Considered sensitive information by the ISO/IEC 24745, biometric data should be stored and used in a protected way. If not, privacy and security of end-users can be compromised. Also, the advent of quantum computers demands quantum-resistant solutions. This work proposes the use of Kyber and Saber public key encryption (PKE) algorithms together with homomorphic encryption (HE) in a face recognition system. Kyber and Saber, both based on lattice cryptography, were two finalists of the third round of NIST post-quantum cryptography standardization process. After the third round was completed, Kyber was selected as the PKE algorithm to be standardized. Experimental results show that recognition performance of the non-protected face recognition system is preserved with the protection, achieving smaller sizes of protected templates and keys, and shorter execution times than other HE schemes reported in literature that employ lattices. The parameter sets considered achieve security levels of 128, 192 and 256 bits.

Efficient large-scale biometric identification is a challenging open problem in biometrics today. Adding biometric information protection by cryptographic techniques increases the computational workload even further. Therefore, this paper proposes an efficient and improved use of coefficient packing for homomorphically protected biometric templates, allowing for the evaluation of multiple biometric comparisons at the cost of one. In combination with feature dimensionality reduction, the proposed technique facilitates a quadratic computational workload reduction for biometric identification, while long-term protection of the sensitive biometric data is maintained throughout the system. In previous works on using coefficient packing, only a linear speed-up was reported. In an experimental evaluation on a public face database, efficient identification in the encrypted domain is achieved on off-the-shelf hardware with no loss in recognition performance. In particular, the proposed improved use of coefficient packing allows for a computational workload reduction down to 1.6% of a conventional homomorphically protected identification system without improved packing.

Advanced Encryption Standard (AES) algorithm plays an important role in a data security application. In general S-box module in AES will give maximum confusion and diffusion measures during AES encryption and cause significant path delay overhead. In most cases, either L UTs or embedded memories are used for S- box computations which are vulnerable to attacks that pose a serious risk to real-world applications. In this paper, implementation of the composite field arithmetic-based Sub-bytes and inverse Sub-bytes operations in AES is done. The proposed work includes an efficient multiple round AES cryptosystem with higher-order transformation and composite field s-box formulation with some possible inner stage pipelining schemes which can be used for throughput rate enhancement along with path delay optimization. Finally, input biometric-driven key generation schemes are used for formulating the cipher key dynamically, which provides a higher degree of security for the computing devices.

In healthcare 4.0 ecosystems, authentication of healthcare information allows health stakeholders to be assured that data is originated from correct source. Recently, biometric based authentication is a preferred choice, but as the templates are stored on central servers, there are high chances of copying and generating fake biometrics. An adversary can forge the biometric pattern, and gain access to critical health systems. Thus, to address the limitation, the paper proposes a scheme, PHBio, where an encryption-based biometric system is designed prior before storing the template to the server. Once a user provides his biometrics, the authentication process does not decrypt the data, rather uses a homomorphic-enabled Paillier cryptosystem. The scheme presents the encryption and the comparison part which is based on euclidean distance (EUD) strategy between the user input and the stored template on the server. We consider the minimum distance, and compare the same with a predefined threshold distance value to confirm a biometric match, and authenticate the user. The scheme is compared against parameters like accuracy, false rejection rates (FARs), and execution time. The proposed results indicate the validity of the scheme in real-time health setups.

Cancelable biometric is a new era of technology that deals with the protection of the privacy content of a person which itself helps in protecting the identity of a person. Here the biometric information instead of being stored directly on the authentication database is transformed into a non-invertible coded format that will be utilized for providing access. The conversion into an encrypted code requires the provision of an encryption key from the user side. Both invertible and non-invertible coding techniques are there but non-invertible one provides additional security to the user. In this paper, a non-invertible cancelable biometric method has been proposed where the biometric image information is canceled and encoded into a code using a user-provided encryption key. This code is generated from the image histogram after continuous bin updation to the maximal value and then it is encrypted by the Hill cipher. This code is stored on the database instead of biometric information. The technique is applied to a set of retinal information taken from the Indian Diabetic Retinopathy database.

