The fifth generation (5G) of mobile networks represents a major advancement over previous wireless technologies to deliver ultra-fast data transmission, low latency, and massive connectivity. 5G technologies provide a highly reliable, scalable, and flexible communication for modern social media applications. 5G allows users to stream high-definition videos, live broadcasts, and interactive content with lesser buffering. Moreover, due to massive connectivity of users and devices interact simultaneously in social media platforms, latency and high reliability also major concern. 5G networks incorporate advanced technologies to ensure high Quality of Service (QoS) for social media streaming. Many researchers carried out their research on secured data transmission in 5G network. But the data confidentiality rate has not been significantly improved, and end-to-end delay has not been reduced. To enhance the QoS-Aware Reliable and Scalable data Transmission in 5G Network, a new method named Discriminative AI Transient Quantum Signcryption Cryptography (DAITQ- SigCrypt) method is introduced. The designed DAITQ- SigCrypt method simultaneously achieves both security and QoS aware data transmission in social media streaming data transmission. The discriminative AI model is a used for analyzing the each device’s resources such as bandwidth, signal strength and SINR. Next, identifies resource-efficient devices to achieve the QoS optimized data transmission. During the data transmission, reliability is achieved using Transient Quantum Signcryption Cryptography to deliver data accurately and securely, ensuring that information reaches the authorized receiver without loss, corruption, or unauthorized access. By this way, DAITQ- SigCrypt method achieved Reliable and QoS optimized data transmission. Experimental evaluation of proposed DAITQ- SigCrypt method is carried out with respect to the different performance metrics such as data delivery rate, data loss rate, throughput, latency, jitter, confidentiality rate, integrity rat with respect to number of streaming data samples. Quantitative results reveal that DAITQ- SigCrypt method significantly enhances streaming data communication in 5G networks, achieving higher throughput, data delivery, confidentiality and integrity with lower latency, jitter and packet loss compared to existing methods.
The fifth generation (5G) of mobile networks represents a major advancement over previous wireless technologies to deliver ultra-fast data transmission, low latency, and massive connectivity. 5G technologies provide a highly reliable, scalable, and flexible communication for modern social media applications. 5G allows users to stream high-definition videos, live broadcasts, and interactive content with lesser buffering. Moreover, due to massive connectivity of users and devices interact simultaneously in social media platforms, latency and high reliability also major concern. 5G networks incorporate advanced technologies to ensure high Quality of Service (QoS) for social media streaming. Many researchers carried out their research on secured data transmission in 5G network. But the data confidentiality rate has not been significantly improved, and end-to-end delay has not been reduced. To enhance the QoS-Aware Reliable and Scalable data Transmission in 5G Network, a new method named Discriminative AI Transient Quantum Signcryption Cryptography (DAITQ- SigCrypt) method is introduced. The designed DAITQ- SigCrypt method simultaneously achieves both security and QoS aware data transmission in social media streaming data transmission. The discriminative AI model is a used for analyzing the each device’s resources such as bandwidth, signal strength and SINR. Next, identifies resource-efficient devices to achieve the QoS optimized data transmission. During the data transmission, reliability is achieved using Transient Quantum Signcryption Cryptography to deliver data accurately and securely, ensuring that information reaches the authorized receiver without loss, corruption, or unauthorized access. By this way, DAITQ- SigCrypt method achieved Reliable and QoS optimized data transmission. Experimental evaluation of proposed DAITQ- SigCrypt method is carried out with respect to the different performance metrics such as data delivery rate, data loss rate, throughput, latency, jitter, confidentiality rate, integrity rat with respect to number of streaming data samples. Quantitative results reveal that DAITQ- SigCrypt method significantly enhances streaming data communication in 5G networks, achieving higher throughput, data delivery, confidentiality and integrity with lower latency, jitter and packet loss compared to existing methods.
Internet of Things (IoT) is growing, leading to enhanced data exchange in several areas. Achieving maximum security in the IoT environment is still under the open research. Protecting the confidential data from the external environment in complication for the applications of IoT network. For that purpose, in this article presents a Quantum Computing-Based Cryptography Model with Task Offloading and Data Management (QCCTOD) designed to enhance security and efficiency in IoT networks. It consists of a three-tier architecture, which includes a perceptual tier for data gathering, a network tier that incorporates lightweight cryptography to ensure secure data transmission via sophisticated signature methods to avert data modification, and an application tier for smart decision-making. An intelligent caching system that stores commonly used services from E-APs, improving service provision. The communication model uses an enhanced method for SINR to guarantee swift and effective data transfer while maintaining Quality of Service (QoS). The task offloading process shifts demanding computing tasks from devices with constrained resources to edge servers. This method evaluates energy and latency expenses to find equilibrium between computation and transmission lags, reducing power usage and improving efficiency for IoT applications. A lightweight bio-latticed cryptographic addresses IoT security for the post-quantum era, utilizing methods like the Shortest Vector Problem (SVP) and Galois field computations. The implementation of the proposed QCCTOD is carried out in python and the parameters which are measured to validate the network performance are include signature size analysis, throughput, packet success rate, energy consumption, and network usage. From the final comparison it is proven that the proposed QCCTOD attain better overall performance in terms of network security and data management.
