Rongxin Xu, Qiujun Lan, Shiva Raj Pokhrel, Gang Li
The Internet of Things (IoT) and Distributed ledger technology (DLT) have significantly changed our daily lives. Due to their distributed operational environment and naturally decentralized applications, the convergence of these two technologies indicates a more lavish arrangement for the future. This article develops a comprehensive survey to investigate and illustrate state-of-the-art DLT for various IoT use cases, from smart homes to autonomous vehicles and smart cities. We develop a novel framework for conducting a systematic and comprehensive review of DLT over IoT by extending the knowledge graph approach. With relevant insights from this review, we extract innovative and pragmatic techniques to DLT design that enable high-performance, sustainable, and highly scalable IoT systems. Our findings support designing an end-to-end IoT-native DLT architecture for the future that fully coordinates network-assisted functionalities.
The dominance of a few big companies in the storage market arising various concerns including single point of failure, privacy violation, and oligopoly. To eliminate the dependency on such a centralized storage architecture, several Decentralized Storage Network (DSN) schemes such as Filecoin, Sia, and Storj have been introduced. DSNs leverage blockchain technology to create a storage platform such that the micro storage providers can also participate in the storage market. To verify the accurate data storage by the storage providers during a storage contract, DSNs apply a Proof of Storage (PoS) scheme to continuously inspect the storage service. However, continuous verification of the storage provider imposes an extra cost to the network and therefore end-users. Moreover, DSN's PoS verification is vulnerable to a service denying attack in which the storage provider submits valid PoS to the network while denying the service to the client. Considering the benefits and existing challenges of DSNs, this paper introduces a novel incentive-compatible DSN scheme. In this scheme, the PoS is conducted only if the client submits a challenge request. We model the storage service as a non-cooperative repeated dynamic game and set the players' payoffs such that the storage provider's dominant strategy is to honestly follow the storage contract. Our proposed mechanism leverages the smart-contract and oracle network to govern the storage agreement between the client and storage provider efficiently. Furthermore, our scheme is independent of a specific blockchain platform but can be plugged into any blockchain platform with smart-contract execution capability. As a proof of concept, we have implemented our scheme using solidity language and chainlink oracle network. The performance analysis demonstrates the applicability of our scheme. The outcome of this paper is a new incentive-compatible mechanism designed carefully for the blockchain-based DSN. The proposed mechanism utilizes different tools including game-theory, smart-contract, oracle network, and Merkle tree to improve the security and performance of storage verification in DSN.
The number of internet-connected devices has been exponentially growing with the massive volume of heterogeneous data generated from various devices, resulting in a highly intertwined cyber-physical system. Currently, the Edge Intelligence System (EIS) concept that leverages the merits of edge computing and Artificial Intelligence (AI) is utilized to provide smart cloud services with powerful computational processing and reduce decision-making delays. Thus, EIS offers a possible solution to realizing future Intelligent Transportation Systems (ITS), especially in a vehicular network framework. However, since the central aggregator server supervises the entire system orchestration, the existing EIS framework faces several challenges and is still potentially susceptible to numerous malicious attacks. Hence, to solve the issues mentioned earlier, this paper presents the notion of secure edge intelligence, merging the benefits of Federated Learning (FL), blockchain, and Local Differential Privacy (LDP). The blockchain-assisted FL approach efficiently improves traffic prediction accuracy and enhances user privacy and security by recording transactions in immutable distributed ledger networks and providing a decentralized reward mechanism system. Furthermore, LDP is empowered to strengthen the confidentiality of data sharing transactions, especially in protecting users' private data from various attacks. The proposed framework has been implemented in two scenarios, i.e., blockchain-based FL to efficiently develop the decentralized traffic management for vehicular networks and LDP-based FL to produce randomized privacy protection using the IBM Library for differential privacy.
