Admission control governs Quality of Service (QoS) in cognitive IoT networks (CIoTNs) in which secondary nodes opportunistically share spectrum with preemptive primary users. The optimal policy is of threshold type, but the threshold table is indexed by the 2N fully occupied channel configurations, so both model-free learning and on-chain enforcement scale poorly in N. We show that this table has low intrinsic complexity: across 55 randomised continuous-time Markov decision process (CTMDP) instances, a monotone step function of the aggregate secondary-user drain rate σ(n) carrying only 1.6–2.3 distinct levels reproduces 81–87% of the 2N table entries exactly, the remainder erring by a single queue slot. We give a quasi-static argument for why σ(n) is the right scalar summary. Using this regularity as an inductive bias, an index-pooled Q-learning read-out reduces discounted policy-value loss by up to 4.4× (1.55% to 0.36% at N=4, six seeds) at the largest sample budget, but adds variance and was worse than the per-configuration baseline in one of eight cells; we therefore also specify a deployment gate and report it as untested. We further report a negative result: projecting learned value differences onto the concave cone guaranteed by the structural theorem is inert at N=4 and yields at most a 0.22 percentage-point gain at N=3, because recovery is limited by configuration coverage rather than by shape violation. Finally, we implement Service Level Agreement (SLA) enforcement as a Solidity contract and measure it on a local Ethereum Virtual Machine. Index compression cuts policy-installation gas by 241.8× at N=16 (48.79M to 0.20M gas) and keeps installation in one transaction, but raises the per-decision cost by 14.4–18.4k gas; it is therefore a feasibility mechanism for large N and for frequently re-committed policies, not a uniform improvement.
Shaoyu Li, Hexuan Yu, Shanghao Shi, Md Mohaimin Al Barat · 7 authors
With the growing demand for wireless spectrum, dynamic spectrum sharing (DSS) frameworks such as the Citizens Broadband Radio Service (CBRS) have emerged as practical solutions to improve utilization while protecting incumbent users (IUs) such as military radars. However, current incumbent protection mechanisms face critical limitations. The Environmental Sensing Capability (ESC) requires costly sensor deployments and remains vulnerable to interference and security risks. Alternatively, the Incumbent Informing Capability (IIC) requires IUs to disclose their identities and operational parameters to the Spectrum Coordination System (SCS), creating linkable records that compromise operational privacy and mission secrecy. We propose IU-GUARD, a privacy-preserving spectrum sharing framework that enables IUs to access spectrum without revealing their identities. Leveraging verifiable credentials (VCs) and zero-knowledge proofs (ZKPs), IU-GUARD allows IUs to prove their authorization to the SCS while disclosing only essential operational parameters. This decouples IU identity from spectrum access, prevents cross-request linkage, and mitigates the risk of centralized SCS data leakage. We implement a prototype, and our evaluation shows that IU-GUARD achieves strong privacy guarantees with practical computation and communication overhead, making it suitable for real-time DSS deployment.
Dynamic spectrum sharing (DSS) is essential for 6G networks, yet existing blockchain-based DSS solutions often lack an integrated approach that simultaneously addresses trust, allocation fairness, and system scalability. This paper proposes HierSpectrumChain, a hierarchical blockchain framework that incorporates a global main chain, localized sub-chains, and a smart-contract based Stackelberg auction for credible and automated spectrum allocation. The system model formalizes interactions among spectrum holders, secondary users, and sub-chain validators, enabling transparent bidding and decentralized coordination. A proof-of-concept implementation on an Ethereum Ganache environment evaluates the functional correctness of the auction workflow and measures throughput under varying client loads. While the evaluation is limited to a single-node testbed, the results demonstrate the feasibility of the proposed architecture and establish a basis for future multi-peer experiments on permissioned blockchains. This work provides a coherent design and initial validation for blockchain-enabled DSS in 6G networks.
