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The pharma supply chain comprises various parties including distributors, manufacturers, raw material suppliers, regulators, pharmacies, hospitals, and patients. Due to the product's complexity and transaction flows, an efficient traceability system is needed in the pharma supply chain to identify the current and all previous product owners. Digitizing the track and trace process significantly improves regulatory oversight and guarantees product quality. A distributed platform for shared data that is immutable, trustworthy, accountable, and transparent in the pharmaceutical supply chain could be built using blockchain-based drug traceability. This review aims to shed light on blockchain technology's significance and necessity for pharmaceutical supply chain management systems. A comprehensive literature review was performed between January 2017 and September 2023. The search was conducted to elaborate on blockchain technology. Blockchain is a software-based technology that logs and records transactions using a block structure arranged chronologically. Cryptography technology links and secures these blocks on a peer-to-peer network. Blockchain is anticipated to transform the pharmaceutical supply chain by giving all participants access to a single, straightforward system that provides transparency, security, and oversight of the end-to-end delivery of goods. In all, various literature data were included in this review. Using a supply chain powered by blockchain has many benefits. To begin with, it gives a thorough account of the entire procedure from start to finish. A single piece of software can manage the entire supply chain. Additionally, it increases communication between parties with permission. The enhanced security and traceability that blockchain offers is another important benefit. A blockchain system can track, trace, and recall products. Blockchain-based pharmaceutical supply chain management enables the tracking of medicinal drug transactions from raw materials suppliers to end consumers. The pharma blockchain has the potential to enhance the security, integrity, data provenance, and functionality of the supply chain due to its transparency, immutability, and auditability. [ABSTRACT FROM AUTHOR]

The device-to-device communication (D2D) concept allows direct communication between nearby devices without a base station. At the same time, cellular resources are reused. It reduces the end-to-end delay of D2D active users significantly. Most of the traditional methods consider allocating resources by downlink or uplink alone. The present study considers a novel hybrid approach for joint downlink and uplink to allocate resources, maximizing the network throughput. Further, it minimally restricts cellular and D2D pairs' interference and ensures smooth D2D communication. The challenge is that power control and Quality of service constraints are seriously degraded by strong intra-cell and inter-cell interference due to spectrum reusability and deployment. A hybrid structure that exploits efficient resource allocation is needed to tackle this situation. The optimization problem is formulated as a mixed-integer non-linear problem that is usually NP-hard. Such a problem is divided into two stages, namely channel assignment and power allocation. The factors considered for the objective problem of resource allocation are the transmission power of the cellular user, D2D active user, base station, connection distance, and Quality of Service constraints. The proposed novel hybrid scheme can improve network throughput and improves spectrum efficiency. The numerical results imply that the hybrid method in the proposal functions efficiently and is verified by comparing it with the present joint resource allocation methods. [ABSTRACT FROM AUTHOR]

We investigate the potential and limits of privacy-preserving corporate blockchain applications for information provision. We provide a theoretical model in which heterogeneous firms choose between adopting a blockchain application or relying on traditional third-party intermediaries to inform the capital market. The blockchain's ability to generate information depends on each firm's data profile and all firms' endogenous adoption decisions. We show that blockchain technology can improve the information environment and outperform traditional institutions with firms' adoption decisions serving as a credible value signal and the application uncovering firm values by analyzing all participating firms' data. However, we also characterize an adverse mixed-adoption equilibrium in which neither of the two channels realizes its full potential and information provision declines not only for individual firms, but also in aggregate. The equilibrium is a warning sign that has broad implications for policymakers' regulatory effort and investors' assessment of corporate blockchain applications. This paper was accepted by Suraj Srinivasan, accounting. Funding: B. Franke and Q. Gao Fritz gratefully acknowledge financial support from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) Project-ID 403041268–TRR 266 Accounting for Transparency. A. Stenzel gratefully acknowledges financial support from the DFG through CRC TR 224 (Project C03) during prior employment at the University of Mannheim. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.4718. [ABSTRACT FROM AUTHOR]

