[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3743":3,"related-3743":50},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":8,"published_at":11,"category":12,"cover_url":8,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":22,"tags":24,"primary_topic":8,"secondary_topics":29,"classification":30,"search_phrases":44,"slug":47,"view_count":48,"doi":8,"paper":8,"created_at":49},3743,"安徽省农科院举办网络安全专题培训会","https:\u002F\u002Fwww.aaas.org.cn\u002F4303133\u002F71238548.html","9月20日下午安徽省农科院网信办在合肥城市云数据中心股份有限公司举办网络安全专题培训会。培训采取实地观摩与专题授课相结合的方式，走进数据中心集群现场察看机房基础设施运行环境，了解集群供配电、制冷、机柜布局、网络接入等基础保障情况。",null,"为深入贯彻习近平总书记关于网络强国的重要思想，落实2026年国家网络安全宣传周工作要求，进一步强化全院网络安全意识，9月20日下午，省农科院网信办在合肥城市云数据中心股份有限公司举办网络安全专题培训会，院办公室、机关党委负责同志出席会议，院属各单位网络安全管理员、办公室主任30余人参加培训。\n\n培训采取实地观摩与专题授课相结合的方式进行，参训人员走进合肥城市云数据中心股份有限公司数据中心集群，现场察看机房基础设施运行环境，了解集群供配电、制冷、机柜布局、网络接入等基础保障情况，观摩运营中心对设备状态、网络流量、运行告警的集中监控和运维值守流程。观摩过程中，参训人员结合本单位网络设备管理、系统运行维护和数据存储实际，就日常运维中遇到的难点问题与现场技术人员深入交流。参观结束后，合肥城市云数据中心股份有限公司网络安全专家围绕网络安全法律法规、安全防范意识、典型网络安全事件及单位安全管理行为规范等内容进行专题授课，通过法规解读与勒索病毒等案例分析，帮助参训人员进一步提升网络安全意识和防护能力。\n\n参训人员表示，此次培训把课堂搬到数据中心一线，既有实地观摩的直观感受，又有专题授课的系统讲解，进一步增强了网络安全责任意识和风险防范意识。一致认为，网络安全无小事，必须把责任落实到岗、落实到人，把制度要求转化为具体行动，切实守好农业科研数据安全底线。","安徽省农业科学院","2026-09-20T12:00:00Z","报道",10,false,43,{"impact":17,"substance":13,"depth":17,"authority":18,"freshness":19,"relevant":20,"comment":21},8,11,6,1,"省级农科院网络安全培训，属内部安全意识教育，与农业信息化关联较弱，信息增量有限，不建议进入每日精选。",[23],{"name":10,"url":6},[25,26,27,28],"安徽省农科院","网络安全","数据安全","农业科研数据",[],{"status":31,"locked":14,"version":32,"method":33,"evidence":34},"unclassified","2026-10-22.2","rules",{"candidates":35,"agricultural_evidence":42,"reason":43},[36],{"code":37,"score":38,"supported":14,"title":39,"abstract":40,"tags":41},"I6",2,[],[],[27,26],true,"缺少足够的主题证据",[45,46],"安徽省农科院 网络安全 培训","合肥城市云数据中心 网络安全","安徽省农科院网络安全培训-3743",4,"2026-09-29T00:08:25.050236Z",{"total":19,"page":20,"page_size":19,"items":51},[52,121,181,275,342,411],{"id":53,"title":54,"url":55,"summary":56,"summary_zh":57,"content":8,"source_name":58,"source_url":55,"published_at":59,"category":60,"cover_url":8,"hotness":61,"is_selected":14,"score":62,"score_detail":63,"sources":65,"tags":69,"primary_topic":73,"secondary_topics":79,"classification":80,"search_phrases":103,"slug":106,"view_count":62,"doi":107,"paper":108,"created_at":120},5555,"IoT Security Challenges and Solutions: Threats, Standards and Layered Protection","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23542095","The Internet of Things (IoT) has become an important part of modern life. Smart homes, wearable devices, healthcare systems, industrial machines, and smart agriculture use connected devices to collect and exchange information. Although IoT makes many activities easier, it also introduces security and privacy risks. Weak passwords, insecure communication, outdated firmware, unauthorized access, and data leakage can expose devices and users to cyberattacks. This paper examines major security challenges faced by IoT systems and discusses practical solutions based on established cybersecurity guidance. It synthesizes three complementary perspectives: academic survey research on IoT security, the National Institute of Standards and Technology (NIST) IoT security baseline, and the OWASP Internet of Things security guidance. The study explains common threats, reviews relevant standards, and proposes a layered protection model covering devices, networks, applications, data, and system management. It concludes that IoT security should be considered throughout the device lifecycle rather than added only after a problem occurs","物联网（IoT）已成为现代生活的重要组成部分。智能家居、可穿戴设备、医疗保健系统、工业机械和智慧农业均利用互联设备采集和交换信息。尽管物联网使许多活动更加便捷，但也带来了安全与隐私风险。弱密码、不安全的通信、过时的固件、未经授权的访问以及数据泄露，都可能使设备和用户暴露于网络攻击之中。本文考察了物联网系统面临的主要安全挑战，并基于既有的网络安全指南讨论了切实可行的解决方案。研究综合了三个互补视角：关于物联网安全的学术调查研究、美国国家标准与技术研究院（NIST）物联网安全基线，以及OWASP物联网安全指南。本研究阐释了常见威胁，梳理了相关标准，并提出了一种涵盖设备、网络、应用、数据和系统管理的分层防护模型。