Platooning technologies enable trucks to drive cooperatively and automatically, which bring benefits including less fuel consumption, more road capacity and safety. In order to establish trust during dynamic platoon formation, ensure vehicular data integrity, and guard platoons against potential attackers, it is pivotal to verify any given vehicle's identity information before granting it access to join a platoon. To address this concern in dynamic truck platooning, we present a novel location-aware and privacy-preserving verification protocol based on zero-knowledge proof and permissioned blockchain. By performing the verification process within the spatially-local area defined by a given platoon, our system can provide lower latency and communication overhead compared to a location-agnostic blockchain system. We prototype the proposed system and perform benchmark tests on the Hyperledger platform. The experimental results show that our system is suitable for real-world truck platooning.
Distributed Ledger Technologies (DLT) and Decentralized File Storages (DFS) are becoming increasingly used to create common, decentralized and trustless infrastructures where participants interact and collaborate in Peer-to-Peer interactions. A prominent use case is represented by decentralized data marketplaces, where users are consumers and providers at the same time, and trustless interactions are required. However, data in DLTs and DFS are usually unstructured and there are no efficient mechanisms to query a certain type of data for the search in the market. In this paper, we propose the use of a Distributed Hash Table (DHT) as a layer on top of DLTs where, once the data are acquired and stored in the ledger, these can be searched through multiple keyword based queries, thanks to the lookup functionalities offered by the DHT. The DHT network is a hypercube overlay structure, organized for an efficient processing of multiple keyword-based queries. We provide the architecture of such solution for a decentralized data marketplace and an analysis based on a simulation that proves the viability of the proposed approach.
Plenty of research on smart mobility is currently devoted to the inclusion of novel decentralized software architectures to these systems, due to the inherent advantages in terms of transparency, traceability, trustworthiness. MOVO is a decentralized application (dApp) for smart mobility. It includes: (i) a module for collecting data from vehicles and smartphones sensors; (ii) a component for interacting with Distributed Ledger Technologies (DLT) and Decentralized File Storages (DFS), for storing and validating sensor data; (iii) a module for "offline" interaction between devices. The dApp consists of an Android application intended for use inside a vehicle, which helps the user/driver collect contextually generated data (e.g. a driver's stress level, an electric vehicle's battery level), which can then be shared through the use of DLT (i.e., IOTA DLT and Ethereum smart contracts) and DFS (i.e., IPFS). The third module consists of an implementation of a communication channel that, via Wi-Fi Direct, allows two devices to exchange data and payment information with respect to DLT (i.e. cryptocurrency and token) assets. In this paper, we describe the main software components and provide an experimental evaluation that confirms the viability of the MOVO dApp in real mobility scenarios.
Leonhard Balduf, Sebastian Henningsen, Martin Florian, Sebastian Rust · 5 authors
Decentralized data storage systems like the Interplanetary Filesystem (IPFS) are becoming increasingly popular, e. g., as a data layer in blockchain applications and for sharing content in a censorship-resistant manner. In IPFS, data is hosted by an open set of nodes and data requests are broadcast to connected peers in addition to being routed via a distributed hash table (DHT). In this paper, we present a passive monitoring methodology that exploits this design for obtaining data requests from a significant and upscalable portion of nodes. Using an implementation of our approach for the IPFS network and data collected over a period of fifteen months, we demonstrate how our methodology enables profound insights into, among other things: the size of the IPFS network, activity levels and structure, and content popularity distributions. We furthermore present that our methodology can be abused for attacks on users' privacy. For example, we were able to identify and successfully surveil the IPFS nodes corresponding to public IPFS/HTTP gateways.We give a detailed analysis of the mechanics and reasons behind implied privacy threats and discuss possible countermeasures.