Face recognition is a biometric technique that uses a computer or machine to facilitate the recognition of human faces. The advantage of this technique is that it can detect faces without direct contact with the device. In its application, the security of face recognition data systems is still not given much attention. Therefore, this study proposes a technique for securing data stored in the face recognition system database. It implements the Viola-Jones Algorithm, the Kanade-Lucas-Tomasi Algorithm (KLT), and the Principal Component Analysis (PCA) algorithm by applying a database security algorithm using XOR encryption. Several tests and analyzes have been performed with this method. The histogram analysis results show no visual information related to encrypted images with plain images. In addition, the correlation value between the encrypted and plain images is weak, so it has high security against statistical attacks with an entropy value of around 7.9. The average time required to carry out the introduction process is 0.7896 s.

The cutting-edge biometric recognition systems extract distinctive feature vectors of biometric samples using deep neural networks to measure the amount of (dis-)similarity between two biometric samples. Studies have shown that personal information (e.g., health condition, ethnicity, etc.) can be inferred, and biometric samples can be reconstructed from those feature vectors, making their protection an urgent necessity. State-of-the-art biometrics protection solutions are based on homomorphic encryption (HE) to perform recognition over encrypted feature vectors, hiding the features and their processing while releasing the outcome only. However, this comes at the cost of those solutions' efficiency due to the inefficiency of HE-based solutions with a large number of multiplications; for (dis-)similarity measures, this number is proportional to the vector's dimension. In this paper, we tackle the HE performance bottleneck by freeing the two common (dis-)similarity measures, the cosine similarity and the squared Euclidean distance, from multiplications. Assuming normalized feature vectors, our approach pre-computes and organizes those (dis-)similarity measures into lookup tables. This transforms their computation into simple table-lookups and summation only. We study quantization parameters for the values in the lookup tables and evaluate performances on both synthetic and facial feature vectors for which we achieve a recognition performance identical to the non-tabularized baseline systems. We then assess their efficiency under HE and record runtimes between 28.95ms and 59.35ms for the three security levels, demonstrating their enhanced speed.

Propagation delay in blockchain networks is a major impairment of message transmission and validation in the bitcoin network. The transaction delay caused by message propagation across long network chains can cause significant threats to the bitcoin network integrity by allowing miners to find blocks during the message consensus process. Potential threats of slow transaction dissemination include double-spending, partitions, and eclipse attacks. In this paper, we propose a method for minimizing propagation delay by reducing non-compulsory message broadcasts during transaction dissemination in the underlying blockchain network. Our method will decrease the propagation delay in the bitcoin network and consequently mitigate the security threats based on message dissemination delay. Our results show improvement in the delay time with more effect on networks with a large number of nodes.

Bitcoin P2P networking is especially vulnerable to networking threats because it is permissionless and does not have the security protections based on the trust in identities, which enables the attackers to manipulate the identities for Sybil and spoofing attacks. The Bitcoin node keeps track of its peer’s networking misbehaviors through ban scores. In this paper, we investigate the security problems of the ban-score mechanism and discover that the ban score is not only ineffective against the Bitcoin Message-based DoS (BM-DoS) attacks but also vulnerable to the Defamation attack as the network adversary can exploit the ban score to defame innocent peers. To defend against these threats, we design an anomaly detection approach that is effective, lightweight, and tailored to the networking threats exploiting Bitcoin’s ban-score mechanism. We prototype our threat discoveries against a real-world Bitcoin node connected to the Bitcoin Mainnet and conduct experiments based on the prototype implementation. The experimental results show that the attacks have devastating impacts on the targeted victim while being cost-effective on the attacker side. For example, an attacker can ban a peer in two milliseconds and reduce the victim’s mining rate by hundreds of thousands of hash computations per second. Furthermore, to counter the threats, we empirically validate our detection countermeasure’s effectiveness and performances against the BM-DoS and Defamation attacks.