The symbiotic radio network (SRN) plays a crucial role in green communication solutions by facilitating cooperative communication between devices of primary and secondary links, leading to enhanced transmission quality and optimized resource efficiency. For the joint demodulation of primary and secondary signals, the multiparty trust is essential for operators with different interests. Building multiparty trust in a decentralized manner is challenging for the implementation of the SRN. As an emerging distributed ledger technology, blockchain provides multiparty trust between unreliable devices to share data and resources cooperatively. This paper proposes a consortium Blockchain-based Cooperative Communication scheme for SRN (BCC-SRN), where Hyperledger Fabric is used as the trust anchor with better security, higher throughput, and more flexible organization. In particular, a credit-based incentive mechanism is established to encourage different parties to behave according to the negotiated contracts. The credit is recorded by smart contracts and adjusted based on the contribution of the corresponding cooperators. Simulation results prove that the proposed BCC-SRN is highly effective in improving cooperation security and transmission quality.
The rapid evolution of $\mathbf{6 G}$ communication systems demands artificial intelligence (AI) solutions that are not only adaptive and explainable but also secure and compliant with international standards. A major challenge lies in achieving transparency and regulatory compliance in federated wireless environments while ensuring data privacy and performance. This research introduces a novel architecture that integrates auditable Federated Generative Adversarial Networks (GANs) with explainability frameworks such as SHAP and LIME, supported by a blockchain layer for immutable audit trails and traceable AI decisions across distributed nodes. Smart contracts are employed to enable dynamic policy enforcement and fine-grained access control. The framework is aligned with 3 GPP, ITU-T, and IEEE standards, making it suitable for compliance-driven deployments. Experimental evaluation demonstrates that the proposed architecture enhances model interpretability by up to $81 \%$, reduces security risks through blockchain-based auditing, and maintains competitive performance in key 6 G use cases such as intelligent beamforming, dynamic spectrum allocation, and edge device authentication. The findings confirm that compliant, explainable, and secure AI can be achieved in next-generation wireless networks without compromising efficiency or user trust.
Damla Sarıçelik, Mohaned Chraiti, Albert Lévi, Özgür Erçetin
The Open Radio Access Network (O-RAN) paradigm fosters multi-vendor interoperability, allowing modules from different vendors to cooperatively handle network functions, such as temporary data processing or sensor data collection for network operations optimization. However, this integration agility introduces the risk of selecting suboptimal or adversarial modules, leading to moral hazard. Traditional Moral Hazard testing approaches typically rely on a benchmarking data set in addition to historical performance score. However, they deemed impractical, as vendor-supplied modules may not reveal their outputs before deployment, and the network may lack direct access to reference results for validation. This challenge is further compounded by the dynamic nature of network elements and AI-driven models, whose performance can degrade over time due to malicious tampering, obsolescence, or device deterioration, making historical quality assessments ineffective. In this paper, we address the challenge of identifying legitimate vendor-supplied modules among adversarial ones, with respect to a given network functionality/operation, in the absence of benchmarks. We propose a benchmark-free test framework that detects and eliminates adversarial modules using a methodology inspired by the WereWolf game, combined with zero-knowledge proof techniques. Monte Carlo simulations demonstrate that our approach effectively removes adversarial entities while preserving the privacy of legitimate modules.
Cognitive radio network is prone to many malicious attacks during the process of cooperative spectrum sensing. To overcome this limitation and to efficiently use the spectrum, we incorporate block chain technology in the Fusion center in order to eliminate the malicious users and to maintain only authorized sensing results in the ledger. Fusion center takes the responsibility of smart contract ownership and organizes spectrum sensing effectively. Any malicious attack found during sensing is identified using our proposed algorithm (DETMAL-Detection of malicious users algorithm). This paper proposes a noval algorithm ’DETMAL algorithm’, which is designed in such a way that it can handle both reliant strike and self reliant strike made by the attackers. Detected attackers who are sending falsified reports are removed from the honest local decisions to make an authorised global decision. Legitimate secondary users who are the participants of the smart contract are rewarded with incentives of ethers. DETMAL algorithm shows 12% increased detection probability at 0.1 false alarm probability than the existing algorithm. Results and simulations show that our proposed model outsmarts other existing models in terms of detection probability and accuracy.