The amalgamation of different generations of mobile cellular networks around the globe has resulted in diverse data speed experiences for end users. At present there are no defined mechanisms in place for a subscriber of one mobile network operator (MNO) to use the services of a WiFi provider. Cellular and Data Service providers also have no standardized procedures to securely interact with each other, and to allow their subscribers to use third party services on a pay-as-you-go basis. This paper proposes a blockchain-based offloading framework that allows a subscriber of a mobile operator to temporarily use another MNO or WiFi provider's higher speed network. Smart contracts allow diverse entities such as MNOs, Brokers and WiFi Providers to automatically execute mutual agreements to enable the utilization of third party infrastructure in a secure and controlled manner. To test the proposed framework, the offloading of a subscriber from 3G/4G/4G-LTE/5G networks to a fixed broadband WiFi network was carried out and the results analyzed. The offloading framework was implemented using the ns-3 network simulator, and the Ethereum blockchain smart contract features were used for the settlement of invoices.
Roman Matzutt, Benedikt Kalde, Jan Pennekamp, Arthur Drichel · 6 authors
Popular cryptocurrencies continue to face serious scalability issues due to their ever-growing blockchains. Thus, modern blockchain designs began to prune old blocks and rely on recent snapshots for their bootstrapping processes instead. Unfortunately, established systems are often considered incapable of adopting these improvements. In this work, we present CoinPrune, our block-pruning scheme with full Bitcoin compatibility, to revise this popular belief. CoinPrune bootstraps joining nodes via snapshots that are periodically created from Bitcoin's set of unspent transaction outputs (UTXO set). Our scheme establishes trust in these snapshots by relying on CoinPrune-supporting miners to mutually reaffirm a snapshot's correctness on the blockchain. This way, snapshots remain trustworthy even if adversaries attempt to tamper with them. Our scheme maintains its retrospective deployability by relying on positive feedback only, i.e., blocks containing invalid reaffirmations are not rejected, but invalid reaffirmations are outpaced by the benign ones created by an honest majority among CoinPrune-supporting miners. Already today, CoinPrune reduces the storage requirements for Bitcoin nodes by two orders of magnitude, as joining nodes need to fetch and process only 6 GiB instead of 271 GiB of data in our evaluation, reducing the synchronization time of powerful devices from currently 7 h to 51 min, with even larger potential drops for less powerful devices. CoinPrune is further aware of higher-level application data, i.e., it conserves otherwise pruned application data and allows nodes to obfuscate objectionable and potentially illegal blockchain content from their UTXO set and the snapshots they distribute.
Blockchain (BC) technology can revolutionize future networks by providing a distributed, secure, and unalterable way to boost collaboration among operators, users, and other stakeholders. Its implementations have traditionally been supported by wired communications, with performance indicators like the high latency introduced by the BC being one of the key technology drawbacks. However, when applied to wireless communications, the performance of BC remains unknown, especially if running over contention-based networks. In this paper, we evaluate the latency performance of BC technology when the supporting communication platform is wireless, specifically we focus on IEEE 802.11ax, for the use case of users' radio resource provisioning. For that purpose, we propose a discrete-time Markov model to capture the expected delay incurred by the BC. Unlike other models in the literature, we consider the effect that timers and forks have on the end-to-end latency.
Yaroslav Meshcheryakov, Anna Melman, Oleg Evsutin, Vladimir Morozov · 5 authors
Cyber-physical systems and the Internet of things (IoT) is becoming an integral part of the digital society. The use of IoT services improves human life in many ways. Protection against cyber threats is an important aspect of the functioning of IoT devices. Malicious activities lead to confidential data leakages and incorrect performance of devices are becoming critical. Therefore, development of effective solutions that can protect both IoT devices data and data exchange networks turns in to a real challenge. This study provides a critical analysis of the feasibility of using blockchain technology to protect constrained IoT devices data, justifies the choice of Practical Byzantine Fault Tolerance (PBFT) consensus algorithm for implementation on such devices, and simulates the main distributed ledger scenarios using PBFT. The simulation results demonstrate the efficiency of the blockchain technology for constrained devices and make it possible to evaluate the applicability limits of the chosen consensus algorithm.