Due to Bitcoin's innovative block structure, it is both immutable and decentralized, making it a valuable tool or instrument for changing current financial systems. However, the appealing features of Bitcoin have also drawn the attention of cybercriminals. The Bitcoin scripting system allows users to include up to 80 bytes of arbitrary data in Bitcoin transactions, making it possible to store illegal information in the blockchain. This makes Bitcoin a powerful tool for obfuscating information and using it as the command-and-control infrastructure for blockchain-based botnets. On the other hand, Blockchain offers an intriguing solution for IoT security. Blockchain provides strong protection against data tampering, locks Internet of Things devices, and enables the shutdown of compromised devices within an IoT network. Thus, blockchain could be used both to attack and defend IoT networks and communications.

Cryptocurrencies like Bitcoin have become a popular weapon for illegal activities. They have the characteristics of decentralization and anonymity, which can effectively avoid the supervision of government departments. How to de-anonymize Bitcoin transactions is a crucial issue for regulatory and judicial investigation departments to supervise and combat crimes involving Bitcoin effectively. This paper aims to de-anonymize Bitcoin transactions and present a Bitcoin transaction traceability method based on Bitcoin network traffic analysis. According to the characteristics of the physical network that the Bitcoin network relies on, the Bitcoin network traffic is obtained at the physical convergence point of the local Bitcoin network. By analyzing the collected network traffic data, we realize the traceability of the input address of Bitcoin transactions and test the scheme in the distributed Bitcoin network environment. The experimental results show that this traceability mechanism is suitable for nodes connected to the Bitcoin network (except for VPN, Tor, etc.), and can obtain 47.5% recall rate and 70.4% precision rate, which are promising in practice.

Bitcoin is a famously decentralized cryptocurrency. Bitcoin is excellent because it is a digital currency that provides convenience and security in transactions. Transaction security in Bitcoin uses a consensus involving a distributed system, the security of this system generates a hash sequence with a Proof of Work (PoW) mechanism. However, in its implementation, various attacks appear that are used to generate profits from the existing system. Attackers can use various types of methods to get an unfair portion of the mining income. Such attacks are commonly referred to as Mining attacks. Among which the famous is the Selfish Mining attack. In this study, we simulate the effect of changing decision matrix, attacker region, attacker hash rate on selfish miner attacks by using the opensource NS3 platform. The experiment aims to see the effect of using 1%, 10%, and 20% decision matrices with different attacker regions and different attacker hash rates on Bitcoin selfish mining income. The result of this study shows that regional North America and Europe have the advantage in doing selfish mining attacks. This advantage is also supported by increasing the decision matrix from 1%, 10%, 20%. The highest attacker income, when using decision matrix 20% in North America using 16 nodes on 0.3 hash rate with income 129 BTC. For the hash rate, the best result for a selfish mining attack is between 27% to 30% hash rate.

Blockchain technology has made it possible to store and send digital currencies. Bitcoin wallets and marketplaces have made it easy for nontechnical users to use the protocol. Since its inception, the price of Bitcoin is going up and the number of nodes in the network has increased drastically. The increasing popularity of Bitcoin has made exchanges and individual nodes a target for an attack. Understanding the Bitcoin protocol better helps security engineers to harden the network and helps regular users secure their hot wallets. In this paper, Bitcoin protocol is presented with description of the mining process which secures transactions. In addition, the Bitcoin algorithms and their security are described with potential vulnerabilities in the protocol and potential exploits for attackers. Finally, we propose some security solutions to help mitigate attacks on Bitcoin exchanges and hot wallets.

