Peer Nodes Research Articles

A decentralized authentication scheme for smart factory based on blockchain

The Industrial Internet of Things (IIoT) is recognized as one of the revolutionary technologies driving smart manufacturing and improving productivity. As manufacturing processes grow increasingly intricate, the entire manufacturing ecosystem encompasses multiple managed IoT domains. Within this highly interconnected environment, devices from diverse domains must collaborate, leading to considerable apprehensions about the security and privacy of device-to-device communications. Current authentication methods encounter several challenges. Traditional authentication schemes overly rely on trusted third parties, rendering them susceptible to external attacks or internal spoofing. This susceptibility gives rise to a range of security and privacy concerns. In response to these challenges, this paper aims to contribute to a more secure and efficient service scheme for smart factories by devising a blockchain-based distributed IoT architecture. The proposed scheme introduces a federated blockchain to establish trust among different domains, thereby enabling secure connections between devices in distinct domains. Through security analysis, it is proved that the proposed authentication scheme has integrity, mutual authentication, scalability, and resistance to four attacks. Furthermore, efficiency analysis experiments show that our scheme is feasible for smart factories, and as the number of peer nodes increases, the performance and efficiency of the blockchain network become better.

Local clustering coefficient-based iterative peeling strategy to extract the core and peripheral layers of a network

We propose a novel local clustering coefficient (LCC)-based strategy to extract the peripheral layers of a complex network and identify the nodes that be part of one of these layers as well as those that would form the core of the network. The LCC of a node is the probability that any two neighbors of the node are connected. Our hypothesis is that for any given network topology, nodes with a LCC of 1.0 ideally suit to the role of peripheral nodes. We propose an iterative peeling strategy wherein we remove the nodes with a LCC of 1.0 (the LCC values of the residual nodes are recalculated after each iteration) to extract the peripheral nodes at a particular layer (starting from the outermost peripheral layer to the innermost peripheral layer) and penetrate towards the inner core. We stop the iterative peeling when all the residual nodes (left over nodes in the network after the removal of the nodes at the peripheral layers) have a degree of 0 or the LCC values of all the non-zero degree residual nodes are less than 1.0. We show that the proposed LCC-based iterative peeling strategy has the potential to envision an inner most single-layer core and a hierarchical (one or more peripheral layers) peripheral structure for scale-free networks and a single layer of peer nodes (all nodes have a LCC of less than 1.0) for random networks.

IoT based Efficient and Secure Building Architecture with Constrained Application Protocol (CoAP)

The Internet of Things (IoT), one of the newest technologies, has great potential for many industry businesses. Smart building technology is one of the biggest IoT industries. IoT is used on a regular basis in many different industries. It is used in a variety of contexts, including physical defense, e-health, smart buildings, grids, cities, homes, asset management, and transportation management. IoT-level, networked smart buildings offer affordable assistance. Comfort, accessibility, security, and energy management are necessary for commercial space. Naturally, IoT-based solutions can satisfy these requirements. With the depletion of the energy supply and the increase in demand for energy, there has been a growing focus on energy usage and building maintenance. This paper uses emerging IoT technology to demonstrate a smart building design that is both safe and energy-efficient. Constrained Application Protocol (CoAP) is a crucial internet transmission protocol that assigns a unique address to every device. Data is transferred using this application layer protocol outside of secure channels. While there are several recommended techniques to protect sensitive data transfer, one likely way to improve the security aspect of CoAP for authentication and end-to-end security is through the use of Datagram Transport Layer Protection (DTLS).This paper propose a smart building design in which the Internet of Things is used to control the operation of all technological components. The simulation results show that compared to the situation of employing Message Queuing Telemetry Transport (MQTT), adopting CoAP in a smart building saves energy use by around 34.86%. In order to increase security in a smart building, this article also explains how to include the DTLS protocol inside of CoAPutilising enhancements from the Certificate Authority (CA).Finally, using the ContikiCooja (CC) simulator to simulate system performance and data collecting in terms of latency, throughput, and resource consumption, CoAP is utilized to modify orderer and peer nodes for performance research in smart building.