研究结论认为，物联网安全应在设备全生命周期中加以考虑，而非仅在问题出现后才予以补加。","Zenodo (CERN European Organization for Nuclear Research)","2026-10-21T00:00:00Z","论文",25,0,{"impact":62,"substance":62,"depth":62,"authority":62,"freshness":62,"relevant":62,"comment":64},"通用物联网安全综述，仅泛泛提及智慧农业，与三农及农业信息化主题关联薄弱，不建议入选。",[66,67],{"name":58,"url":55},{"name":58,"url":68},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23541648",[70,26,71,72],"智慧农业","物联网安全","NIST标准",{"code":74,"slug":75,"name":76,"path":77,"parent_code":78},"I5","agricultural-iot","物联网传感与边缘计算","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-iot","I",[],{"status":81,"locked":14,"version":32,"method":33,"evidence":82},"classified",{"candidates":83,"agricultural_evidence":42},[84,92,99],{"code":74,"score":85,"supported":42,"title":86,"abstract":88,"tags":91},17,[87],"IoT",[89,90,87],"物联网","internet of things",[],{"code":93,"score":94,"supported":42,"title":95,"abstract":96,"tags":98},"I1",7,[],[70,97],"smart agriculture",[70],{"code":37,"score":20,"supported":14,"title":100,"abstract":101,"tags":102},[],[],[26],[104,105],"物联网安全 智慧农业 网络安全 NIST标准","物联网安全 智慧农业","物联网安全智慧农业网络安全NIST标准-5555","10.5281\u002Fzenodo.23542095",{"doi":107,"openalex_id":109,"authors":110,"venue":58,"cited_by_count":62,"oa_url":55,"card":113,"direction":117,"ingested_from":119},"W7223144955",[111],{"name":112,"orcid":8},"himesh suryawanshi",{"tldr":114,"method":115,"finding":116,"direction":117,"opportunity":118},"综述物联网安全挑战，结合学术与NIST、OWASP标准提出分层防护模型。","综合学术综述、NIST物联网安全基线与OWASP指南，构建分层防护模型。","物联网安全需覆盖设备全生命周期，而非事后补救。","智慧农业 \u002F 农业物联网","可将通用分层防护模型落地到农业物联网场景，研究低成本设备与田间网络的轻量安全方案。","openalex","2026-10-22T11:20:18.423667Z",{"id":122,"title":123,"url":124,"summary":125,"summary_zh":126,"content":8,"source_name":58,"source_url":124,"published_at":127,"category":60,"cover_url":8,"hotness":13,"is_selected":14,"score":128,"score_detail":129,"sources":136,"tags":138,"primary_topic":142,"secondary_topics":146,"classification":147,"search_phrases":163,"slug":166,"view_count":62,"doi":167,"paper":168,"created_at":180},5079,"Lightweight Blockchain Based Authentication and Secure Data Sharing in UAV Networks","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.23390977","Unmanned Aerial Vehicle (UAV) networks, oper- ating within Flying Ad-Hoc Networks (FANETs), play an in- dispensable role in contemporary surveillance, border patrol, smart agriculture, disaster recovery, and intelligent transporta- tion systems. Owing to their open wireless propagation channels, dynamic line-of-sight flight paths, and severe computational and battery resource constraints, UAVs are exceptionally susceptible to eavesdropping, message forgery, node impersonation, physical node capture, and denial-of-service (DoS) attacks. Conventional public key infrastructure (PKI) frameworks and centralized Certificate Authorities (CAs) exhibit heavy cryptographic over- head, substantial communication latency, and single-point-of- failure vulnerabilities that render them unsuitable for mission- critical aerial swarms. In this paper, we propose LBAS-UAV, a robust, lightweight, consortium blockchain-assisted mutual au- thentication, key agreement, and secure data sharing framework tailored specifically for resource-constrained UAV environments. LBAS-UAV integrates elliptic curve cryptography (ECC), physi- cal unclonable functions (PUFs), and keyed cryptographic hash functions to achieve mutual authentication without high-overhead bilinear pairings or certificate management. Dynamic UAV pseudonyms protect flight-path privacy and user untraceability. A consortium blockchain, maintained jointly by Ground Control Stations (GCS) and mobile edge servers under Practical Byzan- tine Fault Tolerance (PBFT) consensus, provides decentralized public-key validation, non-repudiation, and tamper-proof access auditing. To eliminate on-chain storage bottlenecks, high-volume aerial