In recent years, blockchain technology has become one of the key technical innovation fields in the world. From the simple Bitcoin that can only be transferred at first to the blockchain application ecology that is now blooming, blockchain is gradually building a credible internet of value. However, with the continuous development and application of blockchain, even the blockchain based on cryptography is facing a series of network security problems and has caused great property losses to participants. Therefore, studying blockchain security and accelerating standardization of blockchain security have become the top priority to ensure the orderly and healthy development of blockchain technology. This paper briefly introduces the scope of blockchain security from the perspective of network security, sorts out some existing standards related to blockchain security, and gives some suggestions to promote the development and application of blockchain security standardization.

While it is possible to exchange tokens whose smart contracts are on the same blockchain, cross-exchanging bitcoins for a Bitcoin wrapped token is still cumbersome. In particular, current methods of exchange are still custodial and perform privacy-threatening controls on the users in order to operate. To solve this problem we present BxTB: cross-chain exchanges of bitcoins for any Bitcoin wrapped tokens. BxTB lets users achieve that by bypassing the mint-and-burn paradigm of current wrapped tokens and cross-exchanging already minted tokens in a P2P way. Instead of relaying on HTLCs and the overhead of communication and slowness due to time-locks, we leverage Stateless SPVs, i.e. proof-of-inclusion of transactions in the Bitcoin chain validated through a smart contract deployed on the other blockchain. Furthermore, since this primitive has not been introduced in the academic literature yet, we formally introduce it and we prove its security.

A recent spam wave of IP addresses in the Bitcoin P2P network allowed us to estimate the degree distribution of reachable peers. The resulting distribution indicates that about half of the reachable peers run with Bitcoin Core’s default setting of a maximum of 125 concurrent connections and nearly all connection slots are taken. We validate this result empirically. We use our observations of the spam wave to group IP addresses that belong to the same peer. By doing this grouping, we improve on previous measurements of the number of reachable peers and show that simply counting IP addresses overestimates the number of reachable peers by 15 %. We revalidate previous work by using our observations to estimate the number of unreachable peers.

The term cryptocurrency refers to a digital currency based on cryptographic concepts that have become popular in recent years. Bitcoin is a decentralized cryptocurrency that uses the distributed append-only public database known as blockchain to record every transaction. The incentive-compatible Proof-of-Work (PoW)-centered decentralized consensus procedure, which is upheld by the network's nodes known as miners, is essential to the safety of bitcoin. Interest in Bitcoin appears to be growing as the market continues to rise. Bitcoins and Blockchains have identical fundamental ideas, which are briefly discussed in this paper. Various studies discuss blockchain as a revolutionary innovation that has various applications, spanning from bitcoins to smart contracts, and also about it being a solution to many issues. Furthermore, many papers are reviewed here that not only look at Bitcoin’s fundamental underpinning technologies, such as Mixing and the Bitcoin Wallets but also at the flaws in it.

Spreading codes are the core of the spread spectrum transmission. In this paper, a novel channel-dependent code allocation procedure for enhancing security in multi-carrier code division multiple access (MC-CDMA) system is proposed and investigated over frequency-selective fading. The objective of the proposed technique is to assign the codes to every subcarrier of active/legitimate receivers (Rxs) based on their channel frequency response (CFR). By that, we ensure security for legitimate Rxs against eavesdropping while preserving mutual confidentiality between the legitimate Rxs themselves. To do so, two assigning modes; fixed assigning mode (FAM) and adaptive assigning mode (AAM), are exploited. The effect of the channel estimation error and the number of legitimate Rxs on the bit error rate (BER) performance is studied. The presented simulations show that AAM provides better security with a complexity trade-off compared to FAM. While the latter is more robust against the imperfection of channel estimation.

With the advent of massive machine type of communications, security protection becomes more important than ever. Efforts have been made to impose security protection capability to physical-layer signal design, so called physical-layer security (PLS). The purpose of this paper is to evaluate the performance of PLS schemes for a multi-input-multi-output (MIMO) systems with space-time block coding (STBC) under imperfect channel estimation. Three PLS schemes for STBC schemes are modeled and their bit error rate (BER) performances are evaluated under various channel estimation error environments, and their performance characteristics are analyzed.

