Cui Zhang, Maoxin Ji, Qiong Wu, Pingyi Fan · 5 authors
In the Internet of Vehicles (IoV), Age of Information (AoI) has become a vital performance metric for evaluating the freshness of information in communication systems. Although many studies aim to minimize the average AoI of the system through optimized resource scheduling schemes, they often fail to adequately consider the queue characteristics. Moreover, the vehicle mobility leads to rapid changes in network topology and channel conditions, making it difficult to accurately reflect the unique characteristics of vehicles with the calculated AoI under ideal channel conditions. This paper examines the impact of Doppler shifts caused by vehicle speeds on data transmission in error-prone channels. Based on the M/M/1 and D/M/1 queuing theory models, we derive expressions for the Age of Information and optimize the system's average AoI by adjusting the data extraction rates of vehicles (which affect system utilization). We propose an online optimization algorithm that dynamically adjusts the vehicles' data extraction rates based on environmental changes to ensure optimal AoI. Simulation results have demonstrated that adjusting the data extraction rates of vehicles can significantly reduce the system's AoI. Additionally, in the network scenario of this work, the AoI of the D/M/1 system is lower than that of the M/M/1 system.
The current Domain Name System (DNS), as a core infrastructure of the internet, exhibits several shortcomings: its centralized architecture leads to censorship risks and single points of failure, making domain name resolution vulnerable to attacks. The lack of encryption in the resolution process exposes it to DNS hijacking and cache poisoning attacks. Additionally, the high operational costs limit participation and innovation among small to medium-sized users. To address these issues, this paper proposes a Decentralized Domain Name Service (DDNS) based on blockchain (Phicoin) and distributed storage (IPFS). By leveraging the immutability of blockchain and the content verification of IPFS, the system achieves decentralized storage and distribution of domain name records, eliminating the centralized dependencies of traditional DNS. With a block time of 15 seconds, the system supports rapid broadcasting of domain name updates, significantly improving resolution efficiency. The DDNS aims to serve as a complement or backup to the existing DNS system, providing a pollution-resistant, censorship-resistant, high-performance, and low-cost domain name resolution solution, offering a new technical path for the security and stability of the internet.
In the rapidly evolving landscape of the Metaverse, enhanced by blockchain technology, the efficient processing of data has emerged as a critical challenge, especially in wireless communication systems. Addressing this need, our paper introduces the innovative concept of data processing efficiency (DPE), aiming to maximize processed bits per unit of resource consumption in blockchain-empowered Metaverse environments. To achieve this, we propose the DPE-Aware User Association and Resource Allocation (DAUR) algorithm, a tailored solution for these complex systems. The DAUR algorithm transforms the challenging task of optimizing the sum of DPE ratios into a solvable convex optimization problem. It uniquely alternates the optimization of key variables like user association, work offloading ratios, task-specific computing resource distribution, bandwidth allocation, user power usage ratios, and server computing resource allocation ratios. Our extensive numerical results demonstrate the DAUR algorithm's effectiveness in DPE.
The evolution of vehicle-to-everything (V2X) communication brings significant challenges, such as data integrity and vulnerabilities stemming from centralized management. This paper presents an innovative integration of decentralized blockchain technology with V2X communication through a multi-layered architecture that combines the Simulation of Urban Mobility (SUMO) traffic simulator and the BlockSim blockchain simulator. In addition, as the Social Internet of Vehicles (SIoV) emerges, efficient resource management becomes indispensable for ensuring seamless communication. We also propose a reference multi-connectivity management method named Enhanced MAX-SINR, designed to advance research in blockchain-specific approaches, taking into account retransmission successfull rates. We evaluate blockchain performance in diverse environments such as urban, suburban, and rural areas, demonstrating that enhancing the success rate of retransmitted blockchain-related messages significantly boosts blockchain transaction performance and provides a foundation for developing intelligent SIoV systems.
We hypothesize that peer-to-peer (P2P) overlay network nodes can be attractive to attackers due to their visibility, sustained uptime, and resource potential. Towards validating this hypothesis, we investigate the state of active reconnaissance attacks on Ethereum P2P network nodes by deploying a series of honeypots alongside actual Ethereum nodes across globally distributed vantage points. We find that Ethereum nodes experience not only increased attacks, but also specific types of attacks targeting particular ports and services. Furthermore, we find evidence that the threat assessment on our nodes is applicable to the wider P2P network by having performed port scans on other reachable peers. Our findings provide insights into potential mitigation strategies to improve the security of the P2P networking layer.
