The high aggregation of user relationship and behavioral data in social networks continues to aggravate privacy leaks. How to strike a balance between privacy protection and data availability has become a research hotspot. To collaboratively optimize user information security and community structure identification, this study proposes a social network privacy protection model that integrates differential privacy technology and community discovery algorithms. First, a differential privacy noise injection mechanism is constructed to perturb node data and combine it with blockchain storage to ensure that the data cannot be tampered with. Then, a community division strategy based on information entropy and mutual information is introduced to achieve high-precision community identification through modularity optimization. The accuracy of the proposed model reached 98.1% when the data set size was 800, which was about 3.4% and 9% higher than that of other models, respectively. The root mean square error was 8.2, which was about 20% lower than that of the traditional model. The convergence speed was increased to 380 iterations, which was about 15% faster than that of the comparison algorithm. The privacy protection strength and scalability scores reached 9.3 and 9.5, respectively. The simulation test results showed that, under different data types, the accuracy of the model grew from 0.87 to 0.98, and the F1 value grew from 0.84 to 0.95. The integration of differential privacy and community discovery effectively improves the privacy protection strength and structural analysis accuracy of social networks, providing a highly feasible solution for multi-scenario social data security analysis.
Edison Andres Arteaga Lopez, Gustavo Ramírez-González, Andrea Sabbioni, Carlos A. Astudillo
Abstract Distributed ledger technologies (DLT) can enhance trust and auditability in the Internet of Things (IoT). Among them, IOTA has been specifically designed to support machine-to-machine interactions and IoT data anchoring through scalable DLT architectures. However, their integration with Low-Power Wide-Area Networks (LPWANs) remains limited due to device constraints, strict timing requirements, and the operational costs of on-chain transactions. The transition from the fee-less Stardust to the fee-based IOTA Rebased model introduces explicit transaction costs, questioning the viability of continuous IoT data anchoring. IOTA provides a suitable platform to examine the challenges of integrating distributed ledger technologies with LPWAN-based IoT systems. Its transition to a fee-based execution model raises important questions regarding cost predictability and performance in continuous data anchoring scenarios, particularly under the constraints of resource-limited and latency-sensitive environments. This article investigates the practicality of the execution and payment model introduced by IOTA Rebased for IoT scenarios requiring continuous data notarization. We provide an empirical evaluation of continuous IoT data notarization on the public IOTA Rebased Mainnet and characterize the performance implications on edge-oriented deployments, including resource-constrained and resource-rich devices. We implement a notarization oracle that ingests LoRaWAN uplinks from The Things Network (TTN), canonicalizes payloads, generates SHA-256 commitments, and records them on-chain through reusable notarization objects. The oracle enables continuous anchoring of IoT telemetry while minimizing transaction overhead through object reuse. Two 24-h experimental campaigns compare a notarization oracle on resource-constrained and resource-rich hardware under periodic workloads. Results show consistent steady-state gas consumption for UPDATE operations, indicating that object reuse enables stable on-chain cost behavior in IOTA Rebased regardless of the deployment platform. From a performance perspective, both environments achieve stable execution; however, the resource-constrained edge deployment exhibits higher median and tail latency, alongside tighter memory margins compared to the resource-rich centralized baseline. These findings confirm the feasibility of deploying notarization services on constrained edge infrastructure under the new fee-based model.
The emergence and expansion of the Internet of Things (IoT) have created an increasing need for distributed, secure, and scalable consensus protocols that can validate transactions in such volatile and resource-limited environments. DAG-based ledger systems, in combination with Fast Probabilistic Consensus (FPC) offer high throughput with minimal communication cost for conflict resolution. However, traditional FPC does not have any logical means of assigning weight to different validators in an adversarial setting. In this context, this article attempts to present a hybrid Proof-of-Stake and Fast Probabilistic Consensus (PoS-FPC) protocol for DAG-based IoT systems. The proposed framework consists of transaction attachments on a DAG graph, Ed25519 signatures, BLAKE2b-256 hashing, a weighted quorum for non-conflicting transactions, and a stake-weighted FPC algorithm for the resolution of conflicting transactions. The weight of validators in the proposed framework is computed based on an adaptive weighting scheme that uses the normalized weight of stake and mana, dynamically tunes their weights depending on network traffic, and implements reward and penalty mechanisms to ensure honest participation and prevent malicious attacks. The proposed framework was tested by conducting discrete event simulations of 20,000 transactions in different adversarial situations. The experimental evaluation yielded a throughput of 5,128 transactions per second, a decision accuracy of 99.6%, adversary resistance of 97.81%, a quorum latency of 69.782 ms, FPC conflict latency of 690 ms and average convergence time of 3.73 rounds of the FPC algorithm. When compared to a mana-based DAG-FPC framework that was evaluated under the same simulation setup, the proposed framework outperforms it in terms of decision accuracy, conflict latency, faster convergence, and robustness to adversarial participation of up to 40%.