One of the greatest ways to guarantee that networks designed for fifth generation (5G) and beyond reach the required levels of spectrum efficiency (SE) is through nonorthogonal multiple access (NOMA). This work presents two new blockchain-based techniques that take advantage of massive multiple input multiple output in a single-cell network to improve performance. NOMA power domain is used in the 5G cooperative cognitive radio network (CCRN) to improve the SE of the downlink. This study investigates a novel cooperative NOMA-based CCRN for underlay spectrum sharing. A cooperative NOMA technique is proposed by considering the access modes of relays and secondary users (SUs) on the secondary network. The proposed system's performance is assessed with respect to random channel characteristics, frequency-selective Rayleigh fading and perfect successive interference cancellation (SIC). The first signal decoded by SU identifies the relay states with the best channel quality between users and the destination users to offset the bit error rate. The throughput dropped during the period because of the perfect SIC. The precise closed-form expressions for the system throughput of the secondary network are derived under the interference constraint of the primary network to evaluate the efficacy of the suggested cooperative strategy. The suggested approaches are assessed under various conditions using the MATLAB application by considering varying transmit power levels, power location coefficients and lengths. In every case, four users are assumed to be using a 90 MHz bandwidth and M-ary Quadrature Amplitude Modulation technology. • Each user (PU and SU) is transformed into blockchain-like blocks that collaborate to create a decentralised network. • The cooperative users' authentication verifies the energy detection technique for spectrum sensing and its results. • Blockchain technology is used to leverage the security of the massive-MIMO network and improve user performance by using digital signatures to confirm PU and MU's identities and preventing MU from using PUs bandwidth. • The identification of an in individual sensing for broadcast channel, cooperative channel for M-MIMO DL PD NOMA with relay CCRN is use to validate the energy detection, throughput, spectrum efficiency, and BER.
Cognitive Radio Network uses the available spectrum resources wisely. Spectrum sensing is the central element of a cognitive radio network. However, spectrum sensing is susceptible to multiple security breaches caused by malicious users. These attackers attempt to change the sensed result in order to decrease network performance. In our proposed approach, with the help of Blockchain-based technology, the fusion center is able to detect and prevent such criminal activities. The method of our model makes use of blockchain-based malicious user detection with SHA-3 hashing and energy detection-based Spectrum sensing. The detection strategy takes place in two stages: Block updation phase and iron out phase. The simulation results of the proposed method demonstrate 3.125%, 6.5% and 8.8% more detection probability at -5 dB SNR in the presence of malicious users, when compared to other methods like equal gain combining (EGC), blockchain based coperative spectrum sensing (BCSS) and fault-tolerant cooperative spectrum sensing (FTCSS) respectively. Thus, the security of cognitive radio blockchain network is proved to be significantly improved.
Litao Ye, Bin Chen, Shrivastava Shivanshu, Chen Sun · 7 authors
Centralized Dynamic Spectrum Sharing (DSS) faces challenges like data security, high management costs, and limited scalability. To address these issues, a blockchain-based DSS scheme has been proposed in this paper. First, we utilize the ERC4907 standard to mint Non-Fungible Spectrum Tokens (NFSTs) that serve as unique identifiers for spectrum resources and facilitate renting. Next, we develop a smart contract for NFST auctions, ensuring secure spectrum transactions through the auction process. Lastly, we create a Web3 spectrum auction platform where users can access idle spectrum data and participate in auctions for NFST leases corresponding to the available spectrum. Experimental results demonstrate that our NFST, designed according to the ERC4907 standard, effectively meets users' secure and efficient DSS requirements, making it a feasible solution.
Cognitive Radio Ad-hoc Networks (CRAHNs) are under constant attacks from compromised primary & secondary nodes. These attacks focus on bandwidth manipulation, internal configuration manipulation, and selective spoofing, which can disturb the normal working of the CRAHNs. Researchers propose various security models to mitigate these attacks, each with limitations. Most of these models have higher complexity, while others cannot be used to mitigate multiple attack types. To overcome these issues while maintaining higher security and Quality of Service (QoS) under attacks, this text proposes a design of a novel blockchain-based security model for improving attack resilience in CRAHNs. The model initially collects multiple information sets from different cognitive radio controllers and creates active & redundant miners for the storage of these sets. The number of active & redundant miners is decided via a Mayfly Optimizer (MO) Model, which assists in improving resource utilization while reducing deployment costs. Cognitive rules and configurations are stored on these nodes and updated via a secure blockchain verification. Due to this, the proposed model demonstrated significant improvements in cognitive radio communications across various metrics, even under different attack scenarios. It reduced communication delay by up to 18.5%, increased communication throughput by up to 19.5%, and improved the Packet Delivery Ratio (PDR) by up to 19.4% when compared with existing models such as SRC [2], Prob Less [4], and DDQL [13]. Additionally, the model achieved energy savings of up to 12.5%. These enhancements were made possible by the optimized selection of miner nodes, enabling quicker mining for high-speed communication, low-energy mining tasks for prolonged use, and high-performance mining for consistency. The results affirm the model’s suitability for various real-time cognitive radio scenarios. Due to the integration of the MO Model, the CRAHN showcases better communication speed, lower energy consumption, higher throughput, and higher packet delivery performance when compared with existing methods under real-time scenarios.