Cloud-computing capabilities have revolutionized the remote processing of exploding volumes of healthcare data. However, cloud-based analytics capabilities are saddled with a lack of context-awareness and unnecessary access latency issues as data are processed and stored in remote servers. The emerging network infrastructure tier of fog computing can reduce expensive latency by bringing storage, processing, and networking closer to sensor nodes. Due to the growing variety of medical data and service types, there is a crucial need for efficient and secure architecture for sensor-based health-monitoring devices connected to fog nodes. In this paper, we present publish/subscribe and interest/resource-based non-DHT-based peer-to-peer (P2P) RC-based architecture for resource discovery. The publish/subscribe communication model provides a scalable way to handle large volumes of data and messages in real time, while allowing fine-grained access control to messages, thus enabling heightened security. Our two − level overlay network consists of (1) a transit ring containing group-heads representing a particular resource type, and (2) a completely connected group of peers. Our theoretical analysis shows that our search latency is independent of the number of peers. Additionally, the complexity of the intra-group data-lookup protocol is constant, and the complexity of the inter-group data lookup is O(n), where n is the total number of resource types present in the network. Overall, it therefore allows the system to handle large data throughput in a flexible, cost-effective, and secure way for medical IoT systems.

This article shows how to construct an overlay network of constant degree and diameter O (log n) in O (log n) time starting from an arbitrary weakly connected graph. We assume a synchronous communication network in which nodes can send messages to nodes they know the identifier of, and new connections can be established by sending node identifiers. Suppose the initial network's graph is weakly connected and has constant degree. In that case, our algorithm constructs the desired topology with each node sending and receiving only O (log n) messages in each round in O (log n) time w.h.p., which beats the currently best O (log 3 / 2 n) time algorithm of Götte et al. (International colloquium on structural information and communication complexity (SIROCCO), Springer, 2019). Since the problem cannot be solved faster than by using pointer jumping for O (log n) rounds (which would even require each node to communicate Ω (n) bits), our algorithm is asymptotically optimal. We achieve this speedup by using short random walks to repeatedly establish random connections between the nodes that quickly reduce the conductance of the graph using an observation of Kwok and Lau (Approximation, randomization, and combinatorial optimization. Algorithms and techniques (APPROX/RANDOM 2014), Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, 2014). Additionally, we show how our algorithm can be used to efficiently solve graph problems in hybrid networks (Augustine et al. in Proceedings of the fourteenth annual ACM-SIAM symposium on discrete algorithms, SIAM, 2020). Motivated by the idea that nodes possess two different modes of communication, we assume that communication of the initial edges is unrestricted, whereas only polylogarithmically many messages can be sent over edges that have been established throughout an algorithm's execution. For an (undirected) graph G with arbitrary degree, we show how to compute connected components, a spanning tree, and biconnected components in O (log n) time w.h.p. Furthermore, we show how to compute an MIS in O (log d + log log n) time w.h.p., where d is the initial degree of G. [ABSTRACT FROM AUTHOR]

Conventional loan avenues generally focus more on the formal sector than the unbanked sector. A peer to-peer (p2p) lending platform built on blockchain can help bridge the gap between potential lenders and borrowers in need of money in a secure and decentralized environment. The Ethereum blockchain allows for the creation of smart contracts to perform actions in the network by setting logic rules and conditions thereby removing the need for middlemen and can be inclusive of the unbanked sector. The p2p platform introduces swarm learning for credit scoring, which is a novel methodology that utilizes smart contracts to train decentralized machine learning models. Each training round happens on the local device with the user data, which then exchanges the training parameters and weights to the machine learning model maintained in the smart contract. This allows for preserving the privacy of the user data by ensuring the data never leaves the device but only the inference does. Upon analyzing the user's behavior, a statistical credit score is assessed for validating the chances of the user to default his/her loan repayment. The performance of the proposed model that has been trained using the swarm learning technique is close to the model that had been trained in a centralized environment while overcoming the drawbacks of federated learning by incorporating blockchain and swarm methodology. [ABSTRACT FROM AUTHOR]