Consensus algorithms form the core of distributed systems, enabling multiple nodes to agree on a single, consistent state even in the presence of failures, delays, or malicious actors. This chapter provides an in-depth examination of the principles, mechanisms, and practical applications of consensus in decentralized networks. Foundational models such as crash-fault tolerance (CFT) and Byzantine-fault tolerance (BFT) are introduced to explain system reliability under different failure assumptions. Major consensus algorithms, including Proof of Work (PoW), Proof of Stake (PoS), Practical Byzantine Fault Tolerance (PBFT), Raft, and Paxos, are analyzed with respect to their design logic, operational characteristics, security assumptions, and performance trade-offs. The chapter also explores emerging consensus innovations aimed at improving scalability, energy efficiency, and decentralization. By connecting theoretical foundations with real-world implementations, this work provides readers with a comprehensive understanding of how consensus algorithms maintain trust, integrity, and robustness within blockchain platforms, distributed databases, and large-scale multi-agent systems.
Consensus algorithms are the foundational mechanisms that enable blockchain networks to operate securely, transparently, and without centralized control. This chapter explores the deep interconnection between consensus mechanisms and blockchain architecture, highlighting how decentralized agreement is achieved across distributed nodes. Core concepts such as trustless coordination, ledger immutability, and fault tolerance are introduced to illustrate why consensus is critical for blockchain reliability. Major consensus models, including Proof of Work (PoW), Proof of Stake (PoS), Delegated Proof of Stake (DPoS), and Byzantine Fault Tolerant (BFT) protocols, are analyzed in terms of performance, security assumptions, energy consumption, and scalability. Real-world applications and blockchain platforms are examined to demonstrate how different consensus choices influence system behavior and design trade-offs. The chapter also discusses emerging innovations in hybrid, energy-efficient, and scalable consensus systems. By linking theory with practical implementation, this chapter provides a clear understanding of how consensus algorithms ensure integrity and trust within blockchain ecosystems.
Multi-Swarm Agency Protocol: Emergent Coordination in Heterogeneous Agent Networks Through φ-Resonant Synchronization and Distributed Consensus Mechanisms We present the Multi-Swarm Agency Protocol (MSAP), a comprehensive formal framework for coordinating heterogeneous autonomous agent swarms without centralized control, external orchestration, or pre-negotiated cooperation agreements. MSAP enables N independent swarms, each with distinct objectives, internal governance structures, resource constraints, and temporal dynamics, to achieve coherent collective behavior through a novel mechanism we term φ-resonant synchronization. This synchronization leverages the mathematical properties of the golden ratio φ = 1.618033988749895 to achieve optimal coupling strengths that balance coordination benefits against autonomy costs. We prove that under MSAP, swarm coordination converges in O(log N) synchronization rounds with probability 1 − ε for any ε > 0, provided the inter-swarm coupling matrix satisfies the spectral condition λ₂(K) > φ⁻¹. We further establish that this convergence is optimal—no protocol can achieve coordination in fewer than Ω(log N) rounds under our adversarial message delay model. The protocol is fault-tolerant, maintaining coordination properties even when up to f < N/φ² swarms experience Byzantine failures. Our theoretical contributions include: (1) a complete characterization of the swarm synchronization manifold as a φ-weighted torus, (2) proof that emergent coordination behaviors satisfy a novel compositionality theorem enabling hierarchical swarm-of-swarms architectures, (3) informationtheoretic lower bounds showing our protocol is communication-optimal within constant factors, and (4) extension of classical Kuramoto dynamics to heterogeneous multi-objective settings with rigorous stability analysis. Empirical validation across 47 production deployments spanning six industries (aviation, finance, healthcare, manufacturing, logistics, smart cities) demonstrates 94.7% coordination success rate (σ = 2.3%), mean coordination latency of 127ms (σ = 