Guntur Dharma Putra, Volkan Dedeoglu, Salil S Kanhere, Raja Jurdak
6G is envisioned to enable futuristic technologies, which exhibit more complexities than the previous generations, as it aims to bring connectivity to a large number of devices, many of which may not be trustworthy. Proper authentication can protect the network from unauthorized adversaries. However, it cannot guarantee in situ reliability and trustworthiness of authorized network nodes, as they can be compromised post-authentication and impede the reliability and resilience of the network. Trust and Reputation Management (TRM) is an effective approach to continuously evaluate the trustworthiness of each participant by collecting and processing evidence of their interactions with other nodes and the infrastructure. In this article, we argue that blockchain-based TRM is critical to build trustworthy 6G networks, where blockchain acts as a decentralized platform for collaboratively managing and processing interaction evidence with the end goal of quantifying trust. We present a case study of resource management in 6G networks, where blockchain-based TRM quantifies and maintains reputation scores by evaluating fulfillment of resource owner's obligations and facilitating resource consumers to provide feedback. We also discuss inherent challenges and future directions for the development of blockchain-based TRM for next-generation 6G networks.
Vahid Heidaripour Lakhani, Leander Jehl, Rinke Hendriksen, Vero Estrada-Galiñanes
Peer-to-peer (p2p) networks are not independent of their peers, and the network efficiency depends on peers contributing resources. Because shared resources are not free, this contribution must be rewarded. Peers across the network may share computation power, storage capacity, and bandwidth. This paper looks at how bandwidth incentive encourages peers to share bandwidth and rewards them for their contribution. With the advent of blockchain technology, many p2p networks attempt to reward contributions by crypto-assets. We conduct simulations to better understand current incentive mechanisms, assess the fairness of these mechanisms, and to look for ways to make those incentives more equitable. The following are the primary contributions of this study: (i) We investigate and simulate bandwidth incentives within Swarm, a cutting-edge p2p storage network; (ii) We demonstrate one approach to make the current bandwidth incentives more equitable; (iii) We use the Gini coefficient to define two quantifiable fairness characteristics to evaluate reward sharing in a decentralized p2p storage network.
The safety-critical scenarios of artificial intelligence (AI), such as autonomous driving, Internet of Things, smart healthcare, etc., have raised critical requirements of trustworthy AI to guarantee the privacy and security with reliable decisions. As a nascent branch for trustworthy AI, federated learning (FL) has been regarded as a promising privacy preserving framework for training a global AI model over collaborative devices. However, security challenges still exist in the FL framework, e.g., Byzantine attacks from malicious devices, and model tampering attacks from malicious server, which will degrade or destroy the accuracy of trained global AI model. In this paper, we shall propose a decentralized blockchain based FL (B-FL) architecture by using a secure global aggregation algorithm to resist malicious devices, and deploying practical Byzantine fault tolerance consensus protocol with high effectiveness and low energy consumption among multiple edge servers to prevent model tampering from the malicious server. However, to implement B-FL system at the network edge, multiple rounds of cross-validation in blockchain consensus protocol will induce long training latency. We thus formulate a network optimization problem that jointly considers bandwidth and power allocation for the minimization of long-term average training latency consisting of progressive learning rounds. We further propose to transform the network optimization problem as a Markov decision process and leverage the deep reinforcement learning based algorithm to provide high system performance with low computational complexity. Simulation results demonstrate that B-FL can resist malicious attacks from edge devices and servers, and the training latency of B-FL can be significantly reduced by deep reinforcement learning based algorithm compared with baseline algorithms.