INSURANCE CLAIMS PERFORMANCE IMPROVEMENT USING BLOCKCHAIN

In this work focused the application of blockchain technology in insurance claims. There are four parties involved in insurance claim process, the police, insurance, workshop, and retail shop. Additionally, every participant will have a peer node of their own. The insurance firm that insurances the products and handles claim handling is known as the insurance peer. It is the duty and responsibility of the police peer to confirm the theft allegations. While re peer offers the products to customers, repair shop peer is in charge of product repairs. Operating this network on the IBM (International Business Machines) Blockchain Platform has the advantage of allowing you to easily alter the network infrastructure as needed. This includes changing the nodes' locations, the hardware's CPU (Central processing unit) and RAM (Random access memory), the endorsement policy required to reach consensus, and the ease with which new organizations and members can be added to the network.

Federated learning for performance behavior detection in a fog-IoT system

In fog-based IoT systems, every fog can behave differently due to context and vulnerabilities. In smart irrigation systems, some fog nodes use more or fewer computing resources to analyze the data according to sensor location, soil moisture, plant species, or seasons. Therefore, fog behavior should consider distinct contexts. Federated learning support fog-based IoT systems to detect faster the behavior of fog nodes as it enables them to perceive previous behaviors from their peer nodes. We develop and assess an unsupervised federated learning system to identify fog anomalies. We consider experiments with seven rounds of four minutes, executing K-Means in every node to obtain local centroids, and the system merges them in the cloud to calculate global centroids, sending them back to the fog nodes. This paper evaluates the accuracy and time a fog node needs to predict a behavior already identified by another fog node. We assess the CPU usage and the time the cloud takes to compute global centroids using thousands of local cluster centers and measure the prediction time for different fog hardware. We observe that the cloud CPU usage and time to obtain the global centroids vary according to the number of fog nodes and the number of fog behaviors. Our results also show that, in the worst case, our system predicts a behavior by around 50 ms. In contrast, a non-federated approach must wait for the current round to end, as 51.3 s in our results. Therefore, our approach shows promising results for time-sensitive IoT systems.

Simulation and Evaluation of Distributed consensus Network for Multi-Agent Systems for Sybil Attacks

Distributed average consensus represents the amount of computing of inputs held by multiple agents that communicate through peer-to-peer networks. Collaboration among operators is essential for any distributed standard consensus protocol as every specialist needs to contribute to different operators, typically the adjacent (neighbouring) operators. Internet-of-Things (IoT) implementation is challenging because of its heterogeneous, massively distributed nature. The challenges of this challenge can be addressed with blockchain-based platforms and technologies. Testing and evaluation platforms are required for Blockchain deployments in IoT. A realistic and configurable network environment is presented in this paper to evaluate consensus algorithms. Many blockchainevaluation platforms do not provide a configurable and realistic network environment or are tied to a specific consensus protocol. With our simulator, practitioners can evaluate how consensus algorithms affect network events in congested or contested scenarios to determine the best consensus algorithm. It is proposed to achieve this task by generalizing consensus methods. The Blockchain simulator employs Discrete event network simulations for increased fidelity and scalability. In addition to evaluating the time, state block rate (%), estimation error, average throughput, and simulation time, we evaluate the performance of the proposed techniques based on the number of peer nodes. A comparison of the average transaction delivery rate with a traditional protocol is shown. The proposed protocol has a higher throughput average than the traditional one.

Securing blockchain-based timed data release against adversarial attacks1

Timed data release refers to protecting sensitive data that can be accessed only after a pre-determined amount of time has passed. While blockchain-based solutions for timed data release provide a promising approach for decentralizing the process, designing an attack-resilient timed-release service that is resilient to malicious adversaries in a blockchain network is inherently challenging. A timed-release service on a blockchain network is inevitably exposed to the risk of post-facto attacks where adversaries may launch attacks after the data is released in the blockchain network. Existing incentive-based solutions for timed data release in Ethereum blockchains guarantee protection under the assumption of a fully rational adversarial environment in which every peer acts rationally. However, these schemes fail invariably when even a single participating peer node in the protocol starts acting maliciously and deviates from the rational behavior. In this paper, we propose a systematic solution for attack-resilient and practical blockchain-based timed data release in a mixed adversarial environment, where both malicious adversaries and rational adversaries exist. We first propose an effective uncertainty-aware reputation measure to capture the behaviors of the peer involved in timed data release activities in the network. In light of such a measure, we present the design of a basic protocol that consists of two critical ingredients, namely reputation-aware peer recruitment and verifiable enforcement protocols. The former, prior to the start of the enforcement protocols, performs peer recruitment based on the reputation measure to make the design probabilistically attack-resilient to the post-facto attacks. The latter is responsible for contractually guarding the recruited peers at runtime by transparently reporting observed adversarial behaviors. However, the basic recruitment design is only aware of the reputation of the peers and it does not consider the working time schedule of the participating peers and as a result, it results in lower attack-resilience. To enhance the attack resilience further without impacting the verifiable enforcement protocols, we propose a temporal graph-based reputation-aware peer recruitment algorithm that carefully determines the peer recruitment plan to make the service more attack-resilient. In our proposed approach, we formally capture the timed data release service as a temporal graph and we develop a novel maximal attack-resilient path-finding algorithm on the temporal graph for the participating peers. We implement a prototype of the proposed approach using Smart Contracts and deploy it on the Ethereum official test network, Rinkeby. For extensively evaluating the proposed techniques, we perform simulation experiments to validate the effectiveness of the reputation-aware timed data release protocols as well as our proposed temporal-graph-based improvements. The results demonstrate the effectiveness and strong attack resilience of the proposed mechanisms and our approach incurs only a modest gas cost.