The Web3 ecosystem is highly fragmented, making seamless integration difficult for over a billion Web2 businesses, enterprises, and AI protocols. As blockchains, rollups, and app-specific chains expand, cross-chain interactions remain inefficient, and liquidity is deeply fragmented. AI systems lack standardized blockchain access, limiting autonomous functionality. Intent-based interactions, crucial for AI-driven automation, face scalability issues due to the absence of robust execution platforms. Meanwhile, the current solver ecosystem is centralized, as liquidity rebalancing remains a challenge due to a lack of developer-friendly tools. Dojima's Omnichain Web introduces a universal framework that abstracts blockchain complexity, bridging Web2, Web3, and AI. At its core, OmniRollups facilitate scalable execution across chains, while the Omni Sequencer ensures atomic, secure intent processing. Linera microchains enable AI-driven transaction automation, seamlessly integrating with Web3 data streams. Ragno Network decentralizes L1 infrastructure, optimizing cross-chain liquidity flows, while the Proof Network enhances cryptographic security for omnichain transactions. Finally, the Builder Marketplace introduces a solver-driven execution layer, allowing developers to build and monetize intent-based applications without liquidity constraints. By fostering a composable marketplace at the intersection of Web2 and Web3, Omnichain Web enables the seamless flow of data, value, and computation. This framework mirrors the internet, bridging Web3 decentralization with Web2 scale to drive the next wave of adoption.
Many nations are promoting the green transition in the energy sector to attain neutral carbon emissions by 2050. Smart Grid 2.0 (SG2) is expected to explore data-driven analytics and enhance communication technologies to improve the efficiency and sustainability of distributed renewable energy systems. These features are beyond smart metering and electric surplus distribution in conventional smart grids. Given the high dependence on communication networks to connect distributed microgrids in SG2, potential cascading failures of connectivity can cause disruption to data synchronization to the remote control systems. This paper reviews security threats and defense tactics for three stakeholders: power grid operators, communication network providers, and consumers. Through the survey, we found that SG2's stakeholders are particularly vulnerable to substation attacks/vandalism, malware/ransomware threats, blockchain vulnerabilities and supply chain breakdowns. Furthermore, incorporating artificial intelligence (AI) into autonomous energy management in distributed energy resources of SG2 creates new challenges. Accordingly, adversarial samples and false data injection on electricity reading and measurement sensors at power plants can fool AI-powered control functions and cause messy error-checking operations in energy storage, wrong energy estimation in electric vehicle charging, and even fraudulent transactions in peer-to-peer energy trading models. Scalable blockchain-based models, physical unclonable function, interoperable security protocols, and trustworthy AI models designed for managing distributed microgrids in SG2 are typical promising protection models for future research.
This letter presents a blockchain-based multi-path mobile access point (MAP) selection strategy for secure 5G vehicular ad-hoc networks (VANETs). The proposed method leverages blockchain technology for decentralized, transparent, and secure MAP selection, while the multi-path transmission strategy enhances network reliability and reduces communication delays. A trust-based attack detection mechanism is integrated to ensure network security. Simulation results demonstrate that the proposed algorithm reduces both handover frequency and average communication delay by over 80%, and successfully identifies and excludes more than 95% of Sybil nodes, ensuring reliable and secure communication in highly dynamic vehicular environments.
Manu Drijvers, Tim Gretler, Yotam Harchol, Tobias Klenze · 10 authors
Byzantine fault tolerant (BFT) protocol descriptions often assume application-layer networking primitives, such as best-effort and reliable broadcast, which are impossible to implement in practice in a Byzantine environment as they require either unbounded buffering of messages or giving up liveness, under certain circumstances. However, many of these protocols do not (or can be modified to not) need such strong networking primitives. In this paper, we define a new, slightly weaker networking primitive that we call abortable broadcast. We describe an implementation of this new primitive and show that it (1) still provides strong delivery guarantees, even in the case of network congestion, link or peer failure, and backpressure, (2) preserves bandwidth, and (3) enforces all data structures to be bounded even in the presence of malicious peers. The latter prevents out-of-memory DoS attacks by malicious peers, an issue often overlooked in the literature. The new primitive and its implementation are not just theoretical. We use them to implement the BFT protocols in the IC (Internet Computer), a publicly available blockchain network that enables replicated execution of general-purpose computation, serving hundreds of thousands of applications and their users.