sensory telemetry is encrypted via AES-128-GCM and stored off-chain in the InterPlanetary File System (IPFS), while only 32-byte cryptographic content addresses and fine-grained access policies are registered on-chain. Formal security verification using the Real-Or-Random (ROR) oracle model, Burrows-Abadi- Needham (BAN) logic, and the automated AVISPA tool confirms that LBAS-UAV guarantees session key confidentiality and re- sists physical capture, replay, man-in-the-middle, and ephemeral secret leakage attacks. Extensive hardware benchmarking and network simulations demonstrate that LBAS-UAV demands only 0.318 ms of cryptographic execution time and 206 bytes of communication overhead on the UAV, outperforming recent state- of-the-art schemes by up to 38.4% in computation and 25.3% in energy efficiency.","无人机网络在飞行自组网(FANETs)中运行，在当代监视、边境巡逻、智慧农业、灾难恢复和智能交通系统中发挥着不可或缺的作用。由于其开放的无线传播信道、动态的视距飞行路径以及严重的计算和电池资源限制，无人机极易受到窃听、消息伪造、节点冒充、物理节点捕获和拒绝服务(DoS)攻击。传统的公钥基础设施(PKI)框架和集中式证书颁发机构(CAs)存在沉重的密码学开销、显著的通信延迟和单点故障漏洞，使其不适用于任务关键的空中集群。本文提出了LBAS-UAV，一种鲁棒的、轻量级的、联盟区块链辅助的相互认证、密钥协商和安全数据共享框架，专为资源受限的无人机环境量身定制。LBAS-UAV集成了椭圆曲线密码学(ECC)、物理不可克隆函数(PUFs)和带密钥的密码学哈希函数，无需高开销的双线性配对或证书管理即可实现相互认证。动态无人机假名保护飞行路径隐私和用户不可追踪性。由地面控制站(GCS)和移动边缘服务器在实用拜占庭容错(PBFT)共识下共同维护的联盟区块链，提供去中心化的公钥验证、不可否认性和防篡改的访问审计。为消除链上存储瓶颈，大容量空中传感遥测数据通过AES-128-GCM加密并存储在星际文件系统(IPFS)的链下，而仅将32字节的密码学内容地址和细粒度访问策略注册在链上。使用Real-Or-Random(ROR)预言机模型、Burrows-Abadi-Needham(BAN)逻辑和自动化AVISPA工具进行的形式化安全验证确认，LBAS-UAV保证会话密钥机密性，并能抵抗物理捕获、重放、中间人和临时秘密泄露攻击。广泛的硬件基准测试和网络仿真表明，LBAS-UAV在无人机上仅需0.318毫秒的密码学执行时间和206字节的通信开销，在计算方面优于近期最先进的方案高达38.4%，在能效方面优于25.3%。","2026-10-15T00:00:00Z",74,{"impact":130,"substance":131,"depth":132,"authority":133,"freshness":134,"relevant":20,"comment":135},12,22,18,13,9,"面向资源受限无人机网络的轻量级区块链认证与安全数据共享方案，方法新颖、验证充分，对智慧农业无人机应用有参考价值，但属通用技术论文，农业场景关联较间接。",[137],{"name":58,"url":124},[70,139,140,141,27],"无人机","农业遥感","区块链",{"code":93,"slug":143,"name":144,"path":145,"parent_code":78},"smart-agriculture","智慧农业总论","\u002Ftopic\u002Fdigital-agriculture\u002Fsmart-agriculture",[],{"status":81,"locked":14,"version":32,"method":33,"evidence":148},{"candidates":149,"agricultural_evidence":42},[150,154,159],{"code":93,"score":94,"supported":42,"title":151,"abstract":152,"tags":153},[],[70,97],[70],{"code":155,"score":20,"supported":14,"title":156,"abstract":157,"tags":158},"I3",[],[],[140],{"code":37,"score":20,"supported":14,"title":160,"abstract":161,"tags":162},[],[],[27],[164,165],"UAV 区块链 认证 数据共享","LBAS-UAV 无人机 网络安全","UAV区块链认证数据共享-5079","10.5281\u002Fzenodo.23390977",{"doi":167,"openalex_id":169,"authors":170,"venue":58,"cited_by_count":62,"oa_url":124,"card":175,"direction":117,"ingested_from":119},"W7222323013",[171,173],{"name":172,"orcid":8},"B.  Gnanasankari",{"name":174,"orcid":8},"R.  Padmanaban",{"tldr":176,"method":177,"finding":178,"direction":117,"opportunity":179},"提出轻量级联盟链认证与安全数据共享框架LBAS-UAV，用于资源受限无人机网络。","融合ECC、PUF与哈希函数，PBFT联盟链结合IPFS链下存储，AES-128","仅需0.318ms计算与206字节通信开销，计算性能提升38.4%，可抵御多种攻击。","可将该轻量认证框架迁移至农业无人机植保与农田监测场景，研究能耗与实时性权衡。","2026-10-16T23:30:08.237868Z",{"id":182,"title":183,"url":184,"summary":185,"summary_zh":186,"content":8,"source_name":187,"source_url":184,"published_at":127,"category":60,"cover_url":8,"hotness":13,"is_selected":14,"score":188,"score_detail":189,"sources":192,"tags":194,"primary_topic":198,"secondary_topics":204,"classification":206,"search_phrases":246,"slug":249,"view_count":62,"doi":250,"paper":251,"created_at":274},5077,"A Trust-Boundary Reference Architecture for Secure Cyber-Physical Agriculture: Design and Software-Based Proof-of-Concept for Smart Irrigation","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fs26206545","Smart irrigation is an operational technology (OT) problem as much as an Internet of Things (IoT) one: software decisions act directly on valves, pumps, pressure and water delivery, so a spoofed reading or a replayed command has physical