Krzysztof Pietrzak, Iosif Salem, Stefan Schmid, Michelle Yeo
Payment channel networks are a promising approach to improve the scalability of cryptocurrencies: they allow to perform transactions in a peer-to-peer fashion, along multi-hop routes in the network, without requiring consensus on the blockchain. However, during the discovery of cost-efficient routes for the transaction, critical information may be revealed about the transacting entities. This paper initiates the study of privacy-preserving route discovery mechanisms for payment channel networks. In particular, we present LightPIR, an approach which allows a source to efficiently discover a shortest path to its destination without revealing any information about the endpoints of the transaction. The two main observations which allow for an efficient solution in LightPIR are that: (1) surprisingly, hub labelling algorithms - which were developed to preprocess "street network like" graphs so one can later efficiently compute shortest paths - also work well for the graphs underlying payment channel networks, and that (2) hub labelling algorithms can be directly combined with private information retrieval. LightPIR relies on a simple hub labeling heuristic on top of existing hub labeling algorithms which leverages the specific topological features of cryptocurrency networks to further minimize storage and bandwidth overheads. In a case study considering the Lightning network, we show that our approach is an order of magnitude more efficient compared to a privacy-preserving baseline based on using private information retrieval on a database that stores all pairs shortest paths.
Le Xia, Yao Sun, Mohammad Rafiq Swash, Lina Mohjazi · 6 authors
Securing safe driving for connected and autonomous vehicles (CAVs) continues to be a widespread concern, despite various sophisticated functions delivered by artificial intelligence for in-vehicle devices. Diverse malicious network attacks are ubiquitous, along with the worldwide implementation of the Internet of Vehicles, which exposes a range of reliability and privacy threats for managing data in CAV networks. Combined with the fact that the capability of existing CAVs in handling intensive computation tasks is limited, this implies a need for designing an efficient assessment system to guarantee autonomous driving safety without compromising data security. In this article we propose a novel framework, namely Blockchain-enabled intElligent Safe-driving assessmenT (BEST), which offers a smart and reliable approach for conducting safe driving supervision while protecting vehicular information. Specifically, a promising solution that exploits a long short-term memory model is introduced to assess the safety level of the moving CAVs. Then we investigate how a distributed blockchain obtains adequate trustworthiness and robustness for CAV data by adopting a byzantine fault tolerance-based delegated proof-of-stake consensus mechanism. Simulation results demonstrate that our presented BEST gains better data credibility with a higher prediction accuracy for vehicular safety assessment when compared with existing schemes. Finally, we discuss several open challenges that need to be addressed in future CAV networks.
Aristodemos Paphitis, Nicolas Kourtellis, Michael Sirivianos
Blockchain (BC) systems are highly distributed peer-to-peer networks that offer an alternative to centralized services and promise robustness to coordinated attacks. However, the resilience and overall security of a BC system rests heavily on the structural properties of its underlying peer-to-peer overlay. Despite their success, BC overlay networks' critical design aspects, connectivity properties and network-layer inter-dependencies are still poorly understood. In this work, we set out to fill this gap and study the most important overlay network structural properties and robustness to targeted attacks of seven distinct BC networks. In particular, we probe and crawl these BC networks every two hours to gather information about all their available peers, over a duration of 28 days. We analyze 335 network snapshots per BC network, for a total of 2345 snapshots. We construct, at frequent intervals, connectivity graphs for each BC network, consisting of all potential connections between peers. We analyze the structural graph properties of these networks and compare them across the seven BC networks. We also study how these properties associate with the resilience of each network to partitioning attacks, i.e., when peers are selected, attacked and taken offline, using different selection strategies driven by the aforementioned structural properties. In fact, we show that by targeting fewer than 10 highly-connected peers, major BCs such as Bitcoin can be partitioned into disjoint, i.e., disconnected, components. Finally, we uncover a hidden interconnection between different BC networks, where certain peers participate in more than one BC network, which has serious implications for the robustness of the overall BC network ecosystem.
A k-anonymous broadcast can be implemented using a small group of dining cryptographers to first share the message, followed by a flooding phase started by group members. Members have little incentive to forward the message in a timely manner, as forwarding incurs costs, or they may even profit from keeping the message. In worst case, this leaves the true originator as the only sender, rendering the dining-cryptographers phase useless and compromising their privacy. We present a novel approach using a modified dining-cryptographers protocol to distributed shares of an (n,k)-Shamir's secret sharing scheme. Finally, all group members broadcast their received share through the network, allowing any recipient of k shares to reconstruct the message, enforcing anonymity. If less than k group members broadcast their shares, the message cannot be decoded thus preventing privacy breaches for the originator. Our system provides (n-|attackers|)-anonymity for up to k-1 attackers and has little performance impact on dissemination. We show these results in a security analysis and performance evaluation based on a proof-of-concept prototype. Throughput rates between 10 and 100 kB/s are enough for many real applications with high privacy requirements, e.g., financial blockchain system.
