The wide application of face recognition technology in the commercial field puts forward higher requirements for the protection of users' personal privacy data during the recognition process as well as the accuracy of recognition.This paper explains the basic conceptual content of quantum bits and quantum logic gates.Under the theoretical framework, a three-valued XHZ encryption scheme in three-valued quantum states is proposed to complete the construction and optimization of the quantum encryption algorithm.Using the designed quantum encryption algorithm, the public key is generated in the server based on the face feature data, and the private key is used to decrypt in the client, so as to construct the face recognition system based on the quantum encryption algorithm.In the evaluation experiment, the fastest encryption average time is only 2.465ms, and the shortest calculation time for face similarity is only 4.577ms, which shows that the designed system can fully meet the technical requirements of identity authentication while safeguarding the user's personal privacy and security.
The wide application of face recognition technology in the commercial field puts forward higher requirements for the protection of users' personal privacy data during the recognition process as well as the accuracy of recognition.This paper explains the basic conceptual content of quantum bits and quantum logic gates.Under the theoretical framework, a three-valued XHZ encryption scheme in three-valued quantum states is proposed to complete the construction and optimization of the quantum encryption algorithm.Using the designed quantum encryption algorithm, the public key is generated in the server based on the face feature data, and the private key is used to decrypt in the client, so as to construct the face recognition system based on the quantum encryption algorithm.In the evaluation experiment, the fastest encryption average time is only 2.465ms, and the shortest calculation time for face similarity is only 4.577ms, which shows that the designed system can fully meet the technical requirements of identity authentication while safeguarding the user's personal privacy and security.
Face recognition systems are widely used for biometric authentication but face two major problems. First, processing high-resolution images and large databases requires extensive computational time. Second, emerging quantum computers threaten to break the encryption methods that protect stored facial templates. Quantum computers will soon be able to decrypt current security systems, putting biometric data at permanent risk since facial features cannot be changed like passwords. This paper presents a solution that uses quantum computing to speed up face recognition while adding quantum-resistant security. It applies quantum principal component analysis (QPCA) and the SWAP test to reduce the computational complexity and implement lattice-based cryptography, which quantum computers cannot break. Experimental evaluation demonstrates a significant overall speedup with improved accuracy. The proposed framework achieves a significant improvement in performance, provides 125-bit security against quantum attacks and compresses the data storage requirements significantly. These results demonstrate that quantum-enhanced face recognition can solve both the speed and security challenges facing current biometric systems, making it practical for real-world deployment as quantum technology advances.
Specific to security issues concerning identity authentication of mobile applications, a quantum identity authentication protocol based on optical transmission and face recognition is put forward in this paper with consideration of the unconditional security characteristic of quantum key. As for this protocol, optical transmission technology is adopted to acquire quantum key and identity authentication encrypted by quantum key can thus be realized, for which key feature points of face image and user password serve as dual authentication factors. Experimental result and security analysis indicate that this protocol can resist illegal attack and ensure security of identity authentication of mobile applications, which also has great operating efficiency.
A significant problem facing cybersecurity is that most client/server identity authentication schemes depend on computational complexity which is recently challenged by the super exponential computational abilities of quantum computers. Quantum cryptography with its quantum mechanics principles solves this problem and provides mathematically un-hackable secure communication for the quantum computers epoch. Biometric authentication has a big challenge related to its protection as it has to be submitted and stored in encrypted form. Unfortunately, most existing biometric cryptosystems rely on classical cryptography, so they are insecure in quantum era. This problem is solved in this paper by introducing a novel three-factor biometric quantum identity authentication scheme combining something you know (password), something you produce (client’s voice), and something you are (client’s face image) is proposed. The scheme consists of two phases: client enrollment and client login/authentication. The methodology is to use in the enrollment phase, two layers of quantum encryption for the client’s voice signal. Each layer consists of two simple quantum circuits of SWAP and C-NOT quantum gates respectively using a different pseudorandom key obtained from a cellular automata (CA) pseudorandom generator. The proposed scheme has many merits. Firstly, it introduces a new design of muti-factors quantum biometric authentication scheme as the biometric voice data is processed, transmitted, and stored at the server database in an encrypted unconditionally secure quantum form which provides parallel processing, real-time communications, inherent level of security against attacks, tamper-proof security and exponential powerful storage capability due to the quantum properties. Secondly, the proposed scheme achieves double-layers security by combing quantum voice encryption and quantum secure direct communication in one process such that the quantum channel eavesdropper cannot obtain any valuable information in case of information leakage. Thirdly, the distribution and management of encryption key problem is solved as there is no need for key exchange prior to communication. Fourthly, it achieves high communication efficiency as although it is a three-factor biometric identity authentication, only one biometric data is sent in quantum encrypted form to the server. Fifthly, the numerical simulations showed that the proposed scheme has large key space, high key sensitivity and more robust performance against different types of attacks compared to other existing classical and quantum voice encryption schemes. Finally, as an identity authentication method, the proposed scheme achieves identification accuracy of 100% with zero False Rejection Rate (FRR) and zero False acceptance rate (FAR) which is perfect.