Today, the audit and diagnosis of the causal relationships between the events in a trigger-action-based event chain (e.g., why is a light turned on in a smart home?) in the Internet of Things (IoT) platforms are untrustworthy and unreliable. The current IoT platforms lack techniques for transparent and tamper-proof ordering of events due to their device-centric logging mechanism. In this paper, we develop a framework that facilitates tamper-proof transparency and event order in an IoT platform by proposing a Blockchain protocol and adopting the vector clock system, both tailored for the resource-constrained heterogeneous IoT devices, respectively. To cope with the unsuited storage (e.g., ledger) and computing power (e.g., proof of work puzzle) requirements of the Blockchain in the commercial off-the-shelf IoT devices, we propose a partial consistent cut protocol and engineer a modular arithmetic-based lightweight proof of work puzzle, respectively. To the best of our knowledge, this is the first Blockchain designed for resource-constrained heterogeneous IoT platforms. Our event ordering protocol based on the vector clock system is also novel for the IoT platforms. We implement our framework using an IoT gateway and 30 IoT devices. We experiment with 10 concurrent trigger-action-based event chains while each chain involves 20 devices, and each device participates in 5 different chains. The results show that our framework may order these events in 2.5 seconds while consuming only 140 mJ of energy per device. The results hence demonstrate the proposed platform as a practical choice for many IoT applications such as smart home, traffic monitoring, and crime investigation.
Non-Fungible Tokens (NFTs) are a new development in blockchain technology. News around NFTs is surrounded by skepticism because unrealistically high prices are being paid online for these NFTs which are in the form of apparently simple digital arts and photographs. It is not clear if this is a trend, a hype, a bubble, or a legitimate novel way of holding and trading value. A literature review of peer-reviewed scholarly studies, performed in the context of business and management, is presented here. Moreover, we also discuss open issues, and challenges, and present future research directions. Analysis of these studies reveal that schools of thoughts are divided on the validity of this form of digital tokens. On one hand, there is a lot of criticism but on the other hand, we can find novel business models and applications of NFTs especially the feature of smart contracts. It can, therefore, be concluded that NFTs, even if not in their current form, are here to stay and may promise new ways of protecting digital assets in an immutable and easily traceable form.
Abstract Blockchain (BC) and software-defined networking (SDN) are leading technologies which have recently found applications in several network-related scenarios and have consequently experienced a growing interest in the research community. Indeed, current networks connect a massive number of objects over the Internet and in this complex scenario, to ensure security, privacy, confidentiality, and programmability, the utilization of BC and SDN have been successfully proposed. In this work, we provide a comprehensive survey regarding these two recent research trends and review the related state-of-the-art literature. We first describe the main features of each technology and discuss their most common and used variants. Furthermore, we envision the integration of such technologies to jointly take advantage of these latter efficiently. Indeed, we consider their group-wise utilization—named BC–SDN—based on the need for stronger security and privacy. Additionally, we cover the application fields of these technologies both individually and combined. Finally, we discuss the open issues of reviewed research and describe potential directions for future avenues regarding the integration of BC and SDN. To summarize, the contribution of the present survey spans from an overview of the literature background on BC and SDN to the discussion of the benefits and limitations of BC–SDN integration in different fields, which also raises open challenges and possible future avenues examined herein. To the best of our knowledge, compared to existing surveys, this is the first work that analyzes the aforementioned aspects in light of a broad BC–SDN integration, with a specific focus on security and privacy issues in actual utilization scenarios.
Aug 2, 2022·the 4th International Workshop on Smart City Communication and Networking (SmartCityCom 2022), in conjunction with the 31st International Conference on Computer Communications and Networks (ICCCN 2022), July 27, 2022
The fast integration of 5G communication, Artificial Intelligence (AI), and Internet-of-Things (IoT) technologies is envisioned to enable Next Generation Networks (NGNs) for diverse smart services and user-defined applications for Smart Cities. However, it is still challenging to build a scalable and efficient infrastructure that satisfies the various performance, security, and management demands by heterogeneous IoT applications across multiple administrative domains. This paper presents a dynamic edge resource federation architecture, which integrates the concept of network slicing (NS) and blockchain to improve scalability, dynamicity, and security for multi-domain IoT applications. A NS-enabled dynamic edge resource federation framework adopts intelligent mechanisms to support efficient multi-domain service coordination that satisfies diverse Quality of Service (QoS) and security requirements. We propose a Hierarchical Integrated Federated Ledger (HIFL), which aims to guarantee decentralized security and privacy-preserving properties in multi-domain resource orchestration and service re-adjustment. As a secure-by-design solution, HIFL is promising to support efficient, trust and secured end-to-end IoT services. A preliminary proof-of-concept prototype has been implemented for comparing intra- and inter-domain performance expectations.