David Cuellar, Muntadher Sallal, Christopher B. Williams
The radio frequency spectrum serves as a fundamental resource for wireless communication, encompassing various frequency bands allocated for diverse services and applications. Dynamic spectrum management (DSM) is essential to optimise the utilisation of this limited and valuable natural resource, with the aim of improving performance and adapting to changing wireless communication demands. Traditional static spectrum allocation methods have shown inefficiencies, leading to spectrum scarcity and under-utilisation. To address these challenges, the integration of blockchain and Cognitive Radio (CR) technologies has emerged as a promising approach. Blockchain, with its decentralised and secure attributes, can improve transparency and trust in spectrum allocation processes, while CR enables intelligent spectrum sensing and allocation to maximise utilisation. However, this promising approach comes with its own critical challenges, especially when dealing with the 6th Generation (6G) mobile communication. These challenges are related to the fact that the blockchain ecosystem needs to be interoperable and scalable enough to be compatible with the 6G high-demand and substantial resources. Specifically, integrating blockchain with CR requires efficient interoperability techniques where blockchain can easily and effectively interact with the CR platforms as well as radio spectrum environments. Furthermore, the spectrum management system over 6G networks needs to be designed in a way where massive 6G resources can be accommodated and managed without having any service performance degradation. This paper introduces a novel radio spectrum management model in 6G networks, named as BSM-6G, which integrates blockchain technology with CR where interoperability is preserved and scalability is maximised. Specifically, the proposed BSM-6G model merges blockchain’s transparent record keeping with CR’s intelligent spectrum management capabilities. To overcome the interoperability issue, BSM-6G provides an interoperable blockchain Oracle approach which facilitates the real-time interaction among the blockchain platform, the CR, and any data sources off-chain. This paper details all the technical and procedural challenges when implementing the proposed interoperability Oracle approach. To address the scalability challenge, BSM-6G utilizes the Proof-of-History (PoH) consensus protocol to align with the requirements of DSM in advanced networks like Beyond 5th Generation (B5G) and 6G. Evaluation results indicate that BSM-6G offers viable and less complex blockchain Oracle integration architecture measured by the technical implementation of BSM-6G, as well as low interoperability cost measured by transaction response time and transaction fee cost. Compared to state-of-the-art spectrum-based blockchain systems, BSM-6G shows a high scalable DSM-based blockchain in 6G networks measured by transactions per second (TPS).
The rapid increase in mobile users, the IoT, and data-hungry applications have brought forth unprecedented demand on the spectrum, which is scarce; on top of that, the existing static spectrum allocation schemes have resulted in a heavily underutilized spectrum which can be mitigated with a Dynamic Spectrum Access (DSA) scheme with unlicensed users gaining access to the idle spectrum bands of licensed spectrum users opportunistically. Such a DSA and Dynamic Spectrum Management (DSM) scheme would significantly increase spectral efficiency while facilitating new services and applications beyond 5G (B5G) networks. Even with access to new spectrum bands like terahertz (THz) and Visible light communication and enabling technologies such as Software Defined Networks (SDN) and Cognitive Radio (CR), implementing a fully realized DSM requires rapid sensing, coordination, and management, and sharing of idle spectrum bands in a fair manner while preserving the security and privacy aspects, limiting interferences. With their decentralized, immutable nature, blockchains promise the execution of spectrum access and sharing in a fully transparent, fair manner while preserving privacy and security. Furthermore, blockchain-based Smart Contracts (SCs) allow automation of DSM, cryptocurrencies, and tokens to facilitate the trading of spectrum and related resources. In addition to that, blockchains act as an interface for integrating AI and Machine Learning (ML) techniques into DSM, which provides a certain level of intelligence to the underlying architecture. Although several attempts have been carried out to analyze the research gaps in DSM, a comprehensive analysis addressing the blockchains as the primary solution to address DSM has not been carried out. In this survey, we address the potential of a blockchain-based approach toward realizing a decentralized DSM while presenting future directives to improve the use of blockchains for DSM.