Recommender systems make it easier to search with a large amount of content, supplementing or replacing the classic search output with recommendations. In P2P networks, their use can have additional benefits. Because of indexing and search problems, previously added files may not be available to P2P network users. If the user cannot find the file he is looking for, one can provide him with a list of recommendations based on his preferences and search query. The object of research is the process of creating recommendations for users of decentralized P2P networks to facilitate data search. The urgent task of increasing the accuracy of mathematical modeling of recommender systems by taking into account the requirements for reliability and data security during changes in the structure of a decentralized P2P network is solved. An analytical model of the recommender system of a decentralized P2P network has been developed, the main feature of which is taking into account the requirements of reliability and security of recommendation messages. This was done by introducing the following indicators into the general model of the decentralized recommender system – the probability of reliable packet transmission and the probability of safe packet transmission. The developed analytical model makes it possible to conduct a comparative analysis of different methods of operation of recommender systems and to set acceptable parameters under which the degree of relevance does not fall below a certain threshold. The developed mathematical model of the system based on the GERT scheme differs from the known ones by taking into account the reliability and security requirements during changes in the structure of the decentralized P2P network. This has made it possible to improve the accuracy of simulation results up to 5 %. The proposed mathematical model could be used for prototyping recommender systems in various fields of activity. [ABSTRACT FROM AUTHOR]

This work shows the comprehensive model of obfuscation techniques in decentralized peer-to-peer (P2P) network transactions by consolidating a distributed learning approach and blockchain as the backbone technologies. We provide several protocols by utilizing the CryptoNote protocols to be deployed into the Ethereum blockchain environment that can overcome the demerits of most current blockchain systems in terms of traceability and linkability of data flows. The concerns of traceability and linkability of transactions arise since data record breaches have occurred intermittently, where valuable information is often mishandled and misused, inducing a security threat to personal privacy. Furthermore, We thoroughly analyzed the pros and cons of the constructed protocols along with a systematic security evaluation to satisfy the design objectives and requirements. The constructed protocols are unbiased since the observers cannot extract and associate transactional information with any entity. Our assessment and assumptions neglect the hard fork where a radical change in the blockchain network is required for thorough real-world implementation. Finally, the numerical results and symbolic modelling indicate that the proposed protocols fill the gap of the existing model found in the literature. These findings highlight a fresh concept of privacy awareness in decentralized network environments, the properties that most constructions are lacking.

Cloud-computing capabilities have revolutionized the remote processing of exploding volumes of healthcare data. However, cloud-based analytics capabilities are saddled with a lack of context-awareness and unnecessary access latency issues as data are processed and stored in remote servers. The emerging network infrastructure tier of fog computing can reduce expensive latency by bringing storage, processing, and networking closer to sensor nodes. Due to the growing variety of medical data and service types, there is a crucial need for efficient and secure architecture for sensor-based health-monitoring devices connected to fog nodes. In this paper, we present publish/subscribe and interest/resource-based non-DHT-based peer-to-peer (P2P) RC-based architecture for resource discovery. The publish/subscribe communication model provides a scalable way to handle large volumes of data and messages in real time, while allowing fine-grained access control to messages, thus enabling heightened security. Our two − level overlay network consists of (1) a transit ring containing group-heads representing a particular resource type, and (2) a completely connected group of peers. Our theoretical analysis shows that our search latency is independent of the number of peers. Additionally, the complexity of the intra-group data-lookup protocol is constant, and the complexity of the inter-group data lookup is O(n), where n is the total number of resource types present in the network. Overall, it therefore allows the system to handle large data throughput in a flexible, cost-effective, and secure way for medical IoT systems. [ABSTRACT FROM AUTHOR]

Cluster computing has become an inevitable part of data processing as the huge volume of data being produced from different sources like online social media, IoT, mobiledata, sensor data, black box data and so on increases in an exponentially fast manner. Distributed File System defines different methods to distribute, read and eliminate the files among different cluster computing nodes. It is found that popular distributed file systems such as Google File System and Hadoop Distributed File System store metadata centrally. This creates a chance for a Single Point of Failure that arises the need for backup and alternative solutions to recover the metadata on the failure of the metadata server. Also, the name node server is built using expensive and reliable hardware. For small and medium clusters, it is not cost effective to maintain expensive name node server. Even though cheap commodity hardware may substitute the name node functionality, they are prone to hardware failure. This paper proposes a novel distributed file system to distribute files over a cluster of machines connected in a Peer-to-Peer network. The most significant feature of the file system is its capability to distribute the metadata using distributed consensus, using hash values. Although the distributed metadata is visible to the public, the methodology ensures that it is immutable and irrefutable. As part of the in-depth research, the proposed file system has been successfully tested in the Google Cloud Platform. Also, the basic operations like read, write, and delete on Distributed File System with distributed metadata are compared with that of Hadoop Distributed File System based on distribution time on the same cluster setup. The novel distributed file system provides better results compared to the existing methodologies. [ABSTRACT FROM AUTHOR]

