BC4LLM: Trusted Artificial Intelligence When Blockchain Meets Large Language Models

In recent years, artificial intelligence (AI) and machine learning (ML) are reshaping society's production methods and productivity, and also changing the paradigm of scientific research. Among them, the AI language model represented by ChatGPT has made great progress. Such large language models (LLMs) serve people in the form of AI-generated content (AIGC) and are widely used in consulting, healthcare, and education. However, it is difficult to guarantee the authenticity and reliability of AIGC learning data. In addition, there are also hidden dangers of privacy disclosure in distributed AI training. Moreover, the content generated by LLMs is difficult to identify and trace, and it is difficult to cross-platform mutual recognition. The above information security issues in the coming era of AI powered by LLMs will be infinitely amplified and affect everyone's life. Therefore, we consider empowering LLMs using blockchain technology with superior security features to propose a vision for trusted AI. This paper mainly introduces the motivation and technical route of blockchain for LLM (BC4LLM), including reliable learning corpus, secure training process, and identifiable generated content. Meanwhile, this paper also reviews the potential applications and future challenges, especially in the frontier communication networks field, including network resource allocation, dynamic spectrum sharing, and semantic communication. Based on the above work combined and the prospect of blockchain and LLMs, it is expected to help the early realization of trusted AI and provide guidance for the academic community

Performance Analysis of Non-ideal Wireless PBFT Networks with mmWave and Terahertz Signals

Due to advantages in security and privacy, blockchain is considered a key enabling technology to support 6G communications. Practical Byzantine Fault Tolerance (PBFT) is seen as the most applicable consensus mechanism in blockchain-enabled wireless networks. However, previous studies on PBFT do not consider the channel performance of the physical layer, such as path loss and channel fading, resulting in research results that are far from real networks. Additionally, 6G communications will widely deploy high frequency signals such as millimeter wave (mmWave) and terahertz (THz), while the performance of PBFT is still unknown when these signals are transmitted in wireless PBFT networks. Therefore, it is urgent to study the performance of non-ideal wireless PBFT networks with mmWave and THz siganls, so as to better make PBFT play a role in 6G era. In this paper, we study and compare the performance of mmWave and THz signals in non-ideal wireless PBFT networks, considering Rayleigh Fading (RF) and close-in Free Space (FS) reference distance path loss. Performance is evaluated by consensus success rate and delay. Meanwhile, we find and derive that there is a maximum distance between two nodes that can make PBFT consensus inevitably successful, and it is named active distance of PBFT in this paper. The research results not only analyze the performance of non-ideal wireless PBFT networks, but also provide an important reference for the future transmission of mmWave and THz signals in PBFT networks.Comment: IEEE International Conference on Metaverse Computing, Networking and Applications (MetaCom) 202

ESCM: An Efficient and Secure Communication Mechanism for UAV Networks

UAV (unmanned aerial vehicle) is gradually entering various human activities. It has also become an important part of satellite-air-ground-sea integrated network (SAGS) for 6G communication. In order to achieve high mobility, UAV has strict requirements on communication latency, and it cannot be illegally controlled as weapons of attack with malicious intentions. Therefore, an efficient and secure communication method specifically designed for UAV network is required. This paper proposes a communication mechanism named ESCM for the above requirements. For high efficiency of communication, ESCM designs a routing protocol based on artificial bee colony algorithm (ABC) for UAV network to accelerate communication between UAVs. Meanwhile, we plan to use blockchain to guarantee the communication security of UAV networks. However, blockchain has unstable links in high mobility network scenarios, resulting in low consensus efficiency and high communication overhead. Therefore, ESCM also introduces the concept of the digital twin, mapping the UAVs from the physical world into Cyberspace, transforming the UAV network into a static network. And this virtual UAV network is called CyberUAV. Then, in CyberUAV, we design a blockchain system and propose a consensus algorithm based on network coding, named proof of network coding (PoNC). PoNC not only ensures the security of ESCM, but also further improves the performance of ESCM through network coding. Simulation results show that ESCM has obvious advantages in communication efficiency and security. Moreover, encoding messages through PoNC consensus can increase the network throughput, and make mobile blockchain static through digital twin can improve the consensus success rate