We propose a new way to share licensed spectrum bandwidth capacity in mobile\nnetworks between operators, service providers and consumers using\nblockchain-based smart contracts. We discuss the foundational building blocks\nin the contract as well as various extensions to support more advanced features\nsuch as bulk purchases, future reservations, and various auction mechanisms.\nFurthermore, we demonstrate how the system can be implemented with an\nopen-source, permissioned Enterprise blockchain, Hyperledger Sawtooth. We show\nthat our smart contract implementation can improve blockchain transaction\nperformance, by approximately four orders of magnitude compared to serial\ntransactions and one order of magnitude compared to parallell transactions,\nusing PKI-driven bulk purchases of mobile access grants, paving the way for\nfully automated, efficient, and fine-grained roaming agreements.\n
Payment channel networks (PCNs) have emerged as a scalability solution for blockchains built on the concept of a payment channel: a setting that allows two nodes to safely transact between themselves in high frequencies based on pre-committed peer-to-peer balances. Transaction requests in these networks may be declined because of unavailability of funds due to temporary uneven distribution of the channel balances. In this paper, we investigate how to alleviate unnecessary payment blockage via proper prioritization of the transaction execution order. Specifically, we consider the scheduling problem in PCNs: as transactions continuously arrive on both sides of a channel, nodes need to decide which ones to process and when in order to maximize their objective, which in our case is the channel throughput. We introduce a stochastic model to capture the dynamics of a payment channel under random arrivals, and propose that channels can hold incoming transactions in buffers up to some deadline in order to enable more elaborate processing decisions. We describe a policy that maximizes the channel success rate/throughput for uniform transaction requests of fixed amounts, both in the presence and absence of buffering capabilities, and formally prove its optimality. We also develop a discrete event simulator of a payment channel, and evaluate different heuristic scheduling policies in the more general heterogeneous amounts case, with the results showing superiority of the heuristic extension of our policy in this case as well. Our work opens the way for more formal research on improving PCN performance via joint consideration of routing and scheduling decisions.
Dining-cryptographers networks (DCN) can achieve information-theoretical privacy. Unfortunately, they are not well suited for peer-to-peer networks as they are used in blockchain applications to disseminate transactions and blocks among participants. In previous but preliminary work, we proposed a threephase approach with an initial phase based on a DCN with a group size of k while later phases take care of the actual broadcast within a peer-to-peer network. This paper describes our DCN protocol in detail and adds a performance evaluation powered by our proof-of-concept implementation. Our contributions are (i) an extension of the DCN protocol by von Ahn for fair delivery of arbitrarily long messages sent by potentially multiple senders, (ii) a privacy and security analysis of this extension, (iii) various performance optimisation especially for best-case operation, and (iv) a performance evaluation. The latter uses a latency of 100 ms and a bandwidth limit of 50 Mbit/s between participants. The interquartile range of the largest test of the highly secured version took 35s+-1.25s for a full run. All tests of the optimized common-case mode show the dissemination of a message within 0.5s+-0.1s. These results compare favourably to previously established protocols for k-anonymous transmission of fixed size messages, outperforming the original protocol for messages as small as 2 KiB.