João Paulo de Brito Gonçalves, Gustavo Alochio, Rodolfo da Silva Villaça, Roberta Lima Gomes
The fifth-generation (5G) wireless networks are expected to provide various services compared to the 4G and previous generations of networks. The Quality of Service requirements can be quite different in terms of latency, bandwidth, reliability, and availability. 5G technology allows the fragmentation of the network into small pieces, known as network slices. This network slicing is done by specific tools and the configuration must be protected from attacks that may be performed by malicious users. Thus in this paper, a solution to protect and prevent these failures from happening is addressed. For this solution to be carried out, a study was conducted on the Blockchain technology, as well as the use of Oracles in order to implement an integrity verification system, a system capable of assuring 5G network slices' configuration integrity through a complete architecture involving Blockchain, Smart Contracts and Oracles.
This paper proposes Federated Learning (FL) based smart healthcare system where Medical Centers (MCs) train the local model using the data collected from patients and send the model weights to the miners in a blockchain-based robust framework without sharing raw data, keeping privacy preservation into deliberation. We formulate an optimization problem by maximizing the utility and minimizing the loss function considering energy consumption and FL process delay of MCs for learning effective models on distributed healthcare data underlying a blockchain-based framework. We propose a solution in two stages: first, offer a stable matching-based association algorithm to maximize the utility of both miners and MCs and then solve loss minimization using Stochastic Gradient Descent (SGD) algorithm employing FL under Differential Privacy (DP) and blockchain technology. Moreover, we incorporate blockchain technology to provide tempered resistant and decentralized model weight sharing in the proposed FL-based framework. The effectiveness of the proposed model is shown through simulation on real-world healthcare data comparing other state-of-the-art techniques.
Despite their development for over a decade, a key problem blockchains are still facing is scalability in terms of throughput, typically limited to a few transactions per second. A fundamental factor limiting this metric is the propagation latency of blocks through the underlying peer-to-peer network, which is typically constructed by means of random connectivity. Disseminating blocks fast improves not only the transaction throughput, but also the security of the system as it reduces the probability of forks. In this paper we present CougaR: a simple yet efficient, eclipse-resistant, decentralized protocol that substantially reduces the block dissemination time in blockchain networks. CougaR's key advantages stem from its link selection policy, which combines a network latency criterion with randomness to offer fast and reliable block dissemination to the entire network. Moreover, CougaR is eclipse-resistant by design, as nodes are protected from having all their links directly or indirectly imposed on them by others, which is the typical vulnerability exploited to deploy eclipse attacks. We rigorously evaluate CougaR by an extensive set of experiments, both against a wide spectrum of parameter settings, and in comparison to the current state of the art.
Directed Acyclic Graph (DAG) is a popular approach to achieve scalability of blockchain networks. Due to its high efficiency in data communication and great scalability, DAG has been widely adopted in many applications such as Internet of Things (IoT) and Decentralized Finance (DeFi). DAG-based blockchain, nevertheless, faces the key challenge of transaction inclusion collision due to the high concurrency and the network delay. Particularly, the transaction inclusion collision in DAG-based blockchain leads to the revenue and throughput dilemmas, which would greatly degrade the system performance. In this paper, we propose "TIPS", the Transaction Inclusion Protocol with Signaling, which broadcasts a signal indicating the transactions in the block. We show that with the prompt broadcast of a signal, TIPS substantially reduces the transaction collision and thus resolves these dilemmas. Moreover, we show that TIPS can defend against both the denial-of-service and the delay-of-service attacks. We also conduct intensive experiments to demonstrate the superior performance of the proposed protocol.