34ms), and mean rounds-tosynchronization of 4.2 (σ = 1.1). Our largest deployment coordinates 12 swarms comprising 2,847 agents with sustained throughput of 45,000 coordinated actions per second. Comparative evaluation against seven baseline coordination protocols shows MSAP achieves 2.3× higher coordination success, 4.1× lower latency, and 6.7× better scalability. The MSAP reference implementation is open-source (Apache 2.0 license), with formal verification in Coq ensuring correctness of core synchronization invariants. We discuss implications for the emerging field of multi-swarm robotics, autonomous vehicle coordination, and distributed AI governance. **Keywords:** Multi-agent systems, swarm intelligence, distributed coordination, emergent behavior, φ-synchronization, Kuramoto oscillators, Byzantine fault tolerance, heterogeneous agents, protocol verification, autonomous systems, collective intelligence, decentralized control, golden ratio mathematics **ACM Classification:** I.2.11 Distributed Artificial Intelligence—Multiagent systems; C.2.4 Distributed Systems—Distributed applications; G.1.6 Optimization—Global optimization --- ## 1. Introduction ### 1.1 The Multi-Swarm Challenge Modern enterprise systems increasingly deploy multiple autonomous agent swarms, each optimized for specific domains: supply chain optimization, customer service automation, financial analysis, security monitoring, predictive maintenance, and resource allocation. These swarms must coordinate without: 1. **Central orchestration** — no single point of failure or control 2. **Pre-defined protocols** — agents and swarms may be unknown at design time 3. **Shared objectives** — swarms optimize different, potentially conflicting fitness functions 4. **Global visibility** — each swarm has only local information 5. **Synchronous execution** — communication delays are arbitrary and unpredictable Traditional multi-agent coordination assumes homogeneous agents with aligned goals operating in synchronous rounds with reliable communication. Real-world deployment shatters these assumptions. A supply chain swarm optimizing for just-in-time delivery may conflict with a sustainability swarm minimizing carbon footprint. A security swarm restricting access may impede a customer service swarm maximizing responsiveness. These conflicts cannot be resolved by a central authority—they must emerge from distributed negotiation. ### 1.2 Motivating Applications Distributed Financial Trading A quantitative trading firm operates: - **Alpha generation swarm**: Signal discovery, factor modeling - **Execution swarm**: Order routing, market making, latency arbitrage - **Risk management swarm**: Position limits, VaR monitoring, stress testing - **Compliance swarm**: Regulatory reporting, trade surveillance Alpha wants to maximize returns. Execution wants to minimize slippage. Risk wants to limit exposure. Compliance wants to ensure auditability. These objectives are inherently in tension. MSAP enables these swarms to coordinate in real-time (sub-millisecond) while preserving their distinct mandates. Smart City Infrastructure A metropolitan area coordinates: - **Traffic management swarm**: Signal timing, congestion routing - **Emergency response swarm**: Dispatch, route clearing, hospital coordination - **Energy grid swarm**: Load balancing, renewable integration, demand response - **Public transit swarm**: Schedule optimization, crowd management An emergency affects traffic routing, which affects bus schedules, which affects commuter energy demand. MSAP enables these swarms to coordinate at city scale (millions of agents) with second-level latency. Technical Challenges Multi-swarm coordination presents several fundamental challenges: **Challenge 1: Heterogeneous Objectives** Swarms optimize different fitness functions G₁, G₂, ..., Gₙ. Coordination must not require swarms to abandon their objectives; rather, it must find operating points where swarms can achieve reasonable satisfaction while enabling collective behavior. **Challenge 2: Dynamic Membership** Swarms join and leave the coordination network. New swarm types emerge. The protocol cannot assume fixed membership or pre-shared knowledge of swarm capabilities. **Challenge 3: Adversarial Environment** Some swarms may be compromised, behave selfishly, or actively attempt to disrupt coordination. The protocol must be robust to Byzantine behavior. **Challenge 4: Scale** Real deployments involve thousands of swarms with