consequences. This paper presents a technology-neutral reference architecture that makes those consequences controllable. It is organised into seven functional layers and three cross-cutting planes, six trust-boundary classes that fix which properties must be re-established at each crossing, and an auditable crown-asset inventory with an explicit trust-level rubric. Two governing execution principles enforce this structure: local safety authority, which keeps final actuation permission at the field gateway, remote terminal unit (RTU) or programmable logic controller (PLC), and feedback-aware execution, which treats a command as complete only when independent physical feedback confirms it. Building on process-aware and safety-supervision ideas from industrial control, the architecture makes physical confirmation a mandatory completion condition at the local enforcement point, which catches a fully authorised command that is nonetheless physically unsafe, a failure mode that authorisation checks alone cannot detect. These properties are examined through a deterministic, openly available software proof-of-concept that verifies the design against its own acceptance criteria; it is not a field validation. The software executes six attack and failure scenarios plus one nominal-operation control against an intentionally unsecured negative control and a secure controller, under identical, controlled conditions: the negative control is compromised in all 6 attack scenarios and the secure controller in 0\u002F6, with 0\u002F1 false positives on legitimate operation. Analytically, the design costs 21 bytes and 50–60% additional Long Range Wide Area Network (LoRaWAN) time-on-air per record, and 78% of single-step perturbations of the trust-scoring inputs leave asset classification unchanged: the actuator class (A2) is completely stable, and the gateway\u002FRTU\u002FPLC class (A3) is stable under 6 of 7 admissible perturbations (86%), changing only when its credential\u002Fupdate authority reaches the trust-anchor threshold. A sensor-level mapping from sampling rate, measurement drift and physical fault modes to the edge-verification controls they dictate, provisions for secure time, counter recovery and the choice between fail-closed and fail-open safe states, an illustrative hypothetical worked deployment example, and a transfer of the model to greenhouse, fertigation, livestock-watering and cold-chain settings show how the architecture could be applied in practice.","智能灌溉既是一个物联网(IoT)问题，也是一个运营技术(OT)问题：软件决策直接作用于阀门、水泵、压力和水流输送，因此被欺骗的读数或被重放的命令会产生物理后果。本文提出了一种技术中立的参考架构，使这些后果可控。该架构由七个功能层和三个横切面、六类信任边界(规定每次跨越边界时必须重新建立哪些属性)，以及一份可审计的核心资产清单(配有明确的信任等级评定标准)组成。两条主导性执行原则保障了这一结构：本地安全授权，即将最终执行许可保留在田间网关、远程终端单元(RTU)或可编程逻辑控制器(PLC)处；以及反馈感知执行，即只有当独立的物理反馈予以确认时，才将命令视为完成。该架构以工业控制中的过程感知和安全监督思想为基础，将物理确认设为本地执行点的强制性完成条件，从而能够捕获完全获得授权但在物理上仍不安全的命令——这是仅靠授权检查无法检测到的失效模式。这些特性通过一个确定性、公开可用的软件概念验证进行了检验，该验证依据其自身的验收标准对设计进行评估；这不是现场验证。该软件在相同且受控的条件下，针对一个故意不设防护的阴性对照和一个安全控制器，执行了六种攻击与故障场景以及一项标称运行对照：阴性对照在所有6种攻击场景中均被攻破，而安全控制器为0\u002F6，对合法运行的误报为0\u002F1。分析表明，该设计每条记录额外增加21字节和50–60%的LoRaWAN(LoRaWAN)空中时间，且信任评分输入的78%单步扰动不会改变资产分类：执行器类(A2)完全稳定，网关\u002FRTU\u002FPLC类(A3)在7种可允许扰动中有6种保持稳定(86%)，仅当其凭证\u002F更新权限达到信任锚阈值时才会改变。还提出了从采样率、测量漂移和物理故障模式到其所决定的边缘验证控制的传感器级映射，以及安全时间、计数器恢复和故障关闭与故障打开安全状态之间选择的保障措施。","Sensors",75,{"impact":130,"substance":131,"depth":132,"authority":190,"freshness":134,"relevant":20,"comment":191},14,"面向智慧灌溉的信任边界参考架构论文，方法新颖、含软件验证与量化开销数据，但属概念验证、非田间实证，产业影响有限，可作为技术前沿精选。",[193],{"name":187,"url":184},[195,70,196,197,26],"数字乡村","农业物联网","智能灌溉",{"code":199,"slug":200,"name":201,"path":202,"parent_code":203},"H3","irrigation","水资源与灌溉","\u002Ftopic\u002Fenvironment\u002Firrigation","H",[205],{"code":74,"slug":75,"name":76,"path":77,"parent_code":78},{"status":81,"locked":14,"version":32,"method":33,"evidence":207},{"candidates":208,"agricultural_evidence":42},[209,215,219,226,232,238,242