The Internet of Things (IoT) can be conveniently deployed while empowering various applications, where the IoT nodes can form clusters to finish certain missions collectively. In this paper, we propose to employ unmanned aerial vehicles (UAVs) to assist the clustered IoT data collection with blockchain-based security provisioning. In particular, the UAVs generate candidate blocks based on the collected data, which are then audited through a lightweight proof-of-stake consensus mechanism within the UAV-based blockchain network. To motivate efficient blockchain while reducing the operational cost, a stake pool is constructed at the active UAV while encouraging stake investment from other UAVs with profit sharing. The problem is formulated to maximize the overall profit through the blockchain system in unit time by jointly investigating the IoT transmission, incentives through investment and profit sharing, and UAV deployment strategies. Then, the problem is solved in a distributed manner while being decoupled into two layers. The inner layer incorporates IoT transmission and incentive design, which are tackled with large-system approximation and one-leader-multi-follower Stackelberg game analysis, respectively. The outer layer for UAV deployment is undertaken with a multi-agent deep deterministic policy gradient approach. Results show the convergence of the proposed learning process and the UAV deployment, and also demonstrated is the performance superiority of our proposal as compared with the baselines.
Mohammad Hossein Tabatabaei, Roman Vitenberg, Narasimha Raghavan Veeraragavan
The explosive advent of the blockchain technology has led to hundreds of blockchain systems in the industry, thousands of academic papers published over the last few years, and an even larger number of new initiatives and projects. Despite the emerging consolidation efforts, the area remains highly turbulent without systematization, educational materials, or cross-system comparative analysis. In this paper, we provide a systematic and comprehensive study of four popular yet widely different blockchain systems: Bitcoin, Ethereum, Hyperledger Fabric, and IOTA. The study is presented as a cross-system comparison, which is organized by clearly identified aspects: definitions, roles of the participants, entities, and the characteristics and design of each of the commonly used layers in the cross-system blockchain architecture. Our exploration goes deeper compared to what is currently available in academic surveys and tutorials. For example, we provide the first extensive coverage of the storage layer in Ethereum and the most comprehensive explanation of the consensus protocol in IOTA. The exposition is due to the consolidation of fragmented information gathered from white and yellow papers, academic publications, blogs, developer documentation, communication with the developers, as well as additional analysis gleaned from the source code. We hope that this survey will help the readers gain in-depth understanding of the design principles behind blockchain systems and contribute towards systematization of the area.
Michael Pacheco, Gustavo A. Oliva, Gopi Krishnan Rajbahadur, Ahmed E. Hassan
The Ethereum platform allows developers to implement and deploy applications called Dapps onto the blockchain for public use through the use of smart contracts. To execute code within a smart contract, a paid transaction must be issued towards one of the functions that are exposed in the interface of a contract. However, such a transaction is only processed once one of the miners in the peer-to-peer network selects it, adds it to a block, and appends that block to the blockchain This creates a delay between transaction submission and code execution. It is crucial for Dapp developers to be able to precisely estimate when transactions will be processed, since this allows them to define and provide a certain Quality of Service (QoS) level (e.g., 95% of the transactions processed within 1 minute). However, the impact that different factors have on these times have not yet been studied. Processing time estimation services are used by Dapp developers to achieve predefined QoS. Yet, these services offer minimal insights into what factors impact processing times. Considering the vast amount of data that surrounds the Ethereum blockchain, changes in processing times are hard for Dapp developers to predict, making it difficult to maintain said QoS. In our study, we build random forest models to understand the factors that are associated with transaction processing times. We engineer several features that capture blockchain internal factors, as well as gas pricing behaviors of transaction issuers. By interpreting our models, we conclude that features surrounding gas pricing behaviors are very strongly associated with transaction processing times. Based on our empirical results, we provide Dapp developers with concrete insights that can help them provide and maintain high levels of QoS.