Bitcoin is a popular decentralized cryptocurrency, and the Bitcoin network is essentially an unstructured peer-to-peer (P2P) network that can synchronize distributed database of replicated ledgers through message broadcasting. In the Bitcoin network, the average clustering coefficient of nodes is very high, resulting in low message propagation efficiency. In addition, average node degree in the Bitcoin network is also considerably large, causing high message redundancy when nodes use the gossip protocol to broadcast messages. These may affect message propagation speed, hindering Bitcoin from being applied to scenarios of high transactional throughputs. To illustrate, we have collected single-hop propagation data of transactions of 366 blocks from Bitcoin Core. The analysis results show that transaction verification and network delay are two major causes of low transaction propagation efficiency. In this paper, we propose a novel P2P network structure, called local clique network (LCN), for message broadcasting in the Bitcoin network. Specifically, to reduce transaction validation latency and message redundancy, in LCN local nodes (logically) form cliques, and only a few nodes in a clique broadcast messages to the other cliques, instead of each node sending messages to its neighboring nodes. We have conducted extensive experiments, and the results show that message redundancy is low in LCN, and message propagation speed increases significantly. Meanwhile, LCN exhibits excellent robustness when average node degree remains high in the Bitcoin network. [ABSTRACT FROM AUTHOR]

Blockchain technology has a wide range of applicability in the fields of transportation infrastructure construction and maintenance, transportation big data analysis and application, expressway toll collection, and logistics. The core technology lies in the distributed, decentralized, immutable, and programmable features brought about by consensus. This paper studies the dynamic analytical modeling of Proof-Based Consensus (PBC) strategies in blockchain systems, focusing on basic strategies, including Proof of Work (PoW), Proof of Stake (PoS), Proof of Authority (PoA), and Proof of Luck (PoL), which can be extended to other PBC models. We focus on modeling these typical strategies and discuss their solution characteristics in terms of algorithmic mechanisms and principles. The relevant results can be used for quantitative analysis and evaluation of distributed consensus based on the model. [ABSTRACT FROM AUTHOR]

Copyright of Baghdad Science Journal is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Identity Management System (IDMS) refers to how users or individuals are identified and authorized to use organizational systems and services. Since traditional identity management and authentication systems rely heavily on a trusted central authority, they cannot mitigate the effects of single points of failure. As a decentralized and distributed public ledger in a peer-to- peer (P2P) network, Blockchain (BC) technology has garnered a considerable amount of attention in the field of IDMS in recent years. Through Self-Sovereign Identity (SSI), users can have full authority over their digital identity. Successful implementation of a BC-based IDMS can significantly increase the degree of privacy and security of a user’s SSI. However, the integration of BC-based IMDS to provide a user with SSI is still an unorganized area of research in its early stages of development. This article presents an extensive literature review of state-of-the-art academic publications as well as commercial market offerings regarding the applicability of BC-based SSI solutions. It also provides a detailed preliminary regarding the building blocks of blockchain technology and a progressive roadmap of IDMS solutions. In order to develop an effective BC-based IDMS solution that focuses on securing a user’s SSI, this article outline five essential components of a BC-based IDMS: authentication, integrity, privacy, trust, and simplicity. Furthermore, we perform a security analysis that outlines several types of adversarial threats that can cause potential damage to the BC-based IDMS. We identify and discuss associated issues and challenges by analyzing several notable BC-based IDMS solutions in academic literature. We also highlight potential research gaps and provide future research scope.

