Two legitimate parties, referred to as Alice and Bob, wish to generate secret keys from the wireless channel in the presence of an eavesdropper, referred to as Eve, in order to use such keys for encryption and decryption. In general, the secret key rate highly depends on the coherence time of the channel. In particular, a straightforward method of generating secret keys in static environments results in ultra-low rates. In order to resolve this problem, we introduce a low-complexity method called induced randomness. In this method, Alice and Bob independently generate local randomness to be used together with the uniqueness of the wireless channel coefficients in order to enable high-rate secret key generation. In this work, two scenarios are considered: first, when Alice and Bob share a direct communication channel, and second, when Alice and Bob do not have a direct link and communicate through an untrusted relay. After exchanging the induced randomness, post-processing is done by Alice and Bob to generate highly-correlated samples that are used for the key generation. Such samples are then converted into bits, disparities between the sequences generated by Alice and Bob are mitigated, and the resulting sequences are then hashed to compensate for the information leakage to the eavesdropper and to allow consistency checking of the generated key bit sequences. We utilize semantic security measures and information-theoretic inequalities to upper bound the probability of successful eavesdropping attack in terms of the mutual information measures that can be numerically computed. Given certain reasonable system parameters this bound is numerically evaluated to be 2-31and 2-10.57in the first and the second scenario, respectively.
Two legitimate parties, referred to as Alice and Bob, wish to generate secret keys from the wireless channel in the presence of an eavesdropper, referred to as Eve, in order to use such keys for encryption and decryption. In general, the secret key rate highly depends on the coherence time of the channel. In particular, a straightforward method of generating secret keys in static environments results in ultra-low rates. In order to resolve this problem, we introduce a low-complexity method called induced randomness. In this method, Alice and Bob independently generate local randomness to be used together with the uniqueness of the wireless channel coefficients in order to enable high-rate secret key generation. In this work, two scenarios are considered: first, when Alice and Bob share a direct communication channel, and second, when Alice and Bob do not have a direct link and communicate through an untrusted relay. After exchanging the induced randomness, post-processing is done by Alice and Bob to generate highly-correlated samples that are used for the key generation. Such samples are then converted into bits, disparities between the sequences generated by Alice and Bob are mitigated, and the resulting sequences are then hashed to compensate for the information leakage to the eavesdropper and to allow consistency checking of the generated key bit sequences. We utilize semantic security measures and information-theoretic inequalities to upper bound the probability of successful eavesdropping attack in terms of the mutual information measures that can be numerically computed. Given certain reasonable system parameters this bound is numerically evaluated to be 2-31and 2-10.57in the first and the second scenario, respectively.
Secret key agreement in distributed low-power networks, such as Internet of Things (IoT) networks, is a major requirement for deploying cryptographic protocols to protect the security of sensitive data. However, due to the distributed nature of such networks, the devices need to be able to generate secret keys locally from some common source of randomness. The randomness in the characteristics of the physical layer channel provides such sources, however, this can be quite limited if the devices operate in a static environment and experience static or very slow fading channel. Therefore, fast secret key generation in such environments while keeping a low complexity architecture for the network nodes, such as IoT devices, remains a challenging task. We design a low-complexity protocol for fast secret key generation in static environments. To this end, we propose to use a limited number of random bits independently generated by the legitimate parties, referred to as Alice and Bob, in combination with the fading parameter to create a common source of randomness. In the proposed protocol, Alice and Bob share their random bits over the public channel, assumed to be a fading channel, and then construct a common random sequence. Then they perform several steps for recovery from errors in the shared sequence, privacy amplification to limit the chances of a successful attack, and consistency checking by exploiting universal hash functions. We characterize the reliability of the proposed protocol and provide an upper bound on the probability of accepting a mismatched key by Alice and Bob. The eavesdropper Eve is assumed to be passive and a successful attack by her is the event of guessing the key right based on her observations. We provide an analytical upper bound, that can be numerically evaluated, on the probability of a successful attack by Eve using the cryptographic notion of semantic security. In the simulations, the proposed protocol achieves a bit generation rate of 64-96 bits/packet, bit mismatch rate of 11-24%, bit error rate of 0.005%, 50% randomness efficiency, the probability of successful attack of at most 2-31, and the probability of consistency checking failure of at most 2-16.
Physical layer secret key generation exploits the reciprocal channel randomness for key generation and has proven to be an effective addition security layer in wireless communications. However, static or scarcely random channels require artificially induced dynamics to improve the secrecy performance, e.g., using intelligent reflecting surface (IRS). One key challenge is that the induced random phase from IRS is also reflected in the direction to eavesdroppers (Eve). This leakage enables Eve nodes to estimate the legitimate channels and secret key via a globally known pilot sequence. To mitigate the secret key leakage issue, we propose to exploit random matrix theory to inform the design of a new physical layer secret key generation (PL-SKG) algorithm. We prove that, when sending appropriate random Gaussian matrices, the singular values of Alice's and Bob's received signals follow a similar probability distribution. Leveraging these common singular values, we propose a random Gaussian matrix based PL-SKG (RGM PL-SKG), which avoids the usages of the globally known pilot and thereby prevents the aforementioned leakage issue. Our results show the following: (i) high noise resistance which leads to superior secret key rate (SKR) improvement (up to 300%) in low SNR regime, and (ii) general improved SKR performance against multiple colluded Eves. We believe our combination of random matrix theory and PL-SKG shows a new paradigm to secure the wireless communication channels.
