Zero trust for wireless networks (ZTWN) is a model to ensure that all network traffic, including wireless connections, is considered untrusted and requires authentication and authorization, regardless of the network location or user identity. The infrastructure of zero trust depends on classical cryptographic techniques to guarantee the necessary security measures. Unfortunately, quantum computing has the potential to break many cryptographic techniques, which could compromise the confidentiality and integrity of data transmitted over ZTWN. Therefore, we explored the integration of various quantum components as potential solutions to enhance and achieve the security objectives of ZTWN in the long term. Furthermore, three different quantum machine learning (QML) algorithms have been investigated on two anomaly detection datasets; the achieved accuracies outperform the implemented classical. Quantum identity authentication (QIA) and quantum communication protocols leverage quantum properties, such as quantum entanglement and superposition have been developed to ensure secure and tamper-proof communication between ZTWN entities. The security analysis of the proposed protocols against inside and outside attacks proved that attackers cannot extract any secret information
Zero trust for wireless networks (ZTWN) is a model to ensure that all network traffic, including wireless connections, is considered untrusted and requires authentication and authorization, regardless of the network location or user identity. The infrastructure of zero trust depends on classical cryptographic techniques to guarantee the necessary security measures. Unfortunately, quantum computing has the potential to break many cryptographic techniques, which could compromise the confidentiality and integrity of data transmitted over ZTWN. Therefore, we explored the integration of various quantum components as potential solutions to enhance and achieve the security objectives of ZTWN in the long term. Furthermore, three different quantum machine learning (QML) algorithms have been investigated on two anomaly detection datasets; the achieved accuracies outperform the implemented classical. Quantum identity authentication (QIA) and quantum communication protocols leverage quantum properties, such as quantum entanglement and superposition have been developed to ensure secure and tamper-proof communication between ZTWN entities. The security analysis of the proposed protocols against inside and outside attacks proved that attackers cannot extract any secret information
The quantum Internet promises to revolutionize computing, communications, sensing, and security by leveraging quantum entanglement. In this context, quantum repeaters play a crucial role by performing entanglement swapping to extend entanglement across distant nodes. However, malicious repeaters can retain entangled pairs, enabling man-in-the-middle attacks that compromise security. Quantum Identity Authentication (QIA) protocols aim to mitigate this threat by verifying the legitimacy of communicating parties. However, existing QIA protocols rely on unrealistic assumptions, such as noise-free environments or static noise profiles, that do not reflect the nature of real-world quantum networks. Such noise can cause benign sessions to be flagged as attacks or allow attacks to go undetected. To address these limitations, we propose a machine learning-enhanced QIA framework designed for noisy quantum environments. The protocol performs random authentications during communication sessions using parameters derived from a shared secret key. These parameters determine the preparation and measurement of authentication qubits, known only to legitimate users. A trained machine learning model analyzes physical-layer information (e.g., entanglement fidelity, routing path) and protocol-level data (e.g., basis selection, encoding bit, and measurement outcomes) to detect malicious behavior under fluctuating noise conditions. We evaluate several attack detection models and identify XGBoost as the most effective, achieving 97.18% accuracy and an F1-score of 0.96. The proposed XGBoost-enhanced QIA protocol detects attacks within the first authentication round, achieving a 100% detection and a 1.7% false alarm rate. This reflects a 16.1% improvement in detection rate and a 92.5% reduction in false alarms compared to the entanglement-based QIA benchmark.
The many forms of wireless communication used these days have created a greater demand for strong and flexible cryptographic methods to protect from new security risks that can happen as quantum computing advances.Diffie-Hellman and RSA approaches have been basic to cryptography, but work on these can now be weakened by attack methods such as Shor's and Grover's algorithms following quantum developments which undermines many post-quantum schemes.In our research, we develop a plan using Quantum Machine Learning (QML) to help ensure the security of future wireless networks.As a result, this design pairs quantum theory with reinforcement learning to create strong keys that cannot be accessed by attackers.Value is drawn from quantum entanglement and random measurements of qubits to create key materials needed for physically unclonable keys and at the same time, reinforcement agents support optimizing agreement policies based on variations detected in the channel.Simulations were run using Rayleigh fading and multi-SNR using Qiskit and TensorFlow.The system achieved entropy greater than 95%, agreed on important issues more than 98% successfully and brought latency down to just 0.13 seconds, outshining both classical and post-quantum cryptography in performance, flexibility and safety from attacks.Moreover, the presented encryption solution managed to resist hackers, even if the environment was noisy.As a quantum-AI combination, it is well-positioned to serve as a platform to safely communicate over wireless networks.It builds the basis for examining embedded QML hardware versions of IoT, vehicle networks and smart grid communications, since fast security and reliable performance without high delay are required.