Aggregators can be effective in organizing distributed energy resources (DERs) for smart grids and electricity markets. The recent development of blockchain and peer-to-peer (P2P) networks provides a new ecosystem for aggregating DERs. Initial studies have mainly used off-the-shelf consensuses, which may struggle to balance node sizes and computational intensities. Moreover, the dynamics of DERs changing their selection among multiple aggregators over time are rarely considered in most related literature. This freedom of selection, which is encouraged by the electricity market, can be better activated by a blockchain. In this study, a game-dynamic-based selection framework for multiple aggregators of DERs is proposed in a decentralized blockchain ecosystem. First, a proof-of-dual-credibility (Po2C) protocol is established so that DERs in such an aggregator can reach consensus. At the same time, for one DER node, both an unavoidable objective credit and a malicious subjective credit constitute its credibility with different weights. Then, a function with triple payoffs motivates DERs in terms of both the physical characteristics of being power supply devices and P2P nodes, the latter including consensus winning and data propagation. Third, the selection game of DERs among aggregators is modeled as an evolutionary game under replicator dynamics to find equilibrium. Numerical simulations with two and four aggregators show general stability in the selection game of DERs. Performance achieved with different consensuses and incentives are compared as well. The framework shows its great potential to organize DERs in a decentralized but aggregated mechanism in open electricity markets.

The strong growth of communication and storage gives rise to the significantly increasing demand for collecting, storing, and sharing a large amount of data on networks. This is further enhanced by the data-driven market, where everyone wants to access other parties' data. Data is the bedrock of today's technologies and researchers, especially in machine learning and deep learning. The business value of organizations is also massively data-dependent. Recent studies and industry applications can apply analytic techniques for exploiting data, or Internet users can exchange data on social networks or peer-to-peer (P2P) networks. However, sharing secured data is a challenging problem that attracts much attention from researchers. Sharing secure data with a group of users using P2P applications faces the unavailability problem of peer nodes. Thus users cannot certify and download the protected data. This affects a P2P-based application class of sharing and storing online services or customer-to-customer e-commerce applications. This article proposes a solution for sharing secured data on P2P-based applications using blockchain and attribute-based encryption. The attribute-based encryption guarantees sharing keys among a group of users, while blockchain guarantees keys distribution. We have simulated the proposed solution on the mobile peer-to-peer network that provides services for sharing and storing data securely.

Blockchains are currently gaining attention as a newly emerging technology in both academia and industry, capable of impacting a variety of domains beyond cryptocurrencies. Performance modeling can be used to provide us with a deeper understanding of the behavior and dynamics within blockchain peer-to-peer networks. Blockchain system architects can leverage network models to properly tune their system and to reduce design costs significantly. In this article, we focus on the original and well-established Bitcoin blockchain network. In particular, we propose a random graph model for performance modeling and analysis of the inventory-based protocol for block dissemination. This model addresses the impact of key blockchain parameters on the overall performance of Bitcoin. We derive some explicit and closed-form equations for block propagation delay and traffic overhead in the Bitcoin network. We also adapt our model to study the impact of deploying a relay network and investigate the effect of the relay network size on the network performance and decentralization. We implement our model using the popular network simulator OMNet++. We validate the accuracy of our theoretical model and its implementation with our dataset mined from the Bitcoin network. Our results show the tradeoff between the default number of connections per node, network bandwidth, and block size in order to compute the optimal block propagation delay over the network. Additionally, we found that bigger relay networks can jeopardize the decentralization of the Bitcoin network. [ABSTRACT FROM AUTHOR]

At present, real estate markets hold and contribute a fair share of the Gross Domestic Product (GDP) of any country. The real estate transactions generate revenue in stamp duties, which goes directly into the government kitty. However, this suffers from land document forgery and fraudulent activities due to a lack of an efficient, distributed, and completely digital system. This paper proposes a blockchain-based framework for digitizing property transactions that mitigate the risk of document forgery and other fraudulent activities. Over time, the amount of these transactions can become overwhelming, thus increasing the number of blocks. The proposed framework is based on blockchain technology to decentralize the complete ecosystem. The framework encompasses all major activities for property transactions. The framework uses the InterPlanetary File System (IPFS) that is a Peer-to-Peer (P2P) swarm network, to integrate different region registry offices in the state/country seamlessly. In order to make it secure, a consensus algorithm is proposed that reduces overhead transmissions for multicasting nodes by about 50%. The message exchange communication overhead also reduces by 54.86%. The time taken for the consensus algorithm is around 53.7% lesser than the Proof-of-Work mechanism in which all nodes participate in consensus and 10% lesser than the existing load-based approach. [ABSTRACT FROM AUTHOR]