millions of agents. The coordination overhead must scale sub-linearly with swarm count. **Challenge 5: Latency** Many applications require sub-second coordination. The protocol must minimize synchronization rounds. ### 1.4 Our Approach: φ-Resonant Synchronization MSAP addresses these challenges through a novel coordination mechanism inspired by coupled oscillator dynamics. Each swarm maintains a "coordination phase" θ ∈ [0, 2π) representing its current position in a coordination cycle. Swarms influence each other's phases through φweighted coupling, where the golden ratio φ = 1.618033988749895 appears naturally from optimality conditions . The key insights are: 1. **Phase representation abstracts objectives**: A swarm's phase encodes its current coordination state without revealing internal structure or fitness function. 2. **Kuramoto-like dynamics ensure convergence**: Modified Kuramoto oscillator dynamics guarantee that coupled swarms synchronize their phases. 3. **φ-weighting optimizes coupling**: The golden ratio weighting balances coordination strength against autonomy preservation, emerging from variational principles. 4. **Hierarchical composition**: Synchronized swarms can themselves be treated as agents in a meta-swarm, enabling recursive coordination. ### 1.5 Contributions This paper presents: 1. **MSAP Framework** — A complete formal protocol for multi-swarm coordination, including message formats, state machines, and invariants (Section 3). 2. **φ-Resonance Theory** — Mathematical foundation for emergent synchronization, proving optimality of golden ratio coupling (Section 2). 3. **Convergence Proofs** — Rigorous analysis showing O(log N) coordination with high probability, with matching lower bounds 4. **Fault Tolerance** — Extension to Byzantine settings with f < N/φ² fault threshold (Section 5). 5. **Production Validation** — Comprehensive evaluation across 47 deployments in 6 industries (Section 7). 6. **Formal Verification** — Coq proofs of core protocol invariants (Appendix B). 7. **Reference Implementation** — Open-source implementation with performance benchmarks (Section 6). ### 1.6 Paper Organization Section 2 develops the mathematical foundation. Section 3 specifies the MSAP protocol. Section 4 analyzes convergence and complexity. Section 5 addresses fault tolerance. Section 6 describes implementation. Section 7 presents empirical evaluation. Section 8 surveys related work. Section 9 concludes with future directions. Appendices provide complete proofs, algorithms, and verification artifacts. --- ## 2. Mathematical Foundation ### 2.1 Notation and Preliminaries Throughout this paper, we use the following notation: | Symbol | Meaning | |--------|---------| | φ | Golden ratio, φ = (1 + √5)/2 ≈ 1.618033988749895 | | φ⁻¹ | Reciprocal, φ⁻¹ = φ − 1 ≈ 0.618033988749895 | | N | Number of swarms | | n | Total number of agents across all swarms | | S, Sᵢ | Swarm, i-th swarm | | A, aⱼ | Agent, j-th agent | | Θ, Θᵢ | Phase angle, phase of swarm i | | R, Rᵢ | Order parameter (coherence), coherence of swarm i | | K, Kᵢⱼ | Coupling matrix, coupling between swarms i and j | | G, Gᵢ | Fitness function, fitness of swarm i | | ω, ωᵢ | Natural frequency, frequency of swarm i | | λₖ(M) | k-th eigenvalue of matrix M | | ‖·‖ | Euclidean norm | | ⟨·,·⟩ | Inner product | | ℙ[
The Adaptive Neural Gossip Protocol (ANGP) is a fully decentralized, asynchronous consensus mechanism designed for Directed Acyclic Graph (DAG) based distributed ledgers. Unlike classical Byzantine Fault Tolerant (BFT) systems that rely on leader election or quorums, ANGP uses:• Amedian-based consensus computed from predictions exchanged via gossip.• A continuous reputation engine that distinguishes honest nodes from Byzantine attackers, including coordinated collusion, rare attacks, sensor faults, and network impairments.• Alightweight Proof-of-Work (PoW) layer (SHA-512/256) to prevent Sybil identity floods, while keeping the core protocol free of staking or token-based governance.ANGP tolerates up to 44% coordinated attackers and 66% uncoordinated attackers with no degradation in honest node safety. It operates asynchronously, requires no global time synchronization, and self-heals under packet loss and network delays. This document provides the complete architectural blueprint, component specifications, security analysis, and integration guidelines for building a production-grade DAG based cryptocurrency or distributed application on top of ANGP.
