The transition from static articles to a living Scientific Knowledge Graph, as proposed in our previous work, promises to accelerate discovery and restore feedback loops in science. However, a fully open, semantically linked graph of all scientific knowledge also presents an unprecedented dual-use risk: it could become a roadmap for malicious actors to identify and exploit hidden vulnerabilities. This paper addresses that paradox by introducing a comprehensive framework for "Ethical Immunity" β a set of proactive, architecture-level mechanisms designed to make the Knowledge Graph resilient to misuse without resorting to censorship or secrecy. We detail a three-pillar system: (1) AI-powered Red and Blue Teams that continuously simulate misuse scenarios and generate countermeasures; (2) Decentralized Autonomous Organizations (DAOs) for transparent, expert-driven oversight and risk assessment; and (3) "Ethical Quarantine" protocols that allow for the temporary isolation of high-risk knowledge while ensuring the parallel development of defenses. We argue that such a framework transforms the Knowledge Graph from a passive repository into an active immune system for civilization, capable of identifying and neutralizing threats at the speed of discovery. This paper provides a technical and organizational blueprint for building safety into the very fabric of 21st-century science.
KRILL β Bio-Inspired Architecture for IoT Consensus Decentralized IoT consensus without blockchain β inspired by ant colonies, immune systems & chemical diffusion. What is KRILL? The problem: Blockchain doesn't work for IoT. It's too heavy, too slow, and too expensive for devices running on batteries with 32KB of RAM. IoT needs to answer "What is the physical state of the world?" β not "Who has how much money?" The solution: KRILL replaces blockchain with 9 mechanisms borrowed from biology: Mechanism Biological inspiration What it does Stigmergic Consensus Ant pheromone trails Nodes "deposit" readings like ants deposit pheromones. Truth emerges from convergence, not voting. Pentastratic Immune System Human immune layers 5-layer anomaly detection: skin (format check) β innate (statistical) β adaptive (learned) β NK audit β autoimmune suppression. Metabolic State Cell metabolism Data has a "half-life" β old readings decay and die automatically. No infinite ledger. Entropic Data Valuation Thermodynamic entropy Network autonomously decides which data is worth storing based on information theory. Quorum Sensing Bacterial quorum sensing Nodes detect local density and switch modes (solo β quorum β swarm) without any coordinator. Horizontal Gene Transfer Bacterial gene sharing Firmware updates spread node-to-node like genes between bacteria. No update server needed. Morphogenetic Topology Embryonic development Network self-organizes its topology using reaction-diffusion (Turing patterns). Thymic Tolerance T-cell training in thymus System learns what "normal" looks like to avoid false alarms. Immunological Memory Vaccine/antibody memory Once the network detects an attack pattern, it "vaccinates" all nodes. The result: 1000x less energy than blockchain consensus Runs on a $2 ESP32 microcontroller (240KB RAM) Works with intermittent connectivity (mesh, BLE, LoRa, WiFi) No miners, no staking, no tokens β consensus is grounded in physical reality Scales to millions of nodes without coordinator Status: Research paper + engineering specification. No working implementation yet. Documents Document Description Research Paper (HTML) Full academic paper β mathematical formalizations, energy analysis, novelty assessment, risk analysis. 20 sections. Open in browser β Print β Save as PDF. Engineering Specification (HTML) Implementation reference β byte-level wire formats, state machines, pseudocode, test vectors, transport layers. Ready to code from. Source files (Markdown): krill-bioinspired-architecture.md β Research paper krill-bia-engineering-spec.md β Engineering spec Architecture at a Glance βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ β KRILL Node (ESP32) β ββββββββββββ¬βββββββββββ¬βββββββββββ¬βββββββββββ¬ββββββββββββββ€ β Stigmer- β Immune β Metabolicβ Quorum β Morpho- β β gic β System β State β Sensing β genetic β β Consensusβ (5-layer)β (decay) β (modes) β Topology β ββββββββββββ΄βββββββββββ΄βββββββββββ΄βββββββββββ΄ββββββββββββββ€ β Transport: BLE mesh / WiFi / LoRa β βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€ β PUF Identity + Ed25519 Enrollment β βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ MVP β Where to Start If you want to implement KRILL, start with these 4 subsystems (the rest can be added later): ES-13 β Cryptographic enrollment (PUF + Ed25519 identity) ES-12 β