Security is crucial for wireless communication networks, especially as quantum computing advances rapidly. It won’t be long before quantum attacks become feasible, potentially crippling large wireless networks within minutes. Current methods for securing connections and transactions—such as keys, certificates, and data—could be compromised by quantum computers. One concern is the use of fake base stations with stronger signal strengths to lure users into connecting with them in wireless communication network. A quantum-powered attacker could easily break traditional encryption algorithms and launch various attacks almost instantly. An example of this is the "bidding down" attack, where an attacker convinces both the user and network entities that security features are not upheld, despite their actual presence. This type of attack exploits the security weaknesses of older mobile networks. This paper explores security advancements and challenges related to contemporary public key cryptography, including RSA algorithms based on factorization and discrete logarithm problems with Diffie-Hellman and Elliptic-Curve Cryptography (ECC). While these methods provide adequate protection today, quantum computers could potentially break these algorithms or weaken cryptographic keys and hashes within minutes. Quantum cryptography, or quantum-resistant cryptography, objectives to develop algorithms and protocols resilient to quantum computing threats. This paper examines security vulnerabilities in wireless communication networks, focusing on key confirmation and authentication mechanisms. We propose a robust authentication and key agreement protocol for 5G networks using quantum-resistant cryptography. Our proposed protocol, verified with a verification tool, enhances the security of the authentication and key agreement procedures in wireless communication networks.
The emergence of sixth-generation (6G) networks presents a promising paradigm aimed at meeting stringent quality-of-service (QoS) requirements, thereby paving the way for modern applications such as the metaverse. In contrast, the advent of quantum computers poses a significant threat to the security of such networks. However, the quantum Internet signifies a remarkable advancement in communication technology, harnessing the principles of quantum entanglement and superposition to facilitate unparalleled levels of security and efficient computations. Quantum communication can be achieved through the utilization of quantum entanglement. Through the exchange of entangled pairs between two entities, quantum communication becomes feasible, enabled by the process of quantum teleportation. Given the lossy nature of the channels and the exponential decoherence of the transmitted photons, a set of intermediate nodes can serve as quantum repeaters to perform entanglement swapping and directly entangle two distant nodes. Such quantum repeaters may be malicious and by setting up malicious entanglements, intermediate nodes can jeopardize the confidentiality of the quantum information exchanged between the two communication nodes. Hence, this paper proposes a quantum identity authentication protocol that protects quantum networks from malicious entanglements. Unlike the existing protocols, the proposed quantum authentication protocol does not require periodic refreshments of the shared secret keys. Simulation results demonstrate that the proposed protocol can detect malicious entanglements with a 100% probability after an average of 4 authentication rounds. Moreover, the average number of authentication rounds required to detect an attack is reduced by 69% and 76.5% compared with benchmark protocols. Index Terms—Quantum identity authentication, quantum communications, malicious entanglement, quantum security, quantum Internet, 6G.
As sixth-generation (6G) wireless networks come into existence, there is more ever-growing demand for high-speed and secure communication than ever before. Conventional cryptographic methods are facing growing constraints to keep pace with the challenging reality of cyberattacks. Quantum-based communication technologies like quantum key distribution (QKD), quantum encryption, and quantum-resistant protocols provide an inherently secure means of transmitting data. This study examines how quantum communication technologies can be embedded within 6G architectures to provide enhanced data protection. With the help of AI and machine learning, 6G networks are able to anticipate threats and counter them, and quantum technologies offer unbreakable physical-layer encryption. Proposed work examines the security, architectural requirements, and implementation practicalities of this integration. In addition, we discussed the potential effect of quantum computing on present cryptographic techniques and describe future research directions for deployment at scale of quantum-secure communication in next-generation wireless systems.
In the rapidly evolving landscape of cloud computing, ensuring secure user authentication and protection against cyber-attacks has become increasingly critical. This research proposes a novel security framework for cloud systems based on the Quantum Zero-Knowledge Proof (ZKP) technique, aiming to provide a privacy-preserving and quantum-resilient authentication mechanism. The core of the proposed model lies in leveraging photon polarization at specific quantum angles to implement secure and non-disclosive verification, effectively allowing users (provers) to prove their identity without revealing any sensitive credentials. The system's architecture integrates a Zero Knowledge Proof Engine (ZKE), which forms the backbone of the security protocol, enhancing resilience against Denial-of-Service (DoS) and Distributed Denial-of-Service (DDoS) attacks. The quantum properties of photons enable a high level of randomness and unpredictability, significantly improving the robustness of the system. A Python-based simulation environment has been developed to model the proposed engine and conduct experimental validations. Furthermore, a web-based application interface has been designed to facilitate seamless interaction between cloud users and the authentication system, demonstrating real-time threat detection and response. Experimental results, visualized through performance metrics and interface output, confirm the effectiveness and practicality of the proposed model. This approach not only enhances security but also offers a scalable and user-friendly solution for modern cloud environments, marking a significant step toward integrating quantum principles into mainstream cybersecurity infrastructures.