],{"code":199,"score":210,"supported":42,"title":211,"abstract":212,"tags":214},15,[200],[213,200],"灌溉",[197],{"code":74,"score":13,"supported":42,"title":216,"abstract":217,"tags":218},[],[89,90,87],[196],{"code":220,"score":221,"supported":42,"title":222,"abstract":223,"tags":225},"B7",3,[],[224],"greenhouse",[],{"code":227,"score":221,"supported":42,"title":228,"abstract":229,"tags":231},"C",[],[230],"livestock",[],{"code":233,"score":221,"supported":42,"title":234,"abstract":235,"tags":237},"F3",[],[236],"fertigation",[],{"code":37,"score":38,"supported":14,"title":239,"abstract":240,"tags":241},[],[],[195,26],{"code":93,"score":20,"supported":14,"title":243,"abstract":244,"tags":245},[],[],[70],[247,248],"智能灌溉 信任边界 参考架构","LoRaWAN 灌溉 安全","智能灌溉信任边界参考架构-5077","10.3390\u002Fs26206545",{"doi":250,"openalex_id":252,"authors":253,"venue":187,"cited_by_count":62,"oa_url":184,"card":269,"direction":117,"ingested_from":119},"W7222165876",[254,257,260,263,266],{"name":255,"orcid":256},"Alvertos Ioannis Mourikis","https:\u002F\u002Forcid.org\u002F0009-0009-2386-2803",{"name":258,"orcid":259},"Iosif Polenakis","https:\u002F\u002Forcid.org\u002F0000-0002-6427-5519",{"name":261,"orcid":262},"Christos Sarantidis","https:\u002F\u002Forcid.org\u002F0009-0003-9486-8483",{"name":264,"orcid":265},"Romanos Kalamatianos","https:\u002F\u002Forcid.org\u002F0009-0000-6939-5424",{"name":267,"orcid":268},"Ioannis Karydis","https:\u002F\u002Forcid.org\u002F0000-0002-9470-2729",{"tldr":270,"method":271,"finding":272,"direction":117,"opportunity":273},"提出面向智慧灌溉的安全参考架构，用软件验证可抵御重放与欺骗攻击。","七层三面参考架构、信任边界分类、确定性软件概念验证与LoRaWAN开销分析。","安全控制器在6种攻击场景下0次被攻破，负控制全部被攻破，且误报率为0。","可研究边缘验证控制与采样率、漂移、故障模式的映射，以及安全时间与失效安全状态选择。","2026-10-16T23:30:08.098924Z",{"id":276,"title":277,"url":278,"summary":279,"summary_zh":280,"content":8,"source_name":281,"source_url":278,"published_at":282,"category":60,"cover_url":8,"hotness":13,"is_selected":14,"score":283,"score_detail":284,"sources":287,"tags":289,"primary_topic":8,"secondary_topics":293,"classification":294,"search_phrases":317,"slug":320,"view_count":221,"doi":321,"paper":322,"created_at":341},4574,"A privacy-preserving hyper-spectral remote sensing image analysis framework based on matrix outsourcing computation","https:\u002F\u002Fdoi.org\u002F10.1186\u002Fs42400-026-00667-3","Abstract Hyper-spectral remote sensing image provides more detailed spectral information of ground targets, while the joint sparse coding-based clustering (JSCC) algorithm are proposed for accurate hyper-spectral image segmentation. However, since hyper-spectral image data processing represent one of the most time-consuming computing tasks, it necessitates the acceleration achieved by cloud outsourcing computation. Furthermore, data privacy and result availability issues in cloud computing should be considered in real-world scenarios. In this paper, we propose a novel privacy-preserving outsourcing scheme for matrix multiplication and matrix pseudo-inversion in the JSCC algorithm, to achieve efficient and secure hyper-spectral remote sensing image analysis. The core of our scheme is to present a novel matrix blinding method, which obscures the original matrices through element-wise computation and utilizes secret key index sets rather than subtly designed matrices, thereby further reducing the storage cost of encryption and decryption operations. Additionally, we correspondingly present a new verification method that computes and compares randomly selected elements in obscured matrices to guarantee the availability of returned results. Experimental results demonstrate that our scheme is 4.15–10.79% superior to the state-of-the-art matrix blinding based privacy-preserving outsourcing computation schemes on average and achieves an efficiency improvement of 73.49–80.45% compared to the original hyper-spectral remote sensing image analysis algorithm.","高光谱遥感图像提供了更详细的地物光谱信息，而基于联合稀疏编码的聚类（JSCC）算法则被提出用于实现精确的高光谱图像分割。