Transport layer (BLE mesh for local, WiFi for bridging) ES-1 β Core data types and wire formats ES-3 β Stigmergic Consensus (the core algorithm) ES-10 β Main event loop and message dispatch Target hardware: ESP32 (Nano node) + nRF52840 (Dust node, optional) Why Not Blockchain? Blockchain (e.g. Ethereum) KRILL-BIA Consensus energy ~50 Wh/tx (PoW) or ~0.01 Wh/tx (PoS) ~0.00001 Wh/tx Minimum RAM 512MB+ 32KB (Dust), 240KB (Nano) State growth Infinite (append-only) Bounded (data decays) Offline tolerance Minutes before fork Days (pheromone half-life) Hardware cost $50+ SBC $2 ESP32 Finality Probabilistic (blocks) Convergent (pheromone field) Key Innovation: Physical-World Consensus Grounding Unlike blockchain where consensus is purely computational, KRILL grounds consensus in physical reality: Sensor readings must be physically plausible (a thermometer can't jump 50C in 1 second) Nodes that are physically closer have more weight (radio signal strength = distance proxy) The laws of physics constrain what values are possible β this is a defense layer that doesn't exist in financial systems This means an attacker must not only compromise the software but also defeat physics β a fundamentally harder problem. Contributing See CONTRIBUTING.md for how to get involved. Areas where help is most needed: Rust/C firmware for ESP32 (core protocol implementation) Simulation β model pheromone convergence with 100-10,000 virtual nodes Hardware testing β BLE mesh range, LoRa timing, PUF enrollment on real chips Security review β formal verification of immune system thresholds Documentation β diagrams, tutorials, translations License This project is licensed under the MIT License. Supporting This Work If KRILL is useful to your research or organization, consider supporting further development: ETH / ERC-20 / Base / Arbitrum / Polygon: 0x0BC290355c0B16B5B247701B7BC9AB2E1e61ffa7 Funds go toward: Reference firmware for ESP32 + nRF52840 Hardware test beds (100-node BLE mesh) Independent security audits Bug bounty program for protocol vulnerabilities Code contributions are equally welcome β see CONTRIBUTING.md.
Abstract The accelerating dominance of non-human agents in digital infrastructures has created an existential imbalance between human intentionality and synthetic computation. All identity-centric and post-hoc verification paradigms have failed against advanced automation. This work introduces Proof of Being (PoB) β an ontological cryptographic primitive that binds digital agency to continuous, embodied human presence without revealing identity. Using Human Intention Semantic Proof Units (HISPU) β the fusion of physiological dynamics, semantic activity structure, and changing environmental context β we generate zero-knowledge proofs of authentic human engagement. From this substrate emerges the Vital Presence Token (VPT), a new energy-like digital asset that supplies βexistential energyβ exclusively to human-authorized agents. Ontological Digital Agents Management (ODAM) implements a biological-immune-system analogue: agents lacking fresh VPT undergo ontological death and cannot claim computational resources. The framework establishes verifiable human presence as the constitutional substrate for post-AGI digital civilization and defines the economic foundations of Web4. Keywords: proof of being, ontological cryptography, human presence verification, digital immune system, vital presence token, Web4, post-AGI governance, zero-knowledge biometrics, existential energy, digital agents management, human-in-the-loop, semantic intentionality, biological computing, HLA/MHC analogy, human sovereignty, scarcity, decentralized identity, ODAM, HISPU.
Intelligent infrastructures require control strategies that overcome the limitations of centralized management. This study critically reviews the 2015β2025 literature on the convergence between bioinspired algorithms and distributed decision-making, highlighting their capabilities in decentralization, self-organization, and resilience. Based on an analysis of numerous representative cases, it is evident that Swarm Intelligence and Differential Evolution achieve significant improvements in efficiency and notable reductions in decision latency in power and traffic networks; Artificial Immune Systems strengthen the cybersecurity of critical infrastructures. Challenges remain in scalability, explainability, and ethical governance, which we address with an agenda based on federated Digital Twins and new bioinspired consensus protocols. We conclude that bioinspired algorithms not only optimize daily operations but also enable infrastructures capable of learning and recovery, laying the foundation for more sustainable and user-centered urban services.