Tahmid Hasan Pranto, Abdulla All Noman, Atik Mahmud, AKM Bahalul Haque
The agricultural sector is still lagging behind from all other sectors in terms of using the newest technologies. For production, the latest machines are being introduced and adopted. However, pre-harvest and post-harvest processing are still done by following traditional methodologies while tracing, storing, and publishing agricultural data. As a result, farmers are not getting deserved payment, consumers are not getting enough information before buying their product, and intermediate person/processors are increasing retail prices. Using blockchain, smart contracts, and IoT devices, we can fully automate the process while establishing absolute trust among all these parties. In this research, we explored the different aspects of using blockchain and smart contracts with the integration of IoT devices in pre-harvesting and post-harvesting segments of agriculture. We proposed a system that uses blockchain as the backbone while IoT devices collect data from the field level, and smart contracts regulate the interaction among all these contributing parties. The system implementation has been shown in diagrams and with proper explanations. Gas costs of every operation have also been attached for a better understanding of the costs. We also analyzed the system in terms of challenges and advantages. The overall impact of this research was to show the immutable, available, transparent, and robustly secure characteristics of blockchain in the field of agriculture while also emphasizing the vigorous mechanism that the collaboration of blockchain, smart contract, and IoT presents.
Marc Jayson Baucas, S. Andrew Gadsden, Petros Spachos
Internet of Things (IoT)-based smart home applications are rising in popularity. However, this trend attracts malicious activity, which causes cost-efficient security to be in high demand. This letter proposes a low-end design that reinforces the security of a home network. It uses private blockchain technology and localization via RSSI-based trilateration. We investigated the benefits of private blockchains over their public counterpart, and we improve the precision of the localization algorithm by testing it against different wireless technologies. The results conclude that using a private blockchain with a WiFi-based communication system produces the most efficient iteration of the proposed design.
Since the introduction of the first Bitcoin blockchain in 2008, different decentralized blockchain systems such as Ethereum, Hyperledger Fabric, and Corda, have emerged with public and private accessibility. It has been widely acknowledged that no single blockchain network will fit all use cases. As a result, we have observed the increasing popularity of multi-blockchain ecosystem in which customers will move toward different blockchains based on their particular requirements. Hence, the efficiency and security requirements of interactions among these heterogeneous blockchains become critical. In realization of this multi-blockchain paradigm, initiatives in building Interoperability-Facilitating Platforms (IFPs) that aim at bridging different blockchains (a.k.a. blockchain interoperability) have come to the fore. Despite current efforts, it is extremely difficult for blockchain customers (organizations, governments, companies) to understand the trade-offs between different IFPs and their suitability for different application domains before adoption. A key reason is due to a lack of fundamental and systematic approaches to assess the variables among different IFPs. To fill this gap, developing new IFP requirements specification and open-source benchmark tools to advance research in distributed, multi-blockchain interoperability, with emphasis on IFP performance and security challenges are required. In this document, we outline a research proposal study to the community to realize this gap.
Credit networks rely on decentralized, pairwise trust relationships (channels) to exchange money or goods. Credit networks arise naturally in many financial systems, including the recent construct of payment channel networks in blockchain systems. An important performance metric for these networks is their transaction throughput. However, predicting the throughput of a credit network is nontrivial. Unlike traditional communication channels, credit channels can become imbalanced; they are unable to support more transactions in a given direction once the credit limit has been reached. This potential for imbalance creates a complex dependency between a network's throughput and its topology, path choices, and the credit balances (state) on every channel. Even worse, certain combinations of these factors can lead the credit network to deadlocked states where no transactions can make progress. In this paper, we study the relationship between the throughput of a credit network and its topology and credit state. We show that the presence of deadlocks completely characterizes a network's throughput sensitivity to different credit states. Although we show that identifying deadlocks in an arbitrary topology is NP-hard, we propose a peeling algorithm inspired by decoding algorithms for erasure codes that upper bounds the severity of the deadlock. We use the peeling algorithm as a tool to compare the performance of different topologies as well as to aid in the synthesis of topologies robust to deadlocks.
Jiali Xing, David Fischer, Nitya Labh, Ryan Piersma · 8 authors
In this paper, we present Talaria, a novel permissioned blockchain simulator that supports numerous protocols and use cases, most notably in supply chain management. Talaria extends the capability of BlockSim, an existing blockchain simulator, to include permissioned blockchains and serves as a foundation for further private blockchain assessment. Talaria is designed with both practical Byzantine Fault Tolerance (pBFT) and simplified version of Proof-of-Authority consensus protocols, but can be revised to include other permissioned protocols within its modular framework. Moreover, Talaria is able to simulate different types of malicious authorities and a variable daily transaction load at each node. In using Talaria, business practitioners and policy planners have an opportunity to measure, evaluate, and adapt a range of blockchain solutions for commercial operations.