HPCLS-BC: A novel blockchain framework using heterogeneous peer-node and cloud-based ledger storage for Internet of Things applications

Internet of Things (IoT) has gained its widespread application in various fields. Integrating blockchain technology with IoT-based applications has been attracting more research enthusiasm. On the other hand, the number of peer nodes and distributed ledgers is one vital factor for the security of blockchain-based applications. Due to the enormous number of IoT terminal devices, IoT can potentially enhance the security of blockchain, supposing IoT terminal devices play the role of peer nodes. However, the combination of blockchain and IoT faces several challenges. The distributed ledger storage on peer node, which will consume too much storage space of IoT terminal devices, must be solved properly. With the increase of IoT terminal devices for use as peer nodes, especially full nodes, the performance of blockchain will face another challenge. The additional network traffic of IoT terminal devices must also be well-controlled. In this paper, a Heterogeneous Peer-node and Cloud-based Ledger Storage Blockchain (HPCLS-BC) is suggested, in which smart phone, tablet Personal Computer (PC) and conventional computer play the role of peer nodes. Cloud-based ledger storage is proposed to alleviate the pressure of ledger storage on peer nodes, and to make sure the number of peer nodes always equals that of the distributed ledgers. An anti-telecom-fraud scenario is presented to illustrate its application. Comparative experiment results show that HPCLS-BC is competent to blockchain application with lightweight and middleweight pressure, and does not lead to obvious additional network traffic for mobile peer nodes.

Secure and efficient blockchain-based consensus scheme for MWSNs with clustered architecture

Blockchain has proven in sensor networks as a distributed solution for transparent and secure storage, which allows its application in mobile wireless sensor networks (MWSNs). The consensus mechanism, an essential aspect of blockchain technology, must concern the high mobility, resource-constrained nature, and weak physical defenses of sensor nodes in MWSNs. To secure MWSN data storage in clustered communication, we design a proof-of-information (PoI) variant for fair miner campaigning via the amount of valid data generated from environmental information, including a dynamic adjustment of the data volume threshold to detect malicious nodes and prevent them from misreporting information. Additionally, we introduce a filtering mechanism through the dynamic integrated trust (DIt) of nodes, which integrates the trust evaluation of peer nodes across the network combining objective performance to prevent malicious nodes from infiltrating the final consensus group. The multi-level filtering technique improves the campaign fairness while isolating malicious nodes, ensuring complexity-sensitive PBFT algorithm efficiency in large-scale networks. Simulation results show that the scheme isolates 90% of the malicious nodes and screens 20% of members to produce a smaller final consensus group. Further analysis of impacts on the performance considering network topology and mobility patterns and comparisons of the relevant solutions are presented.

An optimal scheduling algorithm considering the transactions worst-case delay for multi-channel hyperledger fabric network

As the most popular consortium blockchain platform, Hyperledger Fabric (Fabric for short) has released multiple versions that support different consensus protocols to address the risks faced in current and future network transactions. For example, Fabric v1.4 and v2.0 use Kafka and Raft mechanisms to complete consensus and ensure that the system can withstand failures such as crashes, network partitions, or network shutdowns. In a multi-channel Fabric network architecture, the system structure cannot guarantee the behavior of malicious nodes. Complex cooperation between peer groups on different channels can greatly affect the security and efficiency of the entire network architecture, which is challenging to estimate and optimize.To address this challenge, we designed a Drift Plus Penalty Algorithm (DPPA) and a Transaction Worst-case Delay Algorithm (TWDA) based on peer node random scheduling using the Lyapunov optimization framework. The DPPA ensures the stability of the system and provides the maximum transaction processing rate under the minimum safety probability. The numerical results show that this algorithm can achieve a good balance between system security probability and queue accumulation. The TWDA considers discarding transactions with excessively long delay time by setting a worst-case transaction delay threshold. When considering both the security probability and queue accumulation of the Fabric system, the optimal scheduling of peer nodes is given. Numerical simulations were conducted on two types of algorithms, and the results showed that the security of the TWDA was slightly worse than that of the DPPA, but the system queue accumulation was significantly smaller. Therefore, the simulation results not only validate the effectiveness of the two types of algorithms but also provide operators with operational strategies that consider different factors.