In this work, we consider the application of the nonstationary channel polarization theory on the wiretap channel model with non-stationary blocks. Particularly, we present a time-bit coding scheme which is a secure polar codes that constructed on the virtual bit blocks by using the non-stationary channel polarization theory. We have proven that this time-bit coding scheme achieves reliability, strong security and the secrecy capacity. Also, compared with regular secure polar coding methods, our scheme has a lower coding complexity for non-stationary channel blocks.

Blind identification of channel codes is crucial in intelligent communication and non-cooperative signal processing, and it plays a significant role in wireless physical layer security, information interception, and information confrontation. Previous researches show a high computation complexity by manual feature extractions, in addition, problems of indisposed accuracy and poor robustness are to be resolved in a low signal-to-noise ratio (SNR). For solving these difficulties, based on deep residual shrinkage network (DRSN), this paper proposes a novel recognizer by deep learning technologies to blindly distinguish the type and the parameter of channel codes without any prior knowledge or channel state, furthermore, feature extractions by the neural network from codewords can avoid intricate calculations. We evaluated the performance of this recognizer in AWGN, single-path fading, and multi-path fading channels, the results of the experiments showed that the method we proposed worked well. It could achieve over 85 % of recognition accuracy for channel codes in AWGN channels when SNR is not lower than 4dB, and provide an improvement of more than 5% over the previous research in recognition accuracy, which proves the validation of the proposed method.

A new framework is presented in this paper for proving coding theorems for linear codes, where the systematic bits and the corresponding parity-check bits play different roles. Precisely, the noisy systematic bits are used to limit the list size of typical codewords, while the noisy parity-check bits are used to select from the list the maximum likelihood codeword. This new framework for linear codes allows that the systematic bits and the parity-check bits are transmitted in different ways and over different channels. In particular, this new framework unifies the source coding theorems and the channel coding theorems. With this framework, we prove that the Bernoulli generator matrix codes (BGMCs) are capacity-achieving over binary-input output symmetric (BIOS) channels and also entropy-achieving for Bernoulli sources.

The high maneuverability of the unmanned aerial vehicle (UAV), facilitating fast and flexible deployment of communication infrastructures, brings potentially valuable opportunities to the future wireless communication industry. Nevertheless, UAV communication networks are faced with severe security challenges since air to ground (A2G) communications are more vulnerable to eavesdropping attacks than terrestrial communications. To solve the problem, we propose a coding scheme that hierarchically utilizes polar codes in order to address channel multi-state variation for UAV wiretap channels, without the instantaneous channel state information (CSI) known at the transmitter. The theoretical analysis and simulation results show that the scheme achieves the security capacity of the channel and meets the conditions of reliability and security.

In this paper, we studies secure wireless transmission using polar codes which based on self-coupling encryption for relay-wiretap channel. The coding scheme proposed in this paper divide the confidential message into two parts, one part used to generate key through a specific extension method, and then use key to perform coupling encryption processing on another part of the confidential message to obtain the ciphertext. The ciphertext is transmitted in the split-channels which are good for relay node, legitimate receiver and eavesdropper at the same time. Legitimate receiver can restore key with the assistance of relay node, and then uses the joint successive cancellation decoding algorithm to restore confidential message. Even if eavesdropper can correctly decode the ciphertext, he still cannot restore the confidential message due to the lack of key. Simulation results show that compared with the previous work, our coding scheme can increase the average code rate to some extent on the premise of ensuring the reliability and security of transmission.

We study semantic security for classical-quantum channels. Our security functions are functional forms of mosaics of combinatorial designs. We extend methods in [25] from classical channels to classical-quantum channels to demonstrate that mosaics of designs ensure semantic security for classical-quantum channels, and are also capacity achieving coding schemes. An advantage of these modular wiretap codes is that we provide explicit code constructions that can be implemented in practice for every channel, given an arbitrary public code.