然而，由于高光谱图像数据处理是最耗时的计算任务之一，因此需要通过云外包计算来加速。此外，在实际应用场景中，还需考虑云计算中的数据隐私和结果可用性问题。本文提出了一种新颖的隐私保护外包方案，用于JSCC算法中的矩阵乘法和矩阵伪逆运算，以实现高效且安全的高光谱遥感图像分析。该方案的核心在于提出一种新颖的矩阵盲化方法，通过逐元素计算对原始矩阵进行混淆，并利用密钥索引集而非精心设计的矩阵，从而进一步降低加密和解密操作的存储开销。此外，我们相应地提出了一种新的验证方法，通过计算并比较混淆矩阵中随机选取的元素来保证返回结果的可用性。实验结果表明，我们的方案平均优于基于矩阵盲化的最新隐私保护外包计算方案4.15–10.79%，并且相较于原始高光谱遥感图像分析算法实现了73.49–80.45%的效率提升。","Cybersecurity","2026-10-08T00:00:00Z",71,{"impact":130,"substance":285,"depth":132,"authority":133,"freshness":17,"relevant":20,"comment":286},20,"高光谱遥感图像隐私保护外包计算新方法，属农业遥感与信息安全交叉的学术进展，方法新颖但应用面偏窄。",[288],{"name":281,"url":278},[70,290,291,292,27],"农业人工智能","遥感","图像分析",[],{"status":295,"locked":14,"version":32,"method":33,"evidence":296},"needs_review",{"candidates":297,"agricultural_evidence":14,"reason":316},[298,303,308,312],{"code":155,"score":210,"supported":42,"title":299,"abstract":301,"tags":302},[300],"remote sensing",[291,300],[291],{"code":304,"score":38,"supported":14,"title":305,"abstract":306,"tags":307},"I2",[],[],[290,292],{"code":93,"score":20,"supported":14,"title":309,"abstract":310,"tags":311},[],[],[70],{"code":37,"score":20,"supported":14,"title":313,"abstract":314,"tags":315},[],[],[27],"农业相关性需要复核",[318,319],"高光谱遥感 图像分析 隐私保护","农业人工智能 图像分析 数据安全 智慧农业","高光谱遥感图像分析隐私保护-4574","10.1186\u002Fs42400-026-00667-3",{"doi":321,"openalex_id":323,"authors":324,"venue":281,"cited_by_count":62,"oa_url":334,"card":335,"direction":117,"ingested_from":119},"W7221009671",[325,327,329,332],{"name":326,"orcid":8},"Xinrong Sun",{"name":328,"orcid":8},"Yunting Tao",{"name":330,"orcid":331},"Fanyu Kong","https:\u002F\u002Forcid.org\u002F0000-0003-1369-6855",{"name":333,"orcid":8},"Guoyan Zhang","https:\u002F\u002Flink.springer.com\u002Fcontent\u002Fpdf\u002F10.1186\u002Fs42400-026-00667-3.pdf",{"tldr":336,"method":337,"finding":338,"direction":339,"opportunity":340},"提出基于矩阵外包计算的隐私保护框架，实现高光谱遥感图像安全高效分析。","矩阵盲化与验证方法，结合JSCC算法，外包矩阵乘法和伪逆计算。","方案比现有矩阵盲化方案平均优4.15-10.79%，比原算法效率提升73.49-80.45%。","农业遥感与作物表型","可探索隐私保护外包计算在实时作物表型分析、多源遥感数据融合中的落地与优化。","2026-10-10T23:30:13.943902Z",{"id":343,"title":344,"url":345,"summary":346,"summary_zh":347,"content":8,"source_name":348,"source_url":345,"published_at":349,"category":60,"cover_url":8,"hotness":13,"is_selected":14,"score":350,"score_detail":351,"sources":353,"tags":355,"primary_topic":360,"secondary_topics":365,"classification":366,"search_phrases":385,"slug":388,"view_count":20,"doi":389,"paper":390,"created_at":410},4243,"Digital corporate responsibility as an element of corporate social responsibility (a case study of Ukrainian agricultural enterprises)","https:\u002F\u002Fdoi.org\u002F10.36887\u002F2524-0455-2026-4-49","The article aims to substantiate the theoretical, methodological, and practical foundations of Digital Corporate Responsibility (DCR\u002FCDR) as a direction of Corporate Social Responsibility (CSR) amid the comprehensive digitalization of business processes, focusing on Ukraine’s agricultural sector. The study applies dialectical analysis and synthesis, grouping, structural-functional analysis, and case study methods. The results show that digitalization creates significant opportunities to improve the efficiency, productivity, and profitability of agribusiness while generating new ethical, social, and environmental risks, including cybersecurity threats, algorithmic bias, digital exclusion, the carbon footprint of IT infrastructure, and electronic waste. DCR is therefore considered an important mechanism for mitigating these risks and ensuring socially and environmentally responsible digital transformation. The scientific novelty lies in substantiating DCR within three interrelated ESG dimensions: digital environmental (E), digital social (S), and digital governance (G) responsibility. The study shows that implementing DCR can strengthen stakeholder