Several types of networks that comprise unmanned aerial vehicles (UAV or drone) are being utilized in important applications such as emergency response, environment and infrastructure monitoring, defense and security, and commerce. In such networks, swarms of UAVs cooperate in executing one or more missions to achieve the application's objectives. The UAVs communicate with terrestrial networks by connecting to fixed or mobile ground control stations (GCS). The ability of drones to connect to online applications and offer services to Internet users has led to the proliferation of the Internet of Drones (IoD). However, IoD applications are highly vulnerable to many types of cyberattacks. Hence, mechanisms must be deployed to secure the IoD operations and data. Recently, the blockchain has been proposed as a solution to detect and prevent malicious attacks on the UAV network (UAVN). Due to the UAV's limited resources, it becomes a challenge to integrate the blockchain into the IoD. In this paper, we propose a model that enables a drone to store the important data that it requires during its flight within a lightweight blockchain system. In addition, we propose a new blockchain consensus mechanism in which several miners produce their blocks in parallel, which decreases the time needed to add transactions securely to the blockchain and meets the requirements of delay-sensitive applications. Our simulations prove the advantages of the proposed model in decreasing the transaction-to-blockchain delay, the average drone energy consumption, and the blockchain block size as compared to other IoD blockchain systems.
Federated learning (FL), thanks in part to the emergence of the edge computing paradigm, is expected to enable true real-time applications in production environments. However, its original dependence on a central server for orchestration raises several concerns in terms of security, privacy, and scalability. To solve some of these worries, blockchain technology is expected to bring decentralization, robustness, and enhanced trust to FL. The empowerment of FL through blockchain (also referred to as FLchain), however, has some implications in terms of ledger inconsistencies and age of information (AoI), which are naturally inherited from the blockchain's fully decentralized operation. Such issues stem from the fact that, given the temporary ledger versions in the blockchain, FL devices may use different models for training, and that, given the asynchronicity of the FL operation, stale local updates (computed using outdated models) may be generated. In this paper, we shed light on the implications of the FLchain setting and study the effect that both the AoI and ledger inconsistencies have on the FL performance. To that end, we provide a faithful simulation tool that allows capturing the decentralized and asynchronous nature of the FLchain operation.
Blockchain-based IoT systems can manage IoT devices and achieve a high level of data integrity, security, and provenance. However, incorporating existing consensus protocols in many IoT systems limits scalability and leads to high computational cost and consensus latency. In addition, location-centric characteristics of many IoT applications paired with limited storage and computing power of IoT devices bring about more limitations, primarily due to the location-agnostic designs in blockchains. We propose a hierarchical and location-aware consensus protocol (LH-Raft) for IoT-blockchain applications inspired by the original Raft protocol to address these limitations. The proposed LH-Raft protocol forms local consensus candidate groups based on nodes' reputation and distance to elect the leaders in each sub-layer blockchain. It utilizes a threshold signature scheme to reach global consensus and the local and global log replication to maintain consistency for blockchain transactions. To evaluate the performance of LH-Raft, we first conduct an extensive numerical analysis based on the proposed reputation mechanism and the candidate group formation model. We then compare the performance of LH-Raft against the classical Raft protocol from both theoretical and experimental perspectives. We evaluate the proposed threshold signature scheme using Hyperledger Ursa cryptography library to measure various consensus nodes' signing and verification time. Experimental results show that the proposed LH-Raft protocol is scalable for large IoT applications and significantly reduces the communication cost, consensus latency, and agreement time for consensus processing.