Quantum devices capable of breaking the public-key cryptosystems that Bitcoin relies on to secure its transactions are expected with reasonable probability within a decade. Quantum attacks would put at risk the entire Bitcoin network, which has an estimated value of around 500 billion USD. To prevent this threat, a proactive approach is critical. The only known way to prevent any such attack is to upgrade the currently used public-key cryptosystems, namely ECDSA, with so-called post-quantum cryptosystems which have no known vulnerabilities to quantum attacks. In this paper, we analyse the technical cost of such an upgrade. We calculate a non-tight lower bound on the cumulative downtime required for the above transition to be 1827.96 hours, or 76.16 days. We also demonstrate that the transition needs to be fully completed before the availability of ECDSA-256 breaking quantum devices, in order to ensure Bitcoin's ongoing security. The conclusion is that the Bitcoin upgrade to quantum-safe protocols needs to be started as soon as possible in order to guarantee its ongoing operations.
The Lightning Network is a peer-to-peer network designed to address Bitcoin's scalability challenges, facilitating rapid, cost-effective, and instantaneous transactions through bidirectional, blockchain-backed payment channels among network peers. Due to a source-based routing of payments, different pathfinding strategies are used in practice, trading off different objectives for each other such as payment reliability and routing fees. This paper explores differences within pathfinding strategies used by prominent Lightning Network node implementations, which include different underlying cost functions and different constraints, as well as different greedy algorithms of shortest path-type. Surprisingly, we observe that the pathfinding problems that most LN node implementations attempt to solve are NP-complete, and cannot be guaranteed to be optimally solved by the variants of Dijkstra's algorithm currently deployed in production. Through comparative analysis and simulations, we evaluate efficacy of different pathfinding strategies across metrics such as success rate, fees, path length, and timelock. Our experiments indicate that the strategies used by Eclair are advantageous in terms of payment reliability and result in paths with low fees. LND exhibits moderate success rates, while LDK results in paths with higher fee levels for smaller payment amounts; furthermore, CLN stands out for its minimal timelock paths. Additionally, we investigate the impact of Lightning node connectivity levels on routing efficiency. The findings of our analysis provide insights towards future improvements of pathfinding strategies and algorithms used within the Lightning Network.
With the widespread adoption of medical informatics, a wealth of valuable personal health records (PHR) has been generated. Concurrently, blockchain technology has enhanced the security of medical institutions. However, these institutions often function as isolated data silos, limiting the potential value of PHRs. As the demand for data sharing between hospitals on different blockchains grows, addressing the challenge of cross-chain data sharing becomes crucial. When sharing PHRs across blockchains, the limited storage and computational capabilities of medical Internet of Things (IoT) devices complicate the storage of large volumes of PHRs and the handling of complex calculations. Additionally, varying blockchain cryptosystems and the risk of internal attacks further complicate the cross-chain sharing of PHRs. This paper proposes a scheme for sharing PHRs across heterogeneous and interoperable blockchains. Medical IoT devices can encrypt and store real-time PHRs in an InterPlanetary File System, requiring only simple operations for data sharing. An enhanced proxy re-encryption(PRE) algorithm addresses the differences in blockchain cryptosystems. Multi-dimensional analysis demonstrates that this scheme offers robust security and excellent performance.
Blockchain technology holds promise for Web 3.0, but scalability remains a critical challenge. Here, we present a mathematical theory for a novel blockchain network topology based on fractal N-dimensional simplexes. This Hyper-simplex fractal network folds one-dimensional data blocks into geometric shapes, reflecting both underlying and overlaying network connectivities. Our approach offers near-infinite scalability, accommodating trillions of nodes while maintaining efficiency. We derive the mathematical foundations for generating and describing these network topologies, proving key properties such as node count, connectivity patterns, and fractal dimension. The resulting structure facilitates a hierarchical consensus mechanism and enables deterministic address mapping for rapid routing. This theoretical framework lays the groundwork for next-generation blockchain architectures, potentially revolutionizing large-scale decentralized systems. The Part I work was conducted between March and September 2024.