Proof-of-Stake DAG-BFT consensus faces a trilemma between sybil resistance, reward fairness, and plutocracy. Existing protocols prioritize liveness over fair stake-based selection, driving longitudinal centralization. FairWave is a dual-channel DAG-BFT protocol that separates anchor selection from reward distribution. The selection channel is super-linear in stake, guaranteeing Sybil gain < 1 for K > 1; the reward channel is sub-linear via square-root stake normalization. DAG-derived uptime and latency metrics eliminate external oracles,and lagged reputation breaks circular dependency between selection outcomes and weights. Evaluated through approximately 550,000 Monte Carlo rounds against eight baselines, FairWave shows Gini 0.140 (vs. Pure-PoS 0.490, monotone HHI reduction from 0.039 to 0.020 over 50,000 epochs, and optimal Sybil split K * = 1. Safety follows unconditionally from the 2f + 1 commit rule; the liveness model predicts monotone degradation from 94.0% at b = 0.20 to 74.0% at b = 1/3, consistent with the architectural expectation of no discontinuous cliff.
We present Veil, a decentralized messaging protocol that unifies metadata protection, spam prevention, and offline message delivery through a single mechanism: Proof-of-Relay. In Veil, sending a message requires a zero-knowledge proof that the sender has faithfully relayed messages for others through a stratified mixnet. The relay work itself constitutes the anonymizing infrastructure, eliminating the need for cryptocurrency tokens, blockchain consensus, or trusted third parties. We make three contributions. First, we prove that bilateral non-transferable credits with epoch-bound nullifiers achieve incentive compatibility without a global state, a general result applicable beyond messaging to any peer-to-peer system requiring fair exchange. Second, we establish a Growth-Isolation Impossibility theorem showing that no CRDT merge function can simultaneously resist inflation and guarantee completeness for monotonically growing verifiable evidence, and present a resolution via penalty-log CRDTs with locally-computed growth. Third, we prove a constructive adversary bound: any adversary controlling a fraction f of relay nodes necessarily contributes to sender anonymity entropy, while the individual deanonymization probability remains bounded, ensuring that adversarial participation requires a productive contribution while individual targeting remains negligible. Veil requires no economic investment to participate; privacy is earned through device contribution alone. We analyze the protocol's security under a global passive adversary with formal indistinguishability definitions, bound Sybil infiltration under depth-limited social vouching, and demonstrate mobile feasibility with verified constraint counts via Nova folding over BabyJubjub.
Transaction ordering attacks extract billions of dollars annually from decentralized finance users in the form of Maximal Extractable Value (MEV). Byzantine Fault-Tolerant (BFT) consensus protocols guarantee total order but place no constraint on how that order is chosen, leaving the door open for adversarial reordering. Batch-order-fairness (batch-OF) protocols close this gap, but existing designs pay a steep performance price for this guarantee. Leader-based protocols such as Themis concentrate all fairness decisions at a single replica, while recent DAG-based proposals FairDAG and DAG of DAGs (DoD) force their fairness layer into strictly serial execution despite running on multi-proposer DAGs. We present Herring, the first $γ$-batch-OF DAG BFT protocol whose fairness layer parallelizes the dominant graph construction cost across committed subdags. Herring combines post-consensus graph construction with explicit missing edge resolution piggybacked on the DAG's reliable broadcast layer, a pairing that turns fair ordering from a per-round serial bottleneck into a CPU-bound task. We also uncover previously unreported liveness vulnerabilities in both FairDAG-RL and DoD that a malicious client can trigger to halt the fairness layer indefinitely, and propose patches that we integrate into our reimplementations. We implement Herring on top of the Rust implementation of Narwhal \& Tusk and evaluate it against FairDAG-RL, DoD-W, and Themis. Herring tracks the throughput of Narwhal \& Tusk closely up to roughly $10{,}000$\,tx/s, achieves roughly $90\%$ higher saturation throughput than FairDAG-RL and $100\%$ higher than DoD-W, and substantially reduces execution latency at saturation.
The rapid expansion of Artificial Intelligence Data Centers (AIDC) faces severe physical constraints, notably the linear O(n) scaling of power consumption, cooling requirements, and latency. In this paper, we propose the Lattice Swarm Protocol, a paradigm shift in distributed edge computing utilizing an O(1) constant memory architecture combined with the Virtual-to-Materialization (V2M) engine. We mathematically demonstrate that when interconnected via high-speed 400G/800G optical networks, multiple 1MW ultra-low-power edge nodes do not compute independently. Instead, they share Spatiotemporal Environmental Hashes across a 9192-D Lattice network. This mechanism exponentially reduces the computational load of the entire network as node count increases, creating a single 300MW-equivalent "Hyper-Organism" from merely 30 distributed 1MW nodes. We empirically validate this architecture through the implementation of zero-latency Stateless Custody protocols and interstellar acoustic materialization (Voyager 1), both audited by Google DeepMind Antigravity. This infrastructure establishes a new global standard for Autonomous Driving and Urban Air Mobility (UAM).Version 2 Update: Integrated Zero-Knowledge Proof (ZKP) mechanisms and Stateless Key Vaporization (0.024s), aligned with KIPO Patent No. 10-2026-0079266.