Shiva Kazemi Taskou, Mehdi Rasti, Pedro H. J. Nardelli
Many of the key enabling technologies of the fifth-generation (5G), such as network slicing, spectrum sharing, and federated learning, rely on a centralized authority. This may lead to pitfalls in terms of security or single point of failure. Distributed ledger technology, specifically blockchain, is currently employed by different applications related to the Internet of Things (IoT) and 5G to address the drawbacks of centralized systems. For this reason, mobile blockchain networks (MBNs) have recently attracted a great deal of attention. To add a transaction to the blockchain in MBNs, mobile or IoT users must perform various tasks like encryption, decryption, and mining. These tasks require energy and processing power, which impose limitations on mobile and IoT users' performance because they are usually battery powered and have a low processing power. One possible solution is to perform the tasks virtually on commodity servers provided by mobile edge computing (MEC) or cloud computing. To do so, all tasks needed to add a transaction to the blockchain can be treated as virtual blockchain functions that can be executed on commodity servers. We introduce a blockchain virtualization framework called blockchain function virtualization (BFV), through which all blockchain functions can be performed virtually by MEC or cloud computing. Furthermore, we describe applications of the BFV framework and resource allocation challenges brought by the BFV framework in mobile networks. In addition, to illustrate the advantages of BFV, we define an optimization problem to simultaneously minimize the energy consumption cost and maximize miners' rewards. Finally, simulation results show the performance of the proposed framework in terms of total energy consumption, transaction confirmation rate, and miners' average profit.
Cordial Miners are a family of efficient Byzantine Atomic Broadcast protocols, with instances for asynchrony and eventual synchrony. They improve the latency of state-of-the-art DAG-based protocols by almost 2X and achieve optimal good-case complexity of O(n) by forgoing Reliable Broadcast as a building block. Rather, Cordial Miners use the blocklace -- a partially-ordered counterpart of the totally-ordered blockchain data structure -- to implement the three algorithmic components of consensus: Dissemination, equivocation-exclusion, and ordering.
Vipindev Adat Vasudevan, Muhammad Tayyab, George P. Koudouridis, Xavier Gelabert · 5 authors
Future wireless networks must serve dense mobile networks with high data rates, keeping energy requirements to a possible minimum. The small cell-based network architecture and device-to-device (D2D) communication are already being considered part of 5G networks and beyond. In such environments, network coding (NC) can be employed to achieve both higher throughput and energy efficiency. However, NC-enabled systems need to address security challenges specific to NC, such as pollution attacks. All integrity schemes against pollution attacks generally require proper key distribution and management to ensure security in a mobile environment. Additionally, the mobility requirements in small cell environments are more challenging and demanding in terms of signaling overhead. This paper proposes a blockchain-assisted key distribution protocol tailored for MAC-based integrity schemes, which combined with an uplink reference signal (UL RS) handover mechanism, enables energy efficient secure NC. The performance analysis of the protocol during handover scenarios indicates its suitability for ensuring high level of security against pollution attacks in dense small cell environments with multiple adversaries being present. Furthermore, the proposed scheme achieves lower bandwidth and signaling overhead during handover compared to legacy schemes and the signaling cost reduces significantly as the communication progresses, thus enhancing the network's cumulative energy efficiency.
Weizhao Tang, Lucianna Kiffer, Giulia Fanti, Ari Juels
Most permissionless blockchain networks run on peer-to-peer (P2P) networks, which offer flexibility and decentralization at the expense of performance (e.g., network latency). Historically, this tradeoff has not been a bottleneck for most blockchains. However, an emerging host of blockchain-based applications (e.g., decentralized finance) are increasingly sensitive to latency; users who can reduce their network latency relative to other users can accrue (sometimes significant) financial gains. In this work, we initiate the study of strategic latency reduction in blockchain P2P networks. We first define two classes of latency that are of interest in blockchain applications. We then show empirically that a strategic agent who controls only their local peering decisions can manipulate both types of latency, achieving 60\% of the global latency gains provided by the centralized, paid service bloXroute, or, in targeted scenarios, comparable gains. Finally, we show that our results are not due to the poor design of existing P2P networks. Under a simple network model, we theoretically prove that an adversary can always manipulate the P2P network's latency to their advantage, provided the network experiences sufficient peer churn and transaction activity.