The rapid expansion of Internet of Vehicles (IoV) deployments has necessitated the creation of efficient and secure routing models to manage the massive data traffic generated by interconnected devices & vehicles. For IoV deployments, we propose a novel fan-shaped trust-based routing model with Quality of Service (QoS) and security-aware side-chaining. Our method employs temporal levels of delay, throughput, Packet Delivery Ratio (PDR), and energy consumption to determine optimal routing paths, thereby ensuring efficient data transmissions. We employ the Bacterial Foraging Optimizer (BFO) algorithm to manage side-chains within the network, which dynamically adjusts side-chain configurations to optimize system performance. The technique of fan-shaped clustering is used to group nodes into efficient clusters, allowing for more efficient communication and resource utilization sets. Extensive experimentation and performance analysis are utilized to evaluate the proposed model. Existing blockchain-based security models have been significantly improved by our findings. Our model achieves a remarkable 9.5% reduction in delay, a 10.5% improvement in throughput, a 2.9% improvement in PDR, and a 4.5% reduction in energy consumption compared to alternative approaches. In addition, we evaluate the model's resistance to Sybil, Masquerading, and Flooding attacks, which are prevalent security threats for IoV deployments. Even under these attack scenarios, our model provides consistently higher QoS levels compared to existing solutions, ensuring uninterrupted and reliable data transmissions. In IoV deployments, the proposed routing model and side-chaining management approach have numerous applications and use-cases like Smart cities, industrial automation, healthcare systems, transportation networks, and environmental monitoring.
Open-science collaboration using Jupyter Notebooks may expose expensively trained AI models, high-performance computing resources, and training data to security vulnerabilities, such as unauthorized access, accidental deletion, or misuse. The ubiquitous deployments of Jupyter Notebooks (~11 million public notebooks on Github have transformed collaborative scientific computing by enabling reproducible research. Jupyter is the main HPC's science gateway interface between AI researchers and supercomputers at academic institutions, such as the National Center for Supercomputing Applications (NCSA), national labs, and the industry. An impactful attack targeting Jupyter could disrupt scientific missions and business operations. This paper describes the network-based attack taxonomy of Jupyter Notebooks, such as ransomware, data exfiltration, security misconfiguration, and resource abuse for cryptocurrency mining. The open nature of Jupyter (direct data access, arbitrary code execution in multiple programming languages kernels) and its vast attack interface (terminal, file browser, untrusted cells) also attract attacks attempting to misuse supercomputing resources and steal state-of-the-art research artifacts. Jupyter uses encrypted datagrams of rapidly evolving WebSocket protocols that challenge even the most state-of-the-art network observability tools, such as Zeek. We envisage even more sophisticated AI-driven attacks can be adapted to target Jupyter, where defenders have limited visibility. In addition, Jupyter's cryptographic design should be adapted to resist emerging quantum threats. On balance, this is the first paper to systematically describe the threat model against Jupyter Notebooks and lay out the design of auditing Jupyter to have better visibility against such attacks.
Md. Rafid Haque, Sakibul Islam Munna, Sabbir Ahmed, Md. Tariqul Islam · 6 authors
Centralized version control systems (VCS) are vital for software development but pose risks of data loss and ownership disputes. While blockchain offers a decentralized alternative, existing solutions are often hindered by high latency, compromising the real-time collaboration essential for modern workflows. This study introduces a novel hybrid architecture combining the security of the Ethereum blockchain and the InterPlanetary File System (IPFS) with two key contributions: 1) Shamir's Secret Sharing (SSS) to create a trust-minimized model for key distribution, and 2) an authoritative-first, optimistic-fallback retrieval protocol utilizing a temporary middleware to decouple the user experience from blockchain confirmation delays. We implemented a full prototype and conducted a comprehensive performance evaluation on the public Sepolia testnet. Our results demonstrate that this architecture not only provides a secure, auditable, and resilient platform for source code hosting but also achieves highly competitive user-perceived performance. Our user-perceived push time reduces submission latency by up to 49% compared to a standard git push for common repository sizes, proving that a well-designed decentralized VCS can balance the core tenets of security and decentralization with the practical need for speed and efficiency.