SPT × VLSA: Novel Contributions and Scale Proof (Sprute, 2026) This paper presents five original contributions to civilizational protocol theory organized under the SPT triad (Security · Privacy · Trust) and validates them through the ERES VLSA (Very-Large System Architecture) scale test — 91 tests, 100% pass rate, spanning seven orders of magnitude from a personal THOW (~30m²) to an interstellar generation ship. The five contributions map the ERES Institute's 6 Key Development Areas onto the internet's three-tier protocol stack (TCP/HTTPS/WEB3), addressing gaps no existing standard resolves. Under Security: the Energy–Security Dependency identifies every TLS session's security as bounded by its energy supply's sustainability, resolved through SECUIR circular energy; Emergency Retransmission establishes architectural identity between peacetime and crisis delivery via GunnySack Storm Party. Under Privacy: State-Aware Identity introduces psycho-physiological coherence (ARI) into the authentication handshake with zero-knowledge sovereign disclosure through BERA/FAVORS. Under Trust: Semantic Authentication verifies the meaning of exchanges across CyberRAVE's 72-domain × 3-dimension × 3-codex evaluation space (648 semantic coordinates); Proof-of-Resonance introduces a third consensus class where bio-electric coherence — not computational expenditure — validates transactions through Meritcoin ("It's not mining — it's tuning"). The central finding is fractal scale invariance: FDRV at maximum scale IS the interstellar vessel, and the THOW is its test article. A worked medical exchange example demonstrates all five contributions operating simultaneously on a single transaction. Companion to ERES Institute: Complete Architecture (Sprute, 2026). Published under CCAL v2.1.
The Bitcoin protocol [Nakamoto, 2008] represents a landmark achievement in distributed systems and cryptographic engineering. However, its fixed-supply design embeds a critical long-term vulnerability: the mathematical inevitability of permanent supply contraction driven by generational private-key inheritance failure. This paper formalises the generational loss model through discrete probability theory and recurrence relations, demonstrating that conservative estimates predict 51% of total supply becoming permanently inaccessible within 264 years, while realistic models project 64% loss. We further establish that the cessation of block rewards at approximately block height 6,930,000 ($\approx$2140 CE) eliminates the mining security budget, exposing the network to sustained 51% attack risk. We propose Bitcoin Infinity — the Perpetual Continuity Protocol — a minimal, mathematically grounded modification to Bitcoin Core's GetBlockSubsidy() function. The modification replaces a single hard-stop conditional with a modulo operation, restarting the original 50 BTC/block halving curve every 33 halvings ($\approx$132 years) in perpetuity. We prove that under this scheme, circulating supply converges to a stable equilibrium $C^* = S_0r/(1 - r)$ (approximately 49 M BTC at 30% generational loss), mining incentives are preserved indefinitely, and all previously issued bitcoins remain fully valid. The implementation is verified against 113 boundary tests with zero failures, exhibits no undefined behaviour under C++17, and maintains complete backward compatibility with the existing network until the activation block. Link: https://revistazen10.github.io/bitcoin-infinity/
Vehicular ad-hoc networks (VANETs) are networks based on short-range wireless communication technology, mainly used for direct communication between vehicles and interaction with roadside infrastructures. The emergence of VANETs has improved the efficiency and safety of vehicle travel. However, malicious vehicles may intentionally send incorrect messages to mislead other vehicles for personal gain, and this behavior cannot be identified yet. To address this issue, we propose an efficient, identifiable, and abortable multi-party signature scheme for VANETs. Specifically, we utilize the property of zero-knowledge proofs to design a method that can efficiently identify malicious vehicles during the signature process, and define a strategy to quickly locate false proofs. Additionally, the message signing key in the proposed scheme is jointly generated by multiple entities, which avoids the security issues of key escrow and single point failure. Through rigorous security analysis, it is demonstrated that the proposed scheme satisfies essential security requirements for VANETs, including message unforgeability and authentication, vehicle anonymity, malicious traceability, collusion resistance, replay attack resistance, identifiable abort, and forward security of signing private key. Performance analysis shows that our scheme reduces the total aggregation verification time by up to 80% compared to existing schemes, and maintains a lower packet loss rate ($< $0.6%) at higher vehicle densities. Therefore, our scheme is suitable for large-scale VANETs deployments.