relations, transparency, trust, and the sustainable development potential of agricultural companies. The experience of leading Ukrainian agricultural holdings, including Astarta and Kernel, illustrates practical approaches to combining digital technologies with responsible business practices. The research’s practical significance lies in the proposed use of corporate digital ethics codes to strengthen cybersecurity, protect digital rights, develop digital culture, and promote responsible digital behavior among employees and stakeholders. Further research should focus on developing a comprehensive system of indicators to assess the level of DCR, identifying relevant ESG criteria, and adapting international approaches and best practices to the institutional and socio-economic conditions of Ukrainian agribusiness. Keywords: Digital Corporate Responsibility, Corporate Social Responsibility, digitalization, digital transformation, ESG, agricultural sector, agribusiness, precision agriculture, digital ethics, sustainable development, cybersecurity, stakeholders.","本文旨在论证在企业流程全面数字化背景下，数字企业责任（Digital Corporate Responsibility, DCR\u002FCDR）作为企业社会责任（Corporate Social Responsibility, CSR）一个发展方向的理论、方法论与实践基础，并以乌克兰农业部门为聚焦对象。研究采用辩证分析与综合、分组法、结构功能分析以及案例研究等方法。结果表明，数字化为提升农业企业的效率、生产率和盈利能力创造了重要机遇，同时也带来了新的伦理、社会和环境风险，包括网络安全威胁、算法偏见、数字排斥、IT基础设施的碳足迹以及电子废弃物。因此，数字企业责任被视为缓解这些风险、确保社会与环境负责任的数字化转型的重要机制。本研究的科学新颖性在于从三个相互关联的ESG维度论证数字企业责任：数字环境（E）责任、数字社会（S）责任和数字治理（G）责任。研究表明，实施数字企业责任能够加强利益相关者关系、透明度、信任以及农业公司的可持续发展潜力。乌克兰领先农业控股公司，包括Astarta和Kernel的经验，展示了将数字技术与负责任商业实践相结合的实际路径。研究的实践意义在于提出利用企业数字伦理准则来加强网络安全、保护数字权利、发展数字文化，并促进员工和利益相关者负责任的数字行为。未来研究应着重开发评估数字企业责任水平的综合指标体系，确定相关ESG标准，并使国际方法和最佳实践适应乌克兰农业企业的制度与社会经济条件。关键词：数字企业责任，企业社会责任，数字化，数字化转型，ESG，农业部门，农业企业，精准农业，数字伦理，可持续发展，网络安全，利益相关者。","Actual problems of innovative economy and law","2026-10-04T00:00:00Z",55,{"impact":17,"substance":132,"depth":210,"authority":19,"freshness":17,"relevant":20,"comment":352},"乌克兰农业企业数字企业责任的理论与案例研究，提出数字环境、数字社会、数字治理三维ESG框架，对农业数字化风险治理有参考价值，但属境外期刊论文、影响范围有限。",[354],{"name":348,"url":345},[356,26,357,358,359],"数字农业","乌克兰农业","农业ESG","数字伦理",{"code":361,"slug":362,"name":363,"path":364,"parent_code":203},"H4","carbon","农业碳与绿色低碳","\u002Ftopic\u002Fenvironment\u002Fcarbon",[],{"status":81,"locked":14,"version":32,"method":33,"evidence":367},{"candidates":368,"agricultural_evidence":42},[369,375,381],{"code":93,"score":94,"supported":42,"title":370,"abstract":371,"tags":374},[],[372,373],"精准农业","precision agriculture",[356],{"code":361,"score":19,"supported":42,"title":376,"abstract":377,"tags":380},[],[378,379],"碳足迹","carbon footprint",[],{"code":37,"score":20,"supported":14,"title":382,"abstract":383,"tags":384},[],[],[26],[386,387],"Astarta Kernel 数字责任","乌克兰农业企业 数字化转型","AstartaKernel数字责任-4243","10.36887\u002F2524-0455-2026-4-49",{"doi":389,"openalex_id":391,"authors":392,"venue":348,"cited_by_count":62,"oa_url":402,"card":403,"direction":409,"ingested_from":119},"W7219887548",[393,396,399],{"name":394,"orcid":395},"Ірина Пасінович","https:\u002F\u002Forcid.org\u002F0000-0003-4899-7498",{"name":397,"orcid":398},"Olga Sych","https:\u002F\u002Forcid.org\u002F0000-0002-9322-8105",{"name":400,"orcid":401},"Orysia Vasylyna","https:\u002F\u002Forcid.org\u002F0000-0003-2124-3792","https:\u002F\u002Fapie.org.ua\u002Fwp-content\u002Fuploads\u002F2026\u002F10\u002Fapie_2026_r04_a49.pdf",{"tldr":404,"method":405,"finding":406,"direction":407,"opportunity":408},"研究乌克兰农业企业数字化中的数字企业责任，将其作为CSR新方向并构建ESG三维框架。","辩证分析、案例研究法，以Astarta和Kernel等乌克兰农业控股公司为例。","数字化带来效率提升的同时产生网络安全、算法偏见、数字排斥等新风险，需DCR机制应对。","农业绿色发展与碳","可开发DCR评估指标体系，将数字伦理与ESG标准适配到不同国家农业情境中。","数字乡村与农业信息化","2026-10-05T23:30:31.062780Z",{"id":412,"title":413,"url":414,"summary":415,"summary_zh":416,"content":8,"source_name":417,"source_url":414,"published_at":418,"category":60,"cover_url":8,"hotness":13,"is_selected":14,"score":419,"score_detail":420,"sources":422,"tags":424,"primary_topic":426,"secondary_topics":427,"classification":428,"search_phrases":452,"slug":455,"view_count":20,"doi":8,"paper":456,"created_at":470},4015,"Development