Ruiquan Lin, Fushuai Li, Jun Wang, Jinsong Hu · 6 authors
The high-speed movement of Vehicle Users (VUs) in Cognitive Internet of Vehicles (CIoV) causes rapid changes in users location and path loss. In the case of imperfect control channels, the influence of high-speed movement increases the probability of error in sending local spectrum sensing decisions by VUs. On the other hand, Malicious Vehicle Users (MVUs) can launch Spectrum Sensing Data Falsification (SSDF) attacks to deteriorate the spectrum sensing decisions, mislead the final spectrum sensing decisions of Collaborative Spectrum Sensing (CSS), and bring serious security problems to the system. In addition, the high-speed movement can increases the concealment of the MVUs. In this paper, we study the scenario of VUs moving at high speeds, and data transmission in an imperfect control channel, and propose a blockchain-based method to defend against massive SSDF attacks in CIoV networks to prevennt independent and cooperative attacks from MVUs. The proposed method combines blockchain with spectrum sensing and spectrum access, abandons the decision-making mechanism of the Fusion Center (FC) in the traditional CSS, adopts distributed decision-making, and uses Prospect Theory (PT) modeling in the decision-making process, effectively improves the correct rate of final spectrum sensing decision in the case of multiple attacks. The local spectrum sensing decisions of VUs are packaged into blocks and uploaded after the final decision to achieve more accurate and secure spectrum sensing, and then identify MVUs by the reputation value. In addition, a smart contract that changes the mining difficulty of VUs based on their reputation values is proposed. It makes the mining difficulty of MVUs more difficult and effectively limits MVUs' access to the spectrum band. The final simulation results demonstrate the validity and superiority of the proposed method compared with traditional methods.
In cognitive radio networks, cooperative spectrum sensing (CSS) is a key approach to effectively discover spectrum opportunities for secondary users. However, due to the presence of malicious nodes, CSS faces significant challenges in the trust issue of sensing results caused by spectrum sensing data falsification and the privacy leakage of sensing nodes. In this article, we develop a trustworthy and privacy-preserving CSS solution based on blockchain, TaP2-CSS. It achieves the transparency and trustworthiness in exchanging and fusing sensing reports and preserves privacy of sensing nodes. More specifically, a fusion scheme is proposed to realize the high defense capability against the spectrum sensing falsification attack launched by lurking and persistent malicious nodes. Furthermore, to address privacy threats of sensing nodes, we propose a privacy-preserving sensing scheme based on dynamic sensing time for resource-constrained sensing nodes. It effectively limits the location information leaked by sensing reports without the need for complex cryptographic computation and protocol interaction. Comprehensive evaluation and comparison show that the proposed solution achieves high sensing accuracy in the presence of malicious nodes while preserving the privacy of sensing nodes.
Nischal Aryal, Fariba Ghaffari, E. Bertin, Noël Crespi
The Open Radio Access Network (O-RAN) introduces openness and intelligence into the existing, tightly-coupled RAN ecosystem. Openness promotes collaboration among various vendors to provide diverse components (hardware, software, or both) for the RAN ecosystem, while intelligence handles complex network activities using Artificial Intelligence (AI). Although O-RAN design addresses many issues in traditional RANs, such as vendor lock-in, lack of flexibility, and limited innovation, it raises several management and security concerns related to collaboration, access management, privacy, trust, and availability. Distributed Ledger Technologies (DLTs) offer a viable method of establishing trust among entities, managing resources efficiently, and automating complex network tasks. Several DLT properties, such as distributed architecture, high automation through smart contracts, immutability, and transparency, could position DLT-based ideas as game changers in a multi-vendor O-RAN ecosystem. Furthermore, this technology has the potential to introduce new business models and establish secure and trusted micro-payments among vendors and network participants. In this paper, we first present a taxonomy for discussing existing O-RAN challenges. Based on the taxonomy, we then examine the possibility of incorporating DLT-based solutions in O-RAN architecture to address these challenges.