Abstract-Surveillance systems have become indispensable across homes, institutions, industries, and public spaces, providing continuous monitoring and ensuring safety. However, as digital threats advance, conventional encryption techniques used in video surveillance are increasingly vulnerable to interception, tampering, and future quantum-based attacks. This paper presents a Smart and Secure Video Surveillance System that integrates deep-learning-based face detection with quantum cryptographic key distribution to safeguard sensitive video data. A YOLOv3-based DCNN model is utilized to detect human faces in each frame. Detected facial regions are then scrambled using a block-based transformation technique to prevent unauthorized recognition. To ensure uncompromised security, encryption keys are generated using a simulated BB84 Quantum Key Distribution (QKD) protocol, offering resistance against eavesdropping and guaranteeing key integrity. The encrypted video is transmitted securely to the monitoring unit, where decryption occurs only with quantum-authenticated keys. Experimental results demonstrate strong privacy protection, robust resistance to key interception, and reliable face detection performance, highlighting the system’s effectiveness in building next-generation, quantum-secure surveillance frameworks. Key Words: Video Surveillance, Quantum Cryptography, QKD, YOLOv3, Face Detection, Secure Transmission, Block Scrambling.
Quantum computing is based on the principles of quantum mechanics and uses quantum bits (qubits) that can exist in a state of superposition and entanglement. They promise a revolution in computing and information security. Firstly, using quantum algorithms in information technology opens up new possibilities for processing and protecting data. Secondly, biometric information security relies on a person's unique physical and behavioural characteristics, such as fingerprints, facial recognition, iris, voice, and others. These methods provide a high level of security due to their uniqueness and difficulty in counterfeiting. Combining the principles of quantum computing and biometric information security allows us to identify their similarities and integration capabilities to create reliable systems for protecting confidential information. While previous research in biometric information security has focused on individual aspects of decision-making to ensure the information security of educational institutions when using facial recognition technologies, this work presents a comprehensive framework combining several components into a single unified system for using various quantum cryptography algorithms. The main advantages of using quantum computing in object and image detection include accelerating the computational process using quantum components, robustness at different object angles, suitability for moving or static conditions, cryptographic noise immunity, and the ability to work in real practical conditions. The advantages of the quantum cryptographic scheme for face recognition technologies include ease of implementation, high cryptography security, the ability to parallelise the processes of encoding and decoding images, and the fact that complex computer equipment is not required. The study results provide a solid foundation for developing hybrid quantum computing and biometric information security technologies. Using the possibility of hybrid computing opens up new horizons for the standardisation and public dissemination of new technologies, and such a combination ensures reliable protection of confidential information and stimulates further research aimed at improving data protection methods in the context of the rapid development of the digital world.
Abstract The exploration of security applications of quantum cryptography for industrial control systems is a key research effort aimed at enhancing the security of industrial control systems through quantum cryptography. In this paper, we study the security threats faced by industrial control systems, including network attacks, data leakage, and system tampering, and propose to utilize quantum key distribution and quantum invisible state transfer algorithms to ensure the secure transmission of industrial control system data. The simulation test environment of the upper and lower computers of the industrial control system is built. The quantum encryption and decryption algorithms are deployed in the embedded environment and PCs to test the effectiveness of quantum cryptography to enhance the advanced encryption standard key scheme. The experimental results show that the quantum cryptography technology successfully realizes the encryption and decryption of data, and the total time consumed in the whole process is less than 61.8 seconds, which meets the requirements of a real-time industrial control system. Therefore, quantum cryptography is suitable for protecting field-level data in industrial control systems.