of a Blockchain-Internet of Things (IoT) Security Framework","https:\u002F\u002Fcigrjournal.org\u002Findex.php\u002FEjounral\u002Farticle\u002Fview\u002F10447","Internet of Things (IoT) has revolutionized data connectivity, fostering advancements across various sectors enabling real-time monitoring. The integration of blockchain technology to enhance the security of agricultural IoT data presents significant opportunities for improving data integrity and confidentiality in farming operations. The challenge lies in developing reliable framework that ensures securing of data transmission and storage in agricultural IoT networks. This study aims to develop and evaluate a blockchain-IoT framework to enhance security in agricultural data management systems, specifically designed for soil moisture sensors and weather stations. The method adopted involved developing a proof-of-concept mechanisms using JavaScript, Web3.js, and Ethereum smart contracts with Advanced Encryption Standard (AES-256) symmetric encryption cryptography. Results show that the framework maintained unbreachable encryption in man-in-the-middle (MITM) and replay attack simulations, while achieving transaction throughput of up to 100 transactions per second (TPS) with an average confirmation time of under 10 seconds. Network performance remained stable up to 500 simultaneous device connections, with only minor delays noted at 600 devices and significant delays at 1,000, where confirmation times increased to 25-30 seconds. Blockchain framework successfully enhances the security and integrity of agricultural data collected from IoT devices, providing a practical solution to secure farm data management and monitoring systems","物联网（IoT）彻底改变了数据连接方式，推动了各行业的进步，实现了实时监测。将区块链技术集成以增强农业物联网数据的安全性，为提升农业运营中的数据完整性和保密性提供了重要机遇。当前的挑战在于开发一个可靠的框架，确保农业物联网网络中数据传输和存储的安全性。本研究旨在开发并评估一个区块链-物联网框架，以增强农业数据管理系统的安全性，该框架专门针对土壤湿度传感器和气象站设计。所采用的方法包括使用JavaScript、Web3.js和以太坊智能合约，结合高级加密标准（AES-256）对称加密密码学，开发概念验证机制。结果表明，该框架在中间人攻击（MITM）和重放攻击模拟中保持了不可突破的加密性，同时实现了高达每秒100笔交易（TPS）的交易吞吐量，平均确认时间低于10秒。网络性能在多达500个同时设备连接的情况下保持稳定，仅在600个设备时出现轻微延迟，在1，000个设备时出现显著延迟，确认时间增加至25-30秒。该区块链框架成功增强了从物联网设备收集的农业数据的安全性和完整性，为保障农场数据管理和监测系统提供了一种实用的解决方案。","Agricultural Engineering International: CIGR Journal","2026-09-29T00:00:00Z",73,{"impact":210,"substance":285,"depth":85,"authority":133,"freshness":17,"relevant":20,"comment":421},"该论文提出并验证了面向农业物联网的区块链安全框架，方法具体、数据翔实，对智慧农业数据可信管理有参考价值，但属细分技术进展，影响层级有限。",[423],{"name":417,"url":414},[70,196,141,27,425],"土壤墒情监测",{"code":74,"slug":75,"name":76,"path":77,"parent_code":78},[],{"status":81,"locked":14,"version":32,"method":33,"evidence":429},{"candidates":430,"agricultural_evidence":42},[431,436,443,448],{"code":74,"score":432,"supported":42,"title":433,"abstract":434,"tags":435},26,[90,87],[89,90,87],[196],{"code":437,"score":19,"supported":42,"title":438,"abstract":439,"tags":442},"H2",[],[440,441],"土壤","soil",[],{"code":37,"score":48,"supported":42,"title":444,"abstract":445,"tags":447},[],[446],"agricultural data",[27],{"code":93,"score":20,"supported":14,"title":449,"abstract":450,"tags":451},[],[],[70],[453,454],"区块链 农业物联网 数据安全","土壤湿度传感器 气象站 区块链","区块链农业物联网数据安全-4015",{"doi":8,"openalex_id":457,"authors":458,"venue":417,"cited_by_count":62,"oa_url":8,"card":465,"direction":117,"ingested_from":119},"W7215549195",[459,461,463],{"name":460,"orcid":8},"Opeyemi Abisoye",{"name":462,"orcid":8},"Kiddams JOSHUA",{"name":464,"orcid":8},"Blessing Abisoye",{"tldr":466,"method":467,"finding":468,"direction":117,"opportunity":469},"开发并评估基于区块链与物联网的农业数据安全框架，保障土壤湿度与气象站数据。","用JavaScript、Web3.js、以太坊智能合约及AES-256加密构建概","框架可抵御中间人与重放攻击，达100 TPS，500设备连接稳定，1000设备时延迟显著。","可研究轻量级共识与边缘计算结合，提升大规模农业物联网下的吞吐与实时性。","2026-10-02T23:30:15.081491Z"]