Quantum secure direct communication (QSDC), a vital branch of quantum communication, enables reliable, secure transmission under harsh conditions of high channel noise, large optical loss and stringent security constraints. Having undergone field trials and practical deployment, QSDC serves as a promising candidate for confidential transmission in ultra-high-security scenarios. Modern society relies heavily on ubiquitous communication, and 5G mobile networks have achieved rapid development and widespread commercialization in recent years, driving growing demands for robust 5G security. This paper proposes a QSDC-5G integrated secure transmission architecture to safeguard 5G data delivery. The solution maintains full compatibility with legacy classical networks while satisfying long-term security requirements for future communications. Laboratory simulation and stability tests were conducted on the proposed converged security network. Continuous 24-hour measurements demonstrate that the integrated network achieves an interface throughput of 12 kbps with a round-trip latency below 3500 ms. These key metrics satisfy the signaling transmission demands for single mobile terminal authentication when accessing private networks via base stations, laying a solid foundation for deep integration of QSDC into 5G systems.
The fast growth of Internet of Things (IoT) networks has heightened the demand for secure, scalable and energy efficient communications methods. Traditional cryptographic techniques are more susceptible to quantum computing attacks and therefore have pushed the necessity for quantum secure methods. This study presents an energy efficient artificial intelligence assisted quantum secure communication framework designed to scale and provide reliable IoT networks. The framework uses Quantum Key Distribution (QKD) combined with deep learning optimization to improve both relationship and network performance. A self-adaptive AI module applies its lower level of computational resources and dynamically changing network conditions in order to optimize key management, routing decisions, and resource allocation, which reduces both energy consumption and communication latency. The proposed system is intended to support the specific types of constraints faced within an IoT environment. The experimental simulation results demonstrate that the framework improves energy efficiency, increases packet delivery ratio, and decreases latency in IVN (Intelligent Vehicular Networks) by comparison with traditional means of secure communication. In addition, by combining AI and quantum communications, we increase our resilience to threats posed by both classical and quantum forms of attack while providing an added layer of protection for transmitting data between devices in future wireless networks. Additionally, this proposed framework will provide a very scalable and effective method for providing IoT solutions within the environment of 5G mobile networks or later generations.
Even though India’s telecom industry is rapidly transitioning to 5G, users continue to encounter uneven speeds, latency spikes, and dropped calls. Concerns regarding data security are also growing at the same time. This chapter explores the ways in which quantum interventions, such as quantum key distribution (QKD), post-quantum cryptography (PQC), and quantum/quantum-inspired network optimization, can improve perceived service quality as well as objective quality of service (QoS). We only use secondary data, such as user-experience metrics from Opensignal (June 2025) and city-level QoS from TRAI Independent Drive Tests (May 2025). We also define an operator-level Quantum Readiness Index based on public pilots and existing standards. We present the QASQ—Quantum-Assured Service Quality model, which builds upon SERVQUAL and UTAUT-3. According to the model, perceived assurance and responsiveness → trust, satisfaction, and loyalty → quantum readiness → QoS outcomes (call drops, latency/jitter, throughput stability, CSSR). Descriptive comparisons, basic correlations, and fixed-effects regressions at the operator × city level, with an optional composite path view for reporting, comprise our transparent and reproducible analysis plan. The data shows where quantum levers can provide the biggest service gains and where performance dispersion is highest. The chapter offers a framework tailored to India, a clean measurement recipe utilizing publicly available datasets, and a workable pilot roadmap (including metro QKD routes, quantum-inspired optimization on known pain corridors, and crypto-inventory and PQC migration). The objective is simple: increase security and dependability in ways that consumers can relate to and trust.
The Service-Based Architecture (SBA) of the fifth generation (5G) of cellular networks introduced great advancements in flexibility, efficiency, and performance of modern networks, thanks to the distribution and softwarization of core network entities called Network Functions (NFs). Due to the distributed nature of 5G systems, these NFs are usually located in different sites to provide better Quality of Service (QoS) or specific services, which poses a great challenge regarding security. However, even though the 3GPP standard identifies security requirements by leveraging Transport Layer Security (TLS) authentication and OAuth2.0 authorization, current experimental and commercial deployments often disregard these aspects for the sake of simplicity and performance. In fact, even though data and communication protection is crucial, the implementation of security protocols and mechanisms complicates the deployments and may reduce the efficiency of 5G systems. This paper presents a novel solution that implements TLS for authentication and encryption leveraging entanglement-based Quantum Key Distribution (QKD), ensuring that all the communications between NFs in the 5G core network are secured by QKD keys, and are therefore quantum-safe. Additionally, this paper presents a QKD key repository using the Network Repository Function (NRF), which stores and relays TLS session keys to authenticated consumer NFs to access producer NFs in a fast but quantum-safe process. The solution was validated in a real hardware environment, and obtained results demonstrate that the proposed solution enhances the security of the SBA communications in an efficient way, reducing an 85% the service request time compared to the traditional TLS-based procedure, as well as 29.96% fewer bytes transmitted throughout the process.
The integration of quantum communication principles with 5G technology presents a groundbreaking approach to addressing the growing demand for high-speed, secure, and resilient communication systems. This paper proposes a Quantum-Driven Hybrid Network Architecture that leverages Quantum Key Distribution (QKD) for unparalleled security and combines it with 5G's ultra-fast data transmission capabilities. The architecture integrates key components such as QKD modules, 5G infrastructure, and edge computing, organized into a layered framework comprising quantum, network control, and application layers. Simulation results demonstrate significant improvements in throughput (up to 23.5%), latency reduction (up to 25%), and error rate reduction in high-noise environments (from 0.25% to 0.05%). The proposed system also exhibits enhanced security, achieving a 100% success rate in mitigating eavesdropping and man-in-the-middle attacks. Using resource-efficient mechanisms, the hybrid network achieves an overall accuracy of 97.8% in secure and resilient data transmission. This work validates the potential of quantum-enhanced 5G systems to meet the challenges of future communication networks.