With the rapid development of information technologies, industrial Internet has become more open, and security issues have become more challenging. The endogenous security mechanism can achieve the autonomous immune mechanism without prior knowledge. However, endogenous security lacks a scientific and formal definition in industrial Internet. Therefore, firstly we give a formal definition of endogenous security in industrial Internet and propose a new industrial Internet endogenous security architecture with cost analysis. Secondly, the endogenous security innovation mechanism is clearly defined. Thirdly, an improved clone selection algorithm based on federated learning is proposed. Then, we analyze the threat model of the industrial Internet identity authentication scenario, and propose cross-domain authentication mechanism based on endogenous key and zero-knowledge proof. We conduct identity authentication experiments based on two types of blockchains and compare their experimental results. Based on the experimental analysis, Ethereum alliance blockchain can be used to provide the identity resolution services on the industrial Internet. Internet of Things Application (IOTA) public blockchain can be used for data aggregation analysis of Internet of Things (IoT) edge nodes. Finally, we propose three core challenges and solutions of endogenous security in industrial Internet and give future development directions.
The digitization of inheritable information in the genome has been called the 'algorithmic take-over of biology'. The McClintock discovery that viral software based transposable elements that conduct cut-paste (transposon) and copy-paste (retrotransposon) operations are needed for genomic evolvability underscores the truism that only software can change software and also that viral hacking by internal and external bio-malware is the Achilles heel of genomic digital systems. There was a paradigm shift in genomic information processing with the Adaptive Immune System (AIS) 500 mya followed by the Mirror Neuron System (MNS), latterly mostly in primate brains, which reaches its apogee in human social cognition. The AIS and MNS involve distinctive GΓΆdelian features of self-reference (Self-Ref) and offline virtual self-representation (Self-Rep) for complex self-other interaction with prodigious open-ended capacity for anticipative malware detection and novelty production within a unique blockchain distributed ledger (BCDL). The role of self-referential information processing, often considered to be central to the sentient self with origins in the immune system 'Thymic self', is shown to be part of the GΓΆdel logic behind a generator-selector framework at a molecular level, which exerts stringent selection criteria to maintain genomic BCDL. The latter manifests digital and decentralized record keeping where no internal or external bio-malware can compromise the immutability of the life's building blocks and no novel blocks can be added that is not consistent with extant blocks. This is demonstrated with regard to somatic hypermutation with novel anti-body production in the face of external non-self antigen attacks.
Abstract The paper deals with the architecture and design of the complex distributed classifier for the intelligent video surveillance systems considering the contemporary tendency to detect the abnormal or suspicious behavior of the individuals by means of behavioral features set analysis. This paper focuses on the implementation of multiagent systems concept and the distributed ledger technology to the distributed message board architecture. Two selected approaches to the distributed ledger implementation are analyzed and estimated in terms of classifiers cooperation. Some simulation results are provided and discussed in terms of time consumption.
U radu je opisana, implementirana i ispitana metoda authentikacije temeljena na neinteraktivnim dokazima bez poznavanja. Takva metoda omoguΔuje primatelju da authenticira poΕ‘iljatelja i izraΔuna dijeljeni kljuΔ. NaΔin razmjene odnosno raΔunanja zajedniΔkog kljuΔa inspiriran je Diffie-Hellman protokolom. Metoda je implementirana u C++ programskom jeziku te ispitana na prijenosnom raΔunalu i Raspberry Pi-u. Ispitana je i usporeΔena brzina authentikacije. U odnosu na srodne authentikacijske sheme, postignute su usporedive brzine uz usporedivu razinu sigurnosti.
Multi-agents systems communication is a technology, which provides a way for multiple interacting intelligent agents to communicate with each other and with environment. Multiple-agent systems are used to solve problems that are difficult for solving by individual agent. Multiple-agent communication technologies can be used for management and organization of computing fog and act as a global, distributed operating system. In present publication we suggest technology, which combines decentralized P2P BOINC general-purpose computing tasks distribution, multiple-agents communication protocol and smart-contract based rewards, powered by Ethereum blockchain. Such system can be used as distributed P2P computing power market, protected from any central authority. Such decentralized market can further be updated to system, which learns the most efficient way for software-hardware combinations usage and optimization. Once system learns to optimize software-hardware efficiency it can be updated to general-purpose distributed intelligence, which acts as combination of single-purpose AI.
