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This article presents a novel network protocol that incorporates a quantum photonic channel for symmetric key distribution, a Dilithium signature to replace factor-based public key cryptography for enhanced authentication, security, and privacy. The protocol uses strong hash functions to hash original messages and verify heightened data integrity at the destination. This Quantum good authentication protocol (QGP) provides high-level security provided by the theory of quantum mechanics. QGP also has the advantage of quantum-resistant data protection that prevents current digital computer and future quantum computer attacks. QGP transforms the transmission control protocol/internet protocol (TCP/IP) by adding a quantum layer at the bottom of the Open Systems Interconnection (OSI) model (layer 0) and modifying the top layer (layer 7) with Dilithium signatures, thus improving the security of the original OSI model. In addition, QGP incorporates strong encryption, hardware-based quantum channels, post-quantum signatures, and secure hash algorithms over a platform of decryptors, switches, routers, and network controllers to form a testbed of the next-generation, secure quantum internet. The experiments presented here show that QGP provides secure authentication and improved security and privacy and can be adopted as a new protocol for the next-generation quantum internet. 

Randomness is integral to computer security, influencing fields such as cryptography and machine learning. In the context of cybersecurity, particularly for the Internet of Things (IoT), high levels of randomness are essential to secure cryptographic protocols. Quantum computing introduces significant risks to traditional encryption methods. To address these challenges, we propose investigating a quantum-safe solution for IoT-trusted computing. Specifically, we implement the first lightweight, practical integration of a quantum random number generator (QRNG) with a software-based trusted platform module (TPM) to create a deployable quantum trusted platform module (QTPM) prototype for IoT systems to improve cryptographic capabilities. The proposed quantum entropy as a service (QEaaS) framework further extends quantum entropy access to legacy and resource-constrained devices. Through the evaluation, we compare the performance of QRNG with traditional Pseudo-random Number Generators (PRNGs), demonstrating the effectiveness of the quantum TPM. Our paper highlights the transformative potential of integrating quantum technology to bolster IoT security. 

In this study, we apply machine learning and software engineering in analyzing air pollution levels in City of Baltimore. The data model was fed with three primary data sources: 1) a biased method of estimating insurance risk used by homeowners loan corporation, 2) demographics of Baltimore residents, and 3) census data estimate of NO2 and PM2.5 concentrations. The dataset covers 650,643 Baltimore residents in 44.7 million residents in 202 major cities in US. The results show that air pollution levels have a clear association with the biased insurance estimating method. Great disparities present in NO2 level between more desirable and low income blocks. Similar disparities exist in air pollution level between residents' ethnicity. As Baltimore population consists of a greater proportion of people of color, the finding reveals how decades old policies has continued to discriminate and affect quality of life of Baltimore citizens today. A QML-based feature mapping is applied on a small dataset. 

The paradigm of quantum computation has led to the development of new algorithms as well variations on existing algorithms. In particular, novel cryptographic techniques based upon quantum computation are of great interest. Many classical encryption techniques naturally translate into the quantum paradigm because of their well-structured factorizations and the fact that they can be phased in the form of unitary operators. In this work, we demonstrate a quantum approach to data encryption and decryption based upon the McEliece cryptosystem using Reed-Muller codes. This example is of particular interest given that post-quantum analyses have highlighted this system as being robust against quantum attacks. Finally, in anticipation of quantum computation operating over binary fields, we discuss alternative operator factorizations for the proposed cryptosystem. 

This paper discusses quantum computing with a strong focus on quantum software, quantum networks, quantum simulation, and applications. The study on quantum speedups reveals fundamental differences between quantum algorithms and classical algorithms. As a case study, further improvement on Shor’s algorithm is presented with experimental results. The study shows that quantum circuits can be generated automatically to further improve the efficiency of quantum algorithms. 

The advancement of quantum mechanics has accelerated the quantum computer architecture and hardware. However, algorithms and implementations to take the full advantage of entanglements provided by quantum devices are still far behind. Quantum cryptography offers the possibility of theoretically perfect security based on the principles of quantum mechanics, ensuring that the presence of an eavesdropper will be detected before any sensitive information is transmitted. However, the relevant technology is still under development – hardware, though commercially available, is still in an immature state, and the protocols used to implement secure communications using that hardware may still be improved. The use of simulations is an important tool for studying quantum cryptography, as they can enable researchers to make valuable insights at a relatively low cost. The data garnered from working with simulations can provide direction for further research both in the development of new communications protocols and in the improvement of actual hardware systems.