Decentralized, distributed storage offers a way to reduce the impact of data silos as often fostered by centralized cloud storage. While the intentions of this trend are not new, the topic gained traction due to technological advancements, most notably blockchain networks. As a consequence, we observe that a new generation of peer-to-peer data networks emerges. In this survey paper, we therefore provide a technical overview of the next generation data networks. We use select data networks to introduce general concepts and to emphasize new developments. Specifically, we provide a deeper outline of the Interplanetary File System and a general overview of Swarm, the Hypercore Protocol, SAFE, Storj, and Arweave. We identify common building blocks and provide a qualitative comparison. From the overview, we derive future challenges and research goals concerning data networks.
Matthias Grundmann, Hedwig Amberg, Hannes Hartenstein
Bitcoin is based on a P2P network that is used to propagate transactions and blocks. While the P2P network design intends to hide the topology of the P2P network, information about the topology is required to understand the network from a scientific point of view. Thus, there is a natural tension between the 'desire' for unobservability on the one hand, and for observability on the other hand. On a middle ground, one would at least be interested on some statistical features of the Bitcoin network like the number of peers that participate in the propagation of transactions and blocks. This number is composed of the number of reachable peers that accept incoming connections and unreachable peers that do not accept incoming connections. While the number of reachable peers can be measured, it is inherently difficult to determine the number of unreachable peers. Thus, the number of unreachable peers can only be estimated based on some indicators. In this paper, we first define our understanding of unreachable peers and then propose the PAL (Passive Announcement Listening) method which gives an estimate of the number of unreachable peers by observing ADDR messages that announce active IP addresses in the network. The PAL method allows for detecting unreachable peers that indicate that they provide services useful to the P2P network. In conjunction with previous methods, the PAL method can help to get a better estimate of the number of unreachable peers. We use the PAL method to analyze data from a long-term measurement of the Bitcoin P2P network that gives insights into the development of the number of unreachable peers over five years from 2015 to 2020. Results show that about 31,000 unreachable peers providing useful services were active per day at the end of the year 2020. An empirical validation indicates that the approach finds about 50 % of unreachable peers that provide useful services.
Latif U. Khan, Walid Saad, Dusit Niyato, Zhu Han · 5 authors
Internet of Everything (IoE) applications such as haptics, human-computer interaction, and extended reality, using the sixth-generation (6G) of wireless systems have diverse requirements in terms of latency, reliability, data rate, and user-defined performance metrics. Therefore, enabling IoE applications over 6G requires a new framework that can be used to manage, operate, and optimize the 6G wireless system and its underlying IoE services. Such a new framework for 6G can be based on digital twins. Digital twins use a virtual representation of the 6G physical system along with the associated algorithms (e.g., machine learning, optimization), communication technologies (e.g., millimeter-wave and terahertz communication), computing systems (e.g., edge computing and cloud computing), as well as privacy and security-related technologists (e.g., blockchain). First, we present the key design requirements for enabling 6G through the use of a digital twin. Next, the architectural components and trends such as edge-based twins, cloud-based-twins, and edge-cloud-based twins are presented. Furthermore, we provide a comparative description of various twins. Finally, we outline and recommend guidelines for several future research directions.
Payment channel networks, such as Bitcoin's Lightning Network, promise to improve the scalability of blockchain systems by processing the majority of transactions off-chain. Due to the design, the positioning of nodes in the network topology is a highly influential factor regarding the experienced performance, costs, and fee revenue of network participants. As a consequence, today's Lightning Network is built around a small number of highly-connected hubs. Recent literature shows the centralizing tendencies to be incentive-compatible and at the same time detrimental to security and privacy. The choice of attachment strategies therefore becomes a crucial factor for the future of such systems. In this paper, we provide an empirical study on the (local and global) impact of various attachment strategies for payment channel networks. To this end, we introduce candidate strategies from the field of graph theory and analyze them with respect to their computational complexity as well as their repercussions for end users and service providers. Moreover, we evaluate their long-term impact on the network topology.