The Internet of Vehicles (IoV), which enables interactions between vehicles, infrastructure, and the environment, faces challenges in maintaining communication security and reliable automated decisions. This paper introduces a decentralized framework comprising a primary layer for managing inter-vehicle communication and a sub-layer for securing intra-vehicle interactions. By implementing blockchain-based protocols like Blockchain-integrated Secure Authentication (BiSA) and Decentralized Blockchain Name Resolution (DBNR), the framework ensures secure, decentralized identity management and reliable data exchanges, thereby supporting safe and efficient autonomous vehicle operations.
Vehicular Fog Computing (VFC) is significantly enhancing the efficiency, safety, and computational capabilities of Intelligent Transportation Systems (ITS), and the integration of Unmanned Aerial Vehicles (UAVs) further elevates these advantages by incorporating flexible and auxiliary services. This evolving UAV-integrated VFC paradigm opens new doors while presenting unique complexities within the cooperative computation framework. Foremost among the challenges, modeling the intricate dynamics of aerial-ground interactive computing networks is a significant endeavor, and the absence of a comprehensive and flexible simulation platform may impede the exploration of this field. Inspired by the pressing need for a versatile tool, this paper provides a lightweight and modular aerial-ground collaborative simulation platform, termed AirFogSim. We present the design and implementation of AirFogSim, and demonstrate its versatility with five key missions in the domain of UAV-integrated VFC. A multifaceted use case is carried out to validate AirFogSim's effectiveness, encompassing several integral aspects of the proposed AirFogSim, including UAV trajectory, task offloading, resource allocation, and blockchain. In general, AirFogSim is envisioned to set a new precedent in the UAV-integrated VFC simulation, bridge the gap between theoretical design and practical validation, and pave the way for future intelligent transportation domains. Our code will be available at https://github.com/ZhiweiWei-NAMI/AirFogSim.
Mahdi Akbari Zarkesh, Ehsan Dastani, Bardia Safaei, Ali Movaghar
The pervasive adoption of Internet of Things (IoT) has significantly advanced healthcare digitization and modernization. Nevertheless, the sensitive nature of medical data presents security and privacy challenges. On the other hand, resource constraints of IoT devices often necessitates cloud services for data handling, introducing single points of failure, processing delays, and security vulnerabilities. Meanwhile, the blockchain technology offers potential solutions for enhancing security, decentralization, and data ownership. An ideal solution should ensure confidentiality, access control, and data integrity while being scalable, cost-effective, and integrable with the existing systems. However, current blockchain-based studies only address some of these requirements. Accordingly, this paper proposes EdgeLinker; a comprehensive solution incorporating Proof-of-Authority consensus, integrating smart contracts on the Ethereum blockchain for access control, and advanced cryptographic algorithms for secure data communication between IoT edge devices and the fog layer in healthcare fog applications. This novel framework has been implemented in a real-world fog testbed, using COTS fog devices. Based on a comprehensive set of evaluations, EdgeLinker demonstrates significant improvements in security and privacy with reasonable costs, making it an affordable and practical system for healthcare fog applications. Compared with the state-of-the-art, without significant changes in the write-time to the blockchain, EdgeLinker achieves a 35% improvement in data read time. Additionally, it is able to provide better throughput in both reading and writing transactions compared to the existing studies. EdgeLinker has been also examined in terms of energy, resource consumption and channel latency in both secure and non-secure modes, which has shown remarkable improvements.
Crowd-sensing has emerged as a powerful data retrieval model, enabling diverse applications by leveraging active user participation. However, data availability and privacy concerns pose significant challenges. Traditional methods like data encryption and anonymization, while essential, may not fully address these issues. For instance, in sparsely populated areas, anonymized data can still be traced back to individual users. Additionally, the volume of data generated by users can reveal their identities. To develop credible crowd-sensing systems, data must be anonymized, aggregated and separated into uniformly sized chunks. Furthermore, decentralizing the data management process, rather than relying on a single server, can enhance security and trust. This paper proposes a system utilizing smart contracts and blockchain technologies to manage crowd-sensing campaigns. The smart contract handles user subscriptions, data encryption, and decentralized storage, creating a secure data marketplace. Incentive policies within the smart contract encourage user participation and data diversity. Simulation results confirm the system's viability, highlighting the importance of user participation for data credibility and the impact of geographical data scarcity on rewards. This approach aims to balance data origin and reduce cheating risks.