This paper proposes the Physical Law-Based Security System (PLBSS), a novel distributed ledger paradigm that anchors digital records to irreversible astrophysical events rather than computational assumptions. By deriving absolute timestamps from the past light cones of phenomena such as supernovae or gravitational waves, PLBSS achieves physically irreversible, non-consensus-based data integrity. The system combines probabilistic event anchoring and quantum-based node verification, rendering retroactive tampering physically impossible under known laws of nature.
본 논문은 장애, 공격, 검열, 네트워크 분할과 같은 "중단 사건" 이후 분산 원장 및 합의 시스템이 어떻게 재수렴하는지 분석하기 위한 개념적 프레임워크로 흐름 복원력(Flow-Resilience )을 제안합니다 . "칼로 물을 베어도 물은 계속 흐른다"는 고전 속담에 기반하여, 본 논문은 속담과 프로토콜 간의 매핑 템플릿과 흐름→축소→분할→재흐름 단계 모델을 제시하고, 나카모토식 합의, 팍소스 계열 합의, BFT 복제 방식 간의 재수렴 경로를 비교합니다. 단, 구현상의 민감한 세부 정보는 공개하지 않습니다. License and Usage Notice Proprietary — All Rights Reserved This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0). To view a copy of this license, visit: http://creativecommons.org/licenses/by-nc-nd/4.0/ Key Constraints: Attribution: You must give appropriate credit to the author (Jeongchoon Lee). Non-Commercial: You may not use this material for commercial purposes (including corporate-funded research or patent filings by third parties). NoDerivatives (No-Derivs): If you remix, transform, or build upon the material, you may not distribute the modified material. The production of derivative works—including academic papers that hybridize this theory with other frameworks—is strictly prohibited without the express written consent of the author.
Permissionless consensus protocols require a scarce resource to regulate leader election and provide Sybil resistance. Existing paradigms such as Proof of Work and Proof of Stake instantiate this scarcity through parallelizable resources like computation or capital. Once acquired, these resources can be subdivided across many identities at negligible marginal cost, making linear Sybil cost fundamentally unattainable. We introduce Proof of Commitment (PoCmt), a consensus primitive grounded in a non-parallelizable resource: real-time human engagement. Validators maintain a commitment state capturing cumulative human effort, protocol participation, and online availability. Engagement is enforced through a Human Challenge Oracle that issues identity-bound, time-sensitive challenges, limiting the number of challenges solvable within each human window. Under this model, sustaining multiple active identities requires proportional human-time effort. We establish a cost-theoretic separation showing that protocols based on parallelizable resources admit zero marginal Sybil cost, whereas PoCmt enforces a strictly linear cost profile. Using a weighted-backbone analysis, we show that PoCmt achieves safety, liveness, and commitment-proportional fairness under partial synchrony. Simulations complement the analysis by isolating human-time capacity as the sole adversarial bottleneck and validating the predicted commitment drift and fairness properties. These results position PoCmt as a new point in the consensus design space, grounding permissionless security in sustained human effort rather than computation or capital.
Ali Farahbakhsh, Giuliano Losa, Youer Pu, Lorenzo Alvisi · 5 authors
Permissionless blockchains achieve consensus while allowing unknown nodes to join and leave the system at any time. They typically come in two flavors: proof of work (PoW) and proof of stake (PoS), and both are vulnerable to attacks. PoS protocols suffer from long-range attacks, wherein attackers alter execution history at little cost, and PoW protocols are vulnerable to attackers with enough computational power to subvert execution history. PoS protocols respond by relying on external mechanisms like social consensus; PoW protocols either fall back to probabilistic guarantees, or are slow. We present Sieve-MMR, the first fully-permissionless protocol with deterministic security and constant expected latency that does not rely on external mechanisms. We obtain Sieve-MMR by porting a PoS protocol (MMR) to the PoW setting. From MMR we inherit constant expected latency and deterministic security, and proof-of-work gives us resilience against long-range attacks. The main challenge to porting MMR to the PoW setting is what we call time-travel attacks, where attackers use PoWs generated in the distant past to increase their perceived PoW power in the present. We respond by proposing Sieve, a novel algorithm that implements a new broadcast primitive we dub time-travel-resilient broadcast (TTRB). Sieve relies on a black-box, deterministic PoW primitive to implement TTRB, which we use as the messaging layer for MMR.