Data Trusted Sharing Delivery: A Blockchain-Assisted Software-Defined Content Delivery Network

The 6G wireless network aims to forge new spectrum, high technical standards of high time and phase synchronization accuracy, and 100% geographic coverage to connect trillions of devices flexibly and efficiently in the future. However, as connectivity increases and applications become novel, it is a challenge to ensure the privacy and security of networks and applications. Blockchain is seen as a promising technology that can improve efficiency, reduce costs, mitigate security and privacy threats, and establish a trusted data-sharing environment. This paper presents a trusted framework based on block chain technology from the perspective of how to build a trusted software-defined content delivery network. As the peer node of blockchain, SDN (Software Defined Network) controller establishes trust between different regions and a wide range of participants, realizing peer autonomy and flexible business orchestration. The two main purposes of the architecture are to enhance the security of network communications and establish trust relationships between entities in different domains. It includes trusted communication based on routing sandbox, service choreography based on block chain, proxy server selection strategy based on MPC (model predictive control) and optimization consensus based on PBFT. Some simulation experiments verify the effectiveness of the theoretical method.

PUF-Based Mutual Authentication and Key Exchange Protocol for Peer-to-Peer IoT Applications

Peer to Peer (P2P) or direct connection IoT has become increasingly popular owing to its lower latency and higher privacy compared to database-driven or server-based IoT. However, wireless vulnerabilities raise severe concerns on IoT device-to-device communication. This is further aggravated by the challenge to achieve lightweight direct mutual authentication and secure key exchange between IoT peer nodes in P2P IoT applications. Physical unclonable function (PUF) is a key enabler to lightweight, low-power and secure authentication of resource-constrained devices in IoT. Nevertheless, current PUF-enabled authentication protocols, with or without the challenge-response pairs (CRPs) of each of its interlocutors stored in the verifier's side, are incompatible for P2P IoT scenarios due to the security, storage and computing power limitations of IoT devices. To solve this problem, a new lightweight PUF-based mutual authentication and key exchange protocol is proposed. It allows two resource-constrained PUF embedded endpoint devices to authenticate each other directly without the need for local storage of CRPs or any private secrets, and simultaneously establish the session key for secure data exchange without resorting to the public-key algorithm. The proposed protocol is evaluated using the game-based formal security analysis method as well as the automatic security analysis tool ProVerif to corroborate its mutual authenticity, secrecy, and resistance against replay and man-in-the-middle (MITM) attacks. Using two Avnet Ultra96-V2 boards to emulate the two IoT endpoint devices, a physical prototype system is also constructed to demonstrate and validate the feasibility of the proposed secure P2P connection scheme. A comparative analysis shows that the proposed protocol outperforms related protocols in terms of security features, computational complexity as well as communication and storage costs.

B-SAHIC: A blockchain based secured and automated health insurance claim processing system

In recent years, blockchain technology has been successfully used in many distributed environments where different stakeholders, who do not have any trust between them, interact with each other through a secured and transparent platform. The use of blockchain in healthcare insurance industry has not been studied methodically. In this study, we develop a blockchain based Secured and Automated Health Insurance Claim (B-SAHIC) processing system. First, we design an Entity-Relationship (ER) diagram identifying all actors with their respective data and relations between them. We also develop the business model and algorithms for all necessary steps. We implement the system in Hyperledger Fabric and deploy a smart contract to implement these algorithms. We introduce CouchDB to store the OffChain data where we store World-State Database. B-SAHIC provides a web-based portal for all actors who interact with the blockchain. Privacy of clients’ claim-related data is ensured by encrypting treatment-related data with a new key that is derived uniquely for each new submission done of clients’ personal documents. We have also deployed Hyperledger Explorer, a user-friendly web application tool for monitoring the health state of each node participating on the blockchain network. We have studied the performance of B-SAHIC for two to six peer nodes. Moreover, our performance study shows that B-SAHIC is fast and scalable. In our study, the average query latency is decreased from 0.07 second (for two peer nodes) to 0.02 second (for six peer nodes) in case of 1300 queries per second while the average transaction latency remains unchanged (around 3.5 seconds) for 300 transactions per second. Moreover, B-SAHIC consumes minimum resources, around 350MB only for two peer nodes. We believe that the development process of this blockchain based platform can be applicable for the automation of other insurance industry too.