Smart contracts are widely utilized in cross-chain interactions, where their results are transmitted from one blockchain (the producer blockchain) to another (the consumer blockchain). Unfortunately, the consumer blockchain often accepts these results without executing the smart contracts for validation, posing potential security risks. To address this, we propose a method for validating cross-chain smart contract results. Our approach emphasizes consumer blockchain execution of cross-chain smart contracts of producer blockchain, allowing comparison of results with the transmitted ones to detect potential discrepancies and ensure data integrity during cross-chain data dissemination. Additionally, we introduce the confirmation with proof method, which involves incorporating the chain of blocks and relevant cross-chain smart contract data from the producer blockchain into the consumer blockchain as evidence (or proof), establishing a unified and secure perspective of cross-chain smart contract results. Our verification results highlight the feasibility of cross-chain validation at the smart contract level.
Naseem Alsadi, Syed Zaidi, Mankaran Rooprai, Stephen A. Gadsden · 5 authors
The internet of things (IoT) and other emerging ubiquitous technologies are supporting the rapid spread of smart systems, which has underlined the need for safe, open, and decentralized data storage solutions. With its inherent decentralization and immutability, blockchain offers itself as a potential solution for these requirements. However, the practicality of incorporating blockchain into real-time sensor data storage systems is a topic that demands in-depth examination. While blockchain promises unmatched data security and auditability, some intrinsic qualities, namely scalability restrictions, transactional delays, and escalating storage demands, impede its seamless deployment in high-frequency, voluminous data contexts typical of real-time sensors. This essay launches a methodical investigation into these difficulties, illuminating their underlying causes, potential effects, and potential countermeasures. In addition, we present a novel pragmatic experimental setup and analysis of blockchain for smart system applications, with an extended discussion of the benefits and disadvantages of deploying blockchain based solutions for smart system ecosystems.
Symbiotic communication (SC) is known as a new wireless communication paradigm, similar to the natural ecosystem population, and can enable multiple communication systems to cooperate and mutualize through service exchange and resource sharing. As a result, SC is seen as an important potential technology for future sixth-generation (6G) communications, solving the problem of lack of spectrum resources and energy inefficiency. Symbiotic relationships among communication systems can complement radio resources in 6G. However, the absence of established trust relationships among diverse communication systems presents a formidable hurdle in ensuring efficient and trusted resource and service exchange within SC frameworks. To better realize trusted SC services in 6G, in this paper, we propose a solution that converges SC and blockchain, called a symbiotic blockchain network (SBN). Specifically, we first use cognitive backscatter communication to transform blockchain consensus, that is, the symbiotic blockchain consensus (SBC), so that it can be better suited for the wireless network. Then, for SBC, we propose a highly energy-efficient sharding scheme to meet the extremely low power consumption requirements in 6G. Finally, such a blockchain scheme guarantees trusted transactions of communication services in SC. Through ablation experiments, our proposed SBN demonstrates significant efficacy in mitigating energy consumption and reducing processing latency in adversarial networks, which is expected to achieve a sustainable and trusted 6G wireless network.
In the digital era, where innovative technologies like blockchain are revolutionizing traditional organizational paradigms, Decentralized Autonomous Organizations (DAOs) emerge as avant-garde models of collective governance. However, their unique structure challenges existing legal frameworks, especially concerning the liability of participants. This study focuses on analyzing the legal implications of the decentralized nature of DAOs, with a particular emphasis on the aspects of participant liability. Such considerations are essential for understanding how current legal systems might be adapted or reformed to effectively address these novel challenges. The paper examines the specificity of DAOs, highlighting their decentralized governance structure and reliance on smart contracts, which introduce unique issues related to the blurring of liability boundaries. It underscores how the anonymity of DAO participants and the automatic execution of smart contracts complicate the traditional concept of legal liability, both within the DAO context and in interactions with external parties. The analysis also includes a comparison between DAOs and traditional organizational forms, such as corporations and associations, to identify potential analogies and differences in participant liability. It explores how existing regulations on partner liability might be insufficient or inapplicable in the DAO context, prompting the search for new, innovative legal solutions.