Performance Analysis and Comparison of Non-ideal Wireless PBFT and RAFT Consensus Networks in 6G Communications

Due to advantages in security and privacy, blockchain is considered a key enabling technology to support 6G communications. Practical Byzantine Fault Tolerance (PBFT) and RAFT are seen as the most applicable consensus mechanisms (CMs) in blockchain-enabled wireless networks. However, previous studies on PBFT and RAFT rarely consider the channel performance of the physical layer, such as path loss and channel fading, resulting in research results that are far from real networks. Additionally, 6G communications will widely deploy high-frequency signals such as terahertz (THz) and millimeter wave (mmWave), while performances of PBFT and RAFT are still unknown when these signals are transmitted in wireless PBFT or RAFT networks. Therefore, it is urgent to study the performance of non-ideal wireless PBFT and RAFT networks with THz and mmWave signals, to better make PBFT and RAFT play a role in the 6G era. In this paper, we study and compare the performance of THz and mmWave signals in non-ideal wireless PBFT and RAFT networks, considering Rayleigh Fading (RF) and close-in Free Space (FS) reference distance path loss. Performance is evaluated by five metrics: consensus success rate, latency, throughput, reliability gain, and energy consumption. Meanwhile, we find and derive that there is a maximum distance between two nodes that can make CMs inevitably successful, and it is named the active distance of CMs. The research results not only analyze the performance of non-ideal wireless PBFT and RAFT networks, but also provide important references for the future transmission of THz and mmWave signals in PBFT and RAFT networks.Comment: arXiv admin note: substantial text overlap with arXiv:2303.1575

ESIA: An Efficient and Stable Identity Authentication for Internet of Vehicles

Decentralized, tamper-proof blockchain is regarded as a solution to a challenging authentication issue in the Internet of Vehicles (IoVs). However, the consensus time and communication overhead of blockchain increase significantly as the number of vehicles connected to the blockchain. To address this issue, vehicular fog computing has been introduced to improve efficiency. However, existing studies ignore several key factors such as the number of vehicles in the fog computing system, which can impact the consensus communication overhead. Meanwhile, there is no comprehensive study on the stability of vehicular fog composition. The vehicle movement will lead to dynamic changes in fog. If the composition of vehicular fog is unstable, the blockchain formed by this fog computing system will be unstable, which can affect the consensus efficiency. With the above considerations, we propose an efficient and stable identity authentication (ESIA) empowered by hierarchical blockchain and fog computing. By grouping vehicles efficiently, ESIA has low communication complexity and achieves high stability. Moreover, to enhance the consensus security of the hierarchical blockchain, the consensus process is from the bottom layer to the up layer (bottom-up), which we call B2UHChain. Through theoretical analysis and simulation verification, our scheme achieves the design goals of high efficiency and stability while significantly improving the IoV scalability to the power of 1.5 (^1.5) under similar security to a single-layer blockchain. In addition, ESIA has less communication and computation overhead, lower latency, and higher throughput than other baseline authentication schemes

Numerical and Experimental Investigations on Vocal Fold Approximation in Healthy and Simulated Unilateral Vocal Fold Paralysis

We have developed a novel surgical/computational model for the investigation of unilat-eral vocal fold paralysis (UVFP) which will be used to inform future in silico approaches to improve surgical outcomes in type I thyroplasty. Healthy phonation (HP) was achieved using cricothyroid suture approximation on both sides of the larynx to generate symmetrical vocal fold closure. Following high-speed videoendoscopy (HSV) capture, sutures on the right side of the larynx were removed, partially releasing tension unilaterally and generating asymmetric vocal fold closure characteristic of UVFP (sUVFP condition). HSV revealed symmetric vibration in HP, while in sUVFP the sutured side demonstrated a higher frequency (10–11%). For the computational model, ex vivo magnetic resonance imaging (MRI) scans were captured at three configurations: non-approximated (NA), HP, and sUVFP. A finite-element method (FEM) model was built, in which cartilage displacements from the MRI images were used to prescribe the adduction, and the vocal fold deformation was simulated before the eigenmode calculation. The results showed that the frequency comparison between the two sides was consistent with observations from HSV. This alignment between the surgical and computational models supports the future application of these methods for the investigation of treatment for UVFP