Patrick M. Monamo, Vukosi Marivate, Bhekisipho Twala
In the Bitcoin network, lack of class labels tend to cause obscurities in anomalous financial behaviour interpretation. To understand fraud in the latest development of the financial sector, a multifaceted approach is proposed. In this paper, Bitcoin fraud is described from both global and local perspectives using trimmed k-means and kd-trees. The two spheres are investigated further through random forests, maximum likelihood-based and boosted binary regression models. Although both angles show good performance, global outlier perspective outperforms the local viewpoint with exception of random forest that exhibits nearby perfect results from both dimensions. This signifies that features extracted for this study describe the network fairly.
Zeev Dvir, Dan Gutfreund, Guy N. Rothblum, Salil Vadhan
Abstract: We investigate the complexity of the following computational problem: Polynomial Entropy Approximation (PEA): Given a low-degree polynomial mapping p: Fn β Fm, where F is a finite field, approximate the output entropy H(p(Un)), where Un is the uniform distribution on Fn and H may be any of several entropy measures. We show: β’ Approximating the Shannon entropy of degree 3 polynomials p: Fn 2 β Fm 2 over F2 to within an additive constant (or even n.9) is complete for SZKPL, the class of problems having statistical zero-knowledge proofs where the honest verifier and its simulator are computable in logarithmic space. (SZKPL contains most of the natural problems known to be in the full class SZKP.) β’ For prime fields F = F2 and homogeneous quadratic polynomials p: Fn β Fm, there is a probabilistic polynomial-time algorithm that distinguishes the case that p(Un) has entropy smaller than k from the case that p(Un) has min-entropy (or even Renyi entropy) greater than (2 + o(1))k. β’ For degree d polynomials p: Fn 2 β Fm 2, there is a polynomial-time algorithm that distinguishes the case that p(Un) has max-entropy smaller than k (where the max-entropy of a random variable is the logarithm of its support size) from the case that p(Un) has max-entropy at least (1 + o(1)) Β· kd (for fixed d and large k).
In recent years, immunization strategies have been developed for stopping epidemics in complex-network-like environments. Yet it still remains a challenge for existing strategies to deal with dynamically-evolving networks that contain community structures, though they are ubiquitous in the real world. In this paper, we examine the performances of an autonomy-oriented distributed search strategy for tackling such networks. The strategy is based on the ideas of self-organization and positive feedback from Autonomy-Oriented Computing (AOC). Our experimental results have shown that autonomous entities in this strategy can collectively find and immunize most highly-connected nodes in a dynamic, community-based network within a few steps.
Some of the salient biology is reviewed, so that it can be seen how suitable the immune system is as a prototype of "bottom up" artificial intelligence. It is stressed that the immune system is entirely distributed (to first approximation). Its agents, the cells, are highly complex. Much is known about these cells and their interaction with each other and with pathogens, and the system is of high biological and medical interest. Major questions to be addressed include the following: 1) what are the "goals" of the immune system, and how can feedback promote these goals? 2) how can spatial organization allow non-specific chemical signals to select specific immune elements that contribute effectively to system goals? 3) how and in what sense can immune system performance be improved in the absence of an overall goal? and 4) how does the immune system compare with other autonomous decentralized systems.
The basic principles of the intelligent home technology are presented and it is described how it can be modeled as a multi-agent system. Because of the complexity of the system it is argued that it should be generated by an evolutionary process and maintained according to the principles of the immune system.
The self-organizing diagnosis has been studied by applying the idea of autonomous and decentralized systems extracted from the concept of immune network. The model implements network-level recognition by connecting information from local recognition units by dynamical evaluation chain. The model has been further elaborated for engineering concerns of identifying not only sensor faults but process faults. The sensor faults will be identied by evaluating reliability of data from sensor, while the process faults will be identied by evaluating that of constraints that must be satised among these data. We have demonstrated that the extended sensor network will work against both sensor faults and process faults by an illustrative example.