Quantum identification system

A secure quantum identification system combining a classical identification procedure and quantum key distribution is proposed. Each identification sequence is always used just once and new sequences are ``refuelled'' from a shared provably secret key transferred through the quantum channel. Two identification protocols are devised. The first protocol can be applied when legitimate users have an unjammable public channel at their disposal. The deception probability is derived for the case of a noisy quantum channel. The second protocol employs unconditionally secure authentication of information sent over the public channel, and thus it can be applied even in the case when an adversary is allowed to modify public communications. An experimental realization of a quantum identification system is described.Comment: RevTeX, 4 postscript figures, 9 pages, submitted to Physical Review

Biometric multimodal security simulation on schedule Ii controlled drug

The paper present a multimodal (multi biometrics) security system focusing on the implementation of fingerprint recognition and facial feature recognition to enhance the existing method of security using password or personal identification number (PIN). This project is operated through a personal computer where all the identification for fingerprint and facial feature are done by using specific software. Successful identification will send a signal through a serial communication circuit and open an application. In this project, the final application should be a cupboard that store and secure schedule II controlled drug in hospital. Due to some problem, the final application was replaced by using a light emitting diode (LED) simulation circuit

Secure ADS-B authentication system and method

A secure system for authenticating the identity of ADS-B systems, including: an authenticator, including a unique id generator and a transmitter transmitting the unique id to one or more ADS-B transmitters; one or more ADS-B transmitters, including a receiver receiving the unique id, one or more secure processing stages merging the unique id with the ADS-B transmitter's identification, data and secret key and generating a secure code identification and a transmitter transmitting a response containing the secure code and ADSB transmitter's data to the authenticator; the authenticator including means for independently determining each ADS-B transmitter's secret key, a receiver receiving each ADS-B transmitter's response, one or more secure processing stages merging the unique id, ADS-B transmitter's identification and data and generating a secure code, and comparison processing comparing the authenticator-generated secure code and the ADS-B transmitter-generated secure code and providing an authentication signal based on the comparison result

Privacy-Preserving Facial Recognition Using Biometric-Capsules

Indiana University-Purdue University Indianapolis (IUPUI)In recent years, developers have used the proliferation of biometric sensors in smart devices, along with recent advances in deep learning, to implement an array of biometrics-based recognition systems. Though these systems demonstrate remarkable performance and have seen wide acceptance, they present unique and pressing security and privacy concerns. One proposed method which addresses these concerns is the elegant, fusion-based Biometric-Capsule (BC) scheme. The BC scheme is provably secure, privacy-preserving, cancellable and interoperable in its secure feature fusion design. In this work, we demonstrate that the BC scheme is uniquely fit to secure state-of-the-art facial verification, authentication and identification systems. We compare the performance of unsecured, underlying biometrics systems to the performance of the BC-embedded systems in order to directly demonstrate the minimal effects of the privacy-preserving BC scheme on underlying system performance. Notably, we demonstrate that, when seamlessly embedded into a state-of-the-art FaceNet and ArcFace verification systems which achieve accuracies of 97.18% and 99.75% on the benchmark LFW dataset, the BC-embedded systems are able to achieve accuracies of 95.13% and 99.13% respectively. Furthermore, we also demonstrate that the BC scheme outperforms or performs as well as several other proposed secure biometric methods

Formation of global regulatory system for human resources development

Focused on evolutionary and continuous human development the global, the regulatory system should be formed in the conceptual (the constant research for the detection, identification and evaluation of global imperatives) and application (development and implementation of activities and coordination tools of influence to ensure the existence of human civilization in a secure politically, economically, socially and environmentally balanced world) planes. On the author's calculations of its formation in functionally complete, holistic view is expected by 2030 due to historically conditioned transformations in the nature of social relations

A novel deep-learning based approach to DNS over HTTPS network traffic detection

Domain name system (DNS) over hypertext transfer protocol secure (HTTPS) (DoH) is currently a new standard for secure communication between DNS servers and end-users. Secure sockets layer (SSL)/transport layer security (TLS) encryption should guarantee the user a high level of privacy regarding the impossibility of data content decryption and protocol identification. Our team created a DoH data set from captured real network traffic and proposed novel deep-learning-based detection models allowing encrypted DoH traffic identification. Our detection models were trained on the network traffic from the Czech top-level domain maintainer, Czech network interchange center (CZ.NIC), and successfully applied to the identification of the DoH traffic from Cloudflare. The reached detection model accuracy was near 95%, and it is clear that the encryption does not prohibit the DoH protocol identification