An access control scheme in IoT-enabled Smart-Grid systems using blockchain and PUF

IoT-enabled Smart Grid (IoT-SG) is an emerging paradigm that enables the bi-direction communication of IoT devices and hardware to efficiently collect and transmit the consumer’s information over the Internet. However, the underlying open communication network and resource-constrained capabilities of devices invite manifold challenges and threats in terms of security and privacy. To alleviate such issues, we designed a private blockchain-based access control protocol for IoT-SG using Physically Unclonable Function (PUF). Our protocol allows the Service Provider (SP) and smart meters to transfer the data in an efficient and secure manner. The participating SPs form the Peer-to-Peer (P2P) network, and each peer node is responsible for securely creating the blocks from the gathered data. Thereafter, all the peer nodes employ a voting-based consensus mechanism to verify and add the recently created block into the blockchain network. We have rigorously validated the security of our protocol under the Random or Real (RoR) model. The testbed results and security feature analysis show that our protocol is more efficient than competing ones while it also provides significant security properties.

C3P-RPL: A collaborative and proactive approach for optimal peer to peer path selection and sustenance

Internet of Things is evolving from information gathering platforms into collaborative systems wherein, smart devices actively interact with each other in a seamless manner. For instance, Internet of Robotic Things is envisioned to provide augmented solutions through collaboration of varied smart devices and robots. These visions revolve around the ability of smart devices to directly communicate and cooperate with each other in real time. In this context, this paper is an attempt to study RPL’s (Routing Protocol for Low-power Lossy Networks) point to point routing that creates multi-hop paths between peer nodes. This standard routing protocol is known for robust and failsafe upward paths but its peer to peer (P2P) routes are reported to be suboptimal. This work assesses P2P performance of RPL’s storing mode in a network of new generation devices having higher memory. Further, a Collaborative and Proactive Peer to Peer (C3P) path selection and sustenance approach is proposed where, root node collates incremental topology from collaborative nodes and disseminates optimal single source shortest path trees SPT(n). A progressive node betweenness centrality score ensures spread out paths. Minor topology changes are accommodated through incremental node and edge updates to targeted SPT(n) locally. Storing SPTs in intermediate nodes reduces storage and packet size. Through simulations and testbed experiments, it is proven that C3P-RPL improves simultaneous peer to peer communication between all the nodes. Specifically, the path length is reduced by 30% and subsequently the network latency drops by 65% in an experimental testbed of 47 nodes, making it suitable for collaborations.

Enhancing security and ensuring secure performance: A performance evaluation of consensus algorithms in a distributed healthcare blockchain system

Blockchain is an emerging technology in today’s real-time applications and database transaction systems—the primary motto is to determine transactional clarity to end-user without any fluctuation. According to the basic block policy, it is immutable or does not allow updating the existing transaction, which automatically maintains the security and transaction clarity. This paper proposes a system performance evaluation of various consensus algorithms in a distributed environment with a peer-to-peer network. The four different consensus algorithms have been evaluated in four peer nodes. Healthcare application has been successfully tested with the entire system. The first blockchain implementation has done in a Java environment with the custom hash generation, mining strategy, and smart contract for each level. Each algorithm provides different time complexity accordingly. The system evaluates the performance of four consensus algorithms sequentially and demonstrates the effectiveness and utilization of each algorithm according to the requirements.

Hybrid Pointer Based Blockchain Solution and Ledger Data Services Interoperability

The Blockchain concept has erupted from decentralized digital currency world and has reached a high penetration in other areas where the certification of transactions and its immutability is required. The experience on elevated security to event time driven data assertion was transferred from the digital currency to the data driven enterprise world. In applications were highly regulated and certified data intensive systems are needed, Blockchain becomes a strong solution. Areas like the management of the lifecycle of reusable rockets, aeronautics, aerial surveillance, aviation safety, wind turbine and solar farms, electric grids and others, the amount of generated data to be registered and certified is considerable. Many implemented Blockchain solutions tend to register and add to the Blockchain, large amounts of data that reduce the Blockchain management and usability. This work proposes a Hybrid Pointer Based Blockchain solution to overcome the issues, by integrating several parallel services that work side by side with distributed, secured and certified peer node systems that guarantee the data immutability and interconnection to the different blockchains that interact with each other. The proposed Blockchain solution presented in this work interacts with the peer nodes edge services, from software services to hardware generated data and AI assessments.