I Evelyn Ezhilarasi, J. Christopher Clement, Joseph M. Arul
Abstract Cognitive radio network is a promising technology to enhance the spectrum utilization and to resolve the spectrum scarcity issues. But the malicious users play havoc with the network during spectrum sensing and demean the network performance. It is mandatory to identify such malicious attacks and address it. There have been many traditional methods to mitigate the cognitive radio network attacks. In this paper, we have surveyed advanced attack mitigation techniques like machine learning, deep learning and blockchain. Thus, by detecting and addressing the malicious activities, the throughput and overall network performance can be improved.
The future of communication technology is moving from 5G to 6G with new innovations. Blockchain (BC) is a such immersive technology that significantly impacts the betterment of communication technology. BC-based spectrum-sharing solutions can be used in Dynamic Spectrum Access (DSA) systems to fulfill the need for secure and efficient communication. With the invention of cognitive radio networks, DSA became a popular topic for the scientific community. Spectrum misuse/violations can occur due to the rapid growth of spectrum sharing. As the system is open to malicious attacks, licensed spectrum owners must be identified and verified. However, the existing BC-based DSA solutions are more expensive, non-optimized, and lack spectrum misuse detection. This paper proposes a novel consensus algorithm called “Proof of Equation” for spectrum misuse detection. The core of the proposed algorithm is a consensus score calculation based on a numerical equation with three parameters rather than using cryptographic calculations. The performance of the proposed algorithm is studied using Python simulations, and simulation results show that the proposed algorithm outperforms the Proof of Work (PoW) and Proof of Stake (PoS) consensus algorithms in terms of block production time.
As the scarcity of spectrum resources, especially in mid-band (1 to 6 GHz), becomes more significant in beyond 5G and 6G era, spectrum sharing is promising to solve this problem. Various spectrum sharing approaches have been proposed and standardized, such as centralized geolocation database. The emergence of blockchain technology provides a great solution to enhance spectrum sharing technology in a decentralized way. With blockchain technology, trust can be established among multiple public or private wireless networks owned by different operators. Moreover, decentralized ledgers can reduce the number of transactions and validation processes executed by each node, thereby improving spectrum trading efficiency. In this article, we summarize the standardization progress of spectrum sharing and the application of blockchain in wireless communications. Then, we investigate the key issues encountered by blockchain-based spectrum sharing and propose potential solutions to these problems. Finally, we present future research directions for blockchain-based dynamic spectrum sharing.
Cognitive radio networks allow opportunistic spectrum access to the unlicensed users, which rely on effective spectrum sensing. Recently, cooperative sensing has been found to improve sensing reliability. However, sometimes the selfish users do not cooperate, and therefore, different incentive design mechanisms like contract theory have been proposed recently, where the cooperation is encouraged by offering appropriate reward to the sensing participants. However, still no secure structure exists for the reward distribution after a successful contract completion, and a user may also deny sensing even after accepting the contract. This work proposes the use of blockchain-based smart contracts, which are based upon a permissioned blockchain that helps in making the transactions private among the participants. Further, the efficiency of this approach is improved by introducing a reputation parameter for the users. This measures the trustworthiness of a particular user based upon the accuracy of their recent sensing results. Further, a money locking approach is proposed from which a penalty is deducted if the user denies or fails to submit a correct reading. Performance analysis of the proposed scheme is done to show the superiority of the scheme.
Abstract In this article, the authors proposed a novel blockchain‐oriented location privacy‐preserving (BoLPP) for the Cooperative Spectrum Sensing (CSS) in 6G networks. In order to attain the sustainability of privacy and security for 6G wireless networks, it is a great challenge in this sensing as it faces various malicious attacks while the secondary user (SU) is active. To tackle these issues, the authors proposed a novel framework for blockchain‐oriented Cognitive Radio Networks (CRNs) for CSS using an energy detection technique. Moreover, the authors implemented another novel paradigm BoLPP, to attain the privacy of SUs location for CSS in 6G networks. This approach preserves the SUs’ location and makes the BoLPP framework immune to all malicious attackers. The simulation results have been undergone based on the performance metrics such as response time, consistency, probability of false alarm, frame loss (%), average network throughput, energy efficiency, and security. The outcomes reveal that the proposed scheme achieves high security, privacy, energy efficiency, average network throughput, and low probability of false alarm and frame loss (%) when compared with the existing frameworks such as Friend or Foe (FoF) and Tidal Trust Algorithm (TTA) mechanisms. It is observed that the proposed BoLPP mechanism provides better security and privacy in 6G wireless networks.