The use of wireless networks for communication has grown significantly in recent times, and continues to develop further. The broadcast nature of wireless communications makes them susceptible to a wide variety of security attacks. Unlike traditional solutions, which usually handle security at the application layer, the primary concern of this dissertation is to analyse and develop solutions for secure communication using channel coding techniques at the physical-layer. \nThe topic of physical layer authenticated encryption using high rate key generation through shared randomness is investigated in this work. First, a physical layer secret key generation scheme is discussed exploiting channel reciprocity in wireless systems. In order to address the susceptibility of this family of schemes to active attacks, a novel physical layer authentication encryption protocol is presented along with its extension to multi-node networks in the presence of active adversaries. Unlike previous work in the area of generating secret keys through shared randomness, it is demonstrated that the proposed scheme is semantically secure with respect to chosen plaintext and chosen cipher text attacks. \nSecondly, in order to increase the rate in bits per seconds at which agreed cryptographic keys are been generated, a multi-level quantization algorithm with public feedback is discussed. It is demonstrated that the proposed scheme is superior to direct information distillation approaches and can substantially increase the key generation rates even at low and medium SNRs. Furthermore, the employment of this low-overhead feedback at the information distillation process can largely simplify the information reconciliation process. \nThe proposed secret key generation schemes are tested for randomness such as required for cryptographic keys. The validation test is perfomed with the aid of National Institute of Standards and Technology (NIST) statistical test suite. The P-values obtained in each of the test carried out indicates that the key sequence generated by our algorithm is random.
This paper studies the problem of extracting common randomness (CR) or secret keys from correlated random sources observed by two legitimate parties, Alice and Bob, through public discussion in the presence of an eavesdropper, Eve. We propose a practical two-stage CR extraction framework. In the first stage, the variational probabilistic quantization (VPQ) step is introduced, where Alice and Bob employ probabilistic neural network (NN) encoders to map their observations into discrete, nearly uniform random variables (RVs) with high agreement probability while minimizing information leakage to Eve. This is realized through a variational learning objective combined with adversarial training. In the second stage, a secure sketch using code-offset construction reconciles the encoder outputs into identical secret keys, whose secrecy is guaranteed by the VPQ objective. As a representative application, we study physical layer key (PLK) generation. Beyond the traditional methods, which rely on the channel reciprocity principle and require two-way channel probing, thus suffering from large protocol overhead and being unsuitable in high mobility scenarios, we propose a sensing-based PLK generation method for integrated sensing and communications (ISAC) systems, where paired range-angle (RA) maps measured at Alice and Bob serve as correlated sources. The idea is verified through both end-to-end simulations and real-world software-defined radio (SDR) measurements, including scenarios where Eve has partial knowledge about Bob's position. The results demonstrate the feasibility and convincing performance of both the proposed CR extraction framework and sensing-based PLK generation method.
Secret key generation based on channel characteristics is an effective physical-layer security method for 5G wireless networks. The issues of how to ensure the high key generation rate and correlation of the secret key under active attack are needed to be addressed. In this paper, a new practical secret key generation scheme with high rate and correlation is proposed. In our proposed scheme, Alice and Bob transmit independent random sequences instead of known training sequences or probing signals; neither Alice nor Bob can decode these random sequences or estimate the channel. User's random sequences together with the channel effects are used as common random source to generate the secret key. With this solution, legitimate users are able to share secret keys with sufficient length and high security under active attack. We evaluate the proposed scheme through both analytic and simulation studies. The results show that our proposed scheme achieves high key generation rate and key security, and is suitable for 5G wireless networks with resource-constrained devices.
Physical layer security (PLS) can be used to pro-vide keyless and innately secure communications by exploiting the propagation characteristics of the wireless channel at the physical layer (PHY) layer to co-generate cipher keys for symmetric encryption. While existing methods use channel state information as input for secret key generation, we consider a novel approach that derives features from frequency-time domain representation of in-phase and quadrature (IQ) samples to derive initial keys with high agreement rate. A recurrent neural network (RNN) with a quadruplet loss function is trained based on spectrograms collected from bi-directional time-division duplex channel probing between the two parties and on spectrograms collected from a passive eavesdropper. Information reconciliation is achieved using Reed Solomon codes. At the last step of the protocol, a 512-bit cryptographic key is generated by feeding the reconciled bit sequence to the Secure Hash Algorithm 3. Our experiments with software-defined radios in both indoor and outdoor environments evaluate the proposed key generation system under different channel propagation environments and hardware inaccuracies. We demonstrate that the proposed RNN-assisted channel feature extractor trained on indoor channel probe data operates successfully in two outdoor setups and produces up to 70 amplified keys out of 100 probes exchanged between two trusted parties i.e., Alice and Bob, while the passive eavesdropper fails to directly predict any of the generated keys.