Vehicular Ad Hoc Networks (VANETs) are emerging as a cornerstone of intelligent transportation systems, enabling efficient data exchange between vehicles and roadside infrastructure. However, ensuring secure and trustworthy routing remains a major challenge due to high node mobility, intermittent connectivity, and malicious node behavior. This research proposes a Blockchain-Assisted Trust-Driven Secure Routing Protocol (BTDSRP) to enhance communication reliability, data integrity, and routing efficiency in VANETs. The proposed BTDSRP integrates blockchain technology with a hybrid trust evaluation model to ensure transparent and tamper-proof routing decisions. Each vehicle maintains both direct trusts, derived from historical packet forwarding behavior, and indirect trust, computed from neighboring recommendations. These trust values are recorded in a lightweight blockchain maintained through a Delegated Proof of Stake-Byzantine Fault Tolerant consensus mechanism, ensuring decentralized verification with minimal latency. Routing decisions are optimized using a Multi-Objective Optimization Function that jointly considers trust, link stability, delay, and residual energy to identify the most reliable path for data forwarding. A Trust Update Algorithm dynamically adjusts node reputation based on deviation from expected behavior, thereby isolating malicious nodes in real time. Extensive simulations using NS-3 and SUMO demonstrate that BTDSRP achieves superior performance compared to the conventional protocols such as AODV, DSR, and TRUSTAODV, yielding improvements of up to 18.7% in packet delivery ratio, 23.4% reduction in end-to-end delay, and 15.2% decrease in routing overhead. The results confirm that integrating blockchain with trust-based routing significantly enhances the security, transparency, and efficiency of vehicular communication networks, providing a robust foundation for next-generation 5G/6G-enabled intelligent transportation systems.
1. Assistant Professor., Dr. Avinash Gudimetla, Katta Kameswara Rao, Pudi Eswar Prasanth · 7 authors
Swarm Intelligence and the Internet of Things (IoT)are rapidly evolving fields that intersect to create innovative solutions. This abstract explores how swarm intelligence, inspired by collective behavior in natural systems, can be applied to enhance the efficiency, scalability, and adaptability of IoT networks.It discusses key concepts such as decentralized decision making,self organization, and emergent intelligence withinIoT environments. The abstract also highlights practical applications, benefits, and challenges of integrating swarm intelligence algorithms with IoT technologies, paving the way for advanced autonomous systems and intelligent networks in diverse domains.
We present Areon, a family of latency-friendly, stake-weighted, multi-proposer proof-of-stake consensus protocols. By allowing multiple proposers per slot and organizing blocks into a directed acyclic graph (DAG), Areon achieves robustness under partial synchrony. Blocks reference each other within a sliding window, forming maximal antichains that represent parallel ``votes'' on history. Conflicting subDAGs are resolved by a closest common ancestor (CCA)-local, window-filtered fork choice that compares the weight of each subDAG -- the number of recent short references -- and prefers the heavier one. Combined with a structural invariant we call Tip-Boundedness (TB), this yields a bounded-width frontier and allows honest work to aggregate quickly. We formalize an idealized protocol (Areon-Ideal) that abstracts away network delay and reference bounds, and a practical protocol (Areon-Base) that adds VRF-based eligibility, bounded short and long references, and application-level validity and conflict checks at the block level. On top of DAG analogues of the classical common-prefix, chain-growth, and chain-quality properties, we prove a backbone-style $(k,\varepsilon)$-finality theorem that calibrates confirmation depth as a function of the window length and target tail probability. We focus on consensus at the level of blocks; extending the framework to richer transaction selection, sampling, and redundancy policies is left to future work. Finally, we build a discrete-event simulator and compare Areon-Base against a chain-based baseline (Ouroboros Praos) under matched block-arrival rates. Across a wide range of adversarial stakes and network delays, Areon-Base achieves bounded-latency finality with consistently lower reorganization frequency and depth.