The fear that location privacy may be compromised greatly hinders the development of location-based service. Accordingly, some schemes based on the distributed architecture in peer-to-peer network for location privacy protection are proposed. Most of them assume that mobile terminals are mutually trusted, but this does not conform to realistic scenes, and they cannot make requirements for the level of location privacy protection. Therefore, this paper proposes a scheme for location attribute-based security authentication and private sharing data group, so that they trust each other in peer-to-peer network and the trusted but curious mobile terminal cannot access the initiator's query request. A new identifier is designed to allow mobile terminals to customize the protection strength. In addition, the caching mechanism is introduced considering the cache capacity, and a cache replacement policy based on deep reinforcement learning is proposed to reduce communications with location-based service server for achieving location privacy protection. Experiments show the effectiveness and efficiency of the proposed scheme. [ABSTRACT FROM AUTHOR]

Patients and healthcare practitioners are faced with the challenge of accessing, managing, integrating, and sharing health records securely. Patients should be able to manage their health records anywhere in the world, keep track of medical background, give access to data, and share those with any healthcare professional securely. Direct access to data for patients and a more robust data-sharing infrastructure could better prepare the healthcare system to manage public health threats during the emergence of deadly disease outbreak such as COVID-19. Current technologies in use by the healthcare industry do not adequately address these requirements due to limitations related to privacy, security, and full ecosystem interoperability. This paper conducted a literature review to find out the pivotal roles blockchain technology play in solving some of the most critical and challenging issues facing the healthcare industry. This paper identifies challenges and opportunities for implementing blockchain technology in healthcare and summarizes health-related blockchain products and key players offering solutions across different applications. In doing this, our research extends and complements existing blockchain research in healthcare. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Engineering & Applications is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The land registry system is one of the very important revenue generator in any governance system that stores land ownership records. There are various issues and loopholes in the existing system that gives rise to corruption and disputes. The digitization of land records is not sufficient to prevent fraud, time delays, and brokers' involvement. Distributed Ledger Technology can be used to make this digitized record more secure and process it in a decentralized way, reducing paperwork in selling and buying of land. This paper presents a scalable and novel blockchain technology-based land/property registration architecture that utilizes a scalable trust based consensus mechanism, where all registry offices participate in improving the registration process. The framework integrates different state registry offices in the country. This article proposes a secure and efficient consensus mechanism compared to fewer message exchanges with the existing Proof-of-Work algorithm. Hence, this approach requires less time to append the block into the blockchain. Time required for message exchange per consensus is lesser by 59.01% than the PoW mechanism and takes 11% less time than the load-based approach. [ABSTRACT FROM AUTHOR]

Considering data safety in more and more applied peer-to-peer networks, such as wireless sensor networks, has become the focus of information fusion, this paper proposes the problem of credible evidence fusion (CEF) in a distributed system with privacy-preserving, where agent's raw evidence is shared only with authenticated neighbors while access or inference by non-neighbors is prevented. This privacy-preserving in a distributed style brings out two challenges never met in centralized CEF. One is about credibility calculation consensus (CCC), where the local evidence difference measure matrix (EDMM) faces elements missing for evidence unavailability to non-neighbors. The other is about privacy-preserving fusion consensus (PFC), because fusion based on raw evidence may lead to a counter-intuitive result. In CCC, missing elements in EDMM are recovered via low-rank matrix completion, and credibility consistency is further guaranteed via diffusion gradient descent. In PFC, a new measure named privacy iterative compensation term (PICT) is constructed based on credibility and discounted evidence so that raw evidence is impossibly inferred. Furthermore, the linear average consensus based on PICT is presented and proved to be converging to the centralized CEF if credibility is accurately given. The computational complexity is proportional to the cube of the number of agents and the square of the number of elements in the power set of the framework of discrimination. Simulation results demonstrate that the proposed method achieves credibility errors below 0.1, leading to fusion results and classification accuracy approaching those of centralized CEF, with a 30% improvement compared to RANSAC-based and COF-based methods. • A distributed credible evidence fusion method for peer-to-peer networks. • The privacy of raw evidence is protected. • Evidence credibility is computed based on evidence comparison. • Simultaneously conducting credibility estimation and evidence fusion. [ABSTRACT FROM AUTHOR]