channels. Three practical candidate key generation schemes are also considered: channel quantization and channel quantization with guardband.
As Internet of Things (IoT) has boomed in recent years, many security issues have also been exposed. Focusing on physical layer security in wireless Internet of Things network communication, a series of security methods have been widely studied. Nevertheless, cooperative jamming methods in physical layer security to fight against collusive eavesdroppers have not been thoroughly studied yet. In this article, we study a cooperative-jamming-based physical layer secure transmission scheme for Internet of Things wireless networks in the presence of collusive eavesdroppers. We design a cooperative jamming strategy without knowing the channel state information of eavesdroppers. Considering the cooperation of multiple nodes with multiple antennas, this strategy can maximize the signal-to-interference-plus-noise ratio at an actuator (legitimate receiver). Meanwhile, the generated cooperative jamming signals can reduce the signal-to-interference-plus-noise ratio at eavesdroppers. To explore the theoretical security performance of our strategy, we perform a secrecy outage probability analysis and an asymptotic analysis. In the cases of cooperative jamming and without cooperative jamming, the closed-form expressions of the secrecy outage probability are deduced, and the influence of system parameters on the secrecy outage probability becomes more intuitive through a strict mathematical asymptotic behavior analysis. In addition, considering the energy limitation of Internet of Things devices, we propose a power allocation algorithm to minimize the total transmission power given the security requirements. The numerical results show the effectiveness of our schemes and are consistent with the theoretical analysis.