EMBN-MANET: A method to Eliminating Malicious Beacon Nodes in Ultra-Wideband (UWB) based Mobile Ad-Hoc Network

Recent breakthroughs in microelectromechanical systems, microsystem technologies, and wireless communications have made energy-efficient, inexpensive, off-the-shelf devices that unambiguously carry data without communication overhead practical. UWB radio technology employs minimal energy for short-range, high-bandwidth communications throughout a large section of the radio. Mobile computing organizations now explore mobile ad-hoc networks. Decentralized networks communicate. Peer nodes enable wireless device-to-device communication. Location-based and location-aided routing improve ad hoc routing. Physical or involuntary configuration places mobile nodes during deployment. Large networks need too much manual setup. GPS receivers for each sensor unit would significantly increase network installation costs. It inspired non-GPS and non-physical configuration localization. Most localization systems use beacon nodes. Beacon nodes are unique. Standard security approaches block secure beacon nodes, which might compromise localization. This research investigates beacon node localization issues and attacks. We constructed a statistical model to detect rogue beacon nodes in the ad hoc network and studied how various attacks affect localization. Bogus beacon nodes find mobile nodes. We enabled malicious beacon node communication. Trilateration and Received Signal Strength Indicator found unknown nodes. Trilateration detects compromised beacon nodes. The algorithm finds malicious beacon nodes. Our experiments removed 90% of compromised beacon nodes. Our flexible localization technique allows several algorithms and range methods without time complexity. Location identification affected fake beacon nodes.

A Reinforcement-Learning-Based Model for Resilient Load Balancing in Hyperledger Fabric

Blockchain with its numerous advantages is often considered a foundational technology with the potential to revolutionize a wide range of application domains, including enterprise applications. These enterprise applications must meet several important criteria, including scalability, performance, and privacy. Enterprise blockchain applications are frequently constructed on private blockchain platforms to satisfy these criteria. Hyperledger Fabric is one of the most popular platforms within this domain. In any privacy blockchain system, including Fabric, every organisation needs to utilise a peer node (or peer nodes) to connect to the blockchain platform. Due to the ever-increasing size of blockchain and the need to support a large user base, the monitoring and the management of different resources of such peer nodes can be crucial for a successful deployment of such blockchain platforms. Unfortunately, little attention has been paid to this issue. In this work, we propose the first-ever solution to this significant problem by proposing an intelligent control system based on reinforcement learning for distributing the resources of Hyperledger Fabric. We present the architecture, discuss the protocol flows, outline the data collection methods, analyse the results and consider the potential applications of the proposed approach.

Robust P2P networking connectivity estimation engine for permissionless Bitcoin cryptocurrency

Blockchain relies on the underlying peer-to-peer (P2P) networking to broadcast and get up-to-date on the blocks and transactions. Because of the blockchain operations’ reliance on the information provided by P2P networking, it is imperative to have high P2P connectivity for the quality of the blockchain system operations and performances. High P2P networking connectivity ensures that a peer node is connected to multiple other peers providing a diverse set of observers of the current state of the blockchain and transactions. However, in a permissionless Bitcoin cryptocurrency network, using the peer identifiers – including the current approach of counting the number of distinct IP addresses and port numbers – can be ineffective in measuring the number of peer connections and estimating the networking connectivity. Such current approach is further challenged by the networking threats manipulating identities. We build a robust estimation engine for the P2P networking connectivity by sensing and processing the P2P networking traffic. We take a systematic approach to study our engine and analyze the followings: the different components of the connectivity estimation engine and how they affect the accuracy performances, the role and the effectiveness of an outlier detection to enhance the connectivity estimation, and the engine’s interplay with the Bitcoin protocol. We implement a working Bitcoin prototype connected to the Bitcoin mainnet to validate and improve our engine’s performances and evaluate the estimation accuracy and cost efficiency of our connectivity estimation engine. Our results show that our scheme effectively counters the identity-manipulations threats, achieves 96.4% estimation accuracy with a tolerance of one peer connection, and is lightweight in the overheads in the mining rate, thus making it appropriate for the miner deployment.