Big Data Technologies and Applications : 13th EAI International Conference, BDTA 2023, Edinburgh, UK, August 23-24, 2023, Proceedings

• Autore: Tan Zhiyuan
• Pubblicazione: Cham : , : Springer International Publishing AG, , 2024; ©2024
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (198 pages)
• Altri autori: WuYulei XuMin
• Nota di contenuto: Intro -- Preface -- Organization -- Contents -- Main Track - Regular Papers -- CTL-I: Infrared Few-Shot Learning via Omnidirectional Compatible Class-Incremental -- 1 Introduction -- 2 Related Work -- 2.1 Few Shot Learning -- 2.2 Class Incremental Learning in Infrared Images -- 3 Proposed Method -- 3.1 Preliminary -- 3.2 Model of CTL-I -- 3.3 Virtual Prototypes Assignment with Loss -- 3.4 Compatibility Update -- 4 Experiments -- 4.1 Implementation Details -- 4.2 Benchmark Comparison -- 4.3 Further Analysis -- 5 Conclusion -- References -- Can Federated Models Be Rectified Through Learning Negative Gradients? -- 1 Introduction -- 2 Related Work -- 2.1 Model Poisoning and Defending Mechanisms -- 2.2 Detection of Poisoned Models -- 2.3 Formulation of Machine Unlearning -- 2.4 Unlearning Federated Learning -- 2.5 Challenges to Federated Unlearning -- 3 Methodology -- 3.1 Experimental Data -- 3.2 Network Implementation -- 4 Experimental Results and Discussion -- 4.1 Federated Main Model -- 4.2 Retraining of Federated Main Model -- 5 Conclusion -- References -- BigText-QA: Question Answering over a Large-Scale Hybrid Knowledge Graph -- 1 Introduction -- 2 Background and Related Work -- 3 BigText Knowledge Graph -- 4 BigText Question Answering -- 4.1 Question-Answering Pipeline -- 4.2 Weighting Schemes -- 4.3 Similarities and Thresholds -- 5 Experiments -- 6 Result and Discussion -- 7 Conclusion -- References -- STLGCN: Spatial-Temporal Graph Convolutional Network for Long Term Traffic Forecasting -- 1 Introduction -- 2 Related Work -- 2.1 Graph Convolution -- 2.2 Graph Generation -- 2.3 Traffic Forecasting -- 3 Methods -- 3.1 Preliminary -- 3.2 Framework -- 3.3 Graph Generation Block -- 3.4 Spatial-Temporal Blocks -- 4 Experiments -- 4.1 Datasets -- 4.2 Baseline Algorithms -- 4.3 Experiment Settings -- 4.4 Experimental Results -- 5 Conclusions. ; References -- Image Forgery Detection Using Cryptography and Deep Learning -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Dataset Summary -- 3.2 Image Processing -- 3.3 Hash Generation -- 4 Experimental Design -- 4.1 Deep Learning Experiment -- 5 Results and Discussion -- 5.1 Deep Learning Without Hashing -- 5.2 Deep Learning with Cryptography -- 5.3 Results Evaluation -- 6 Conclusion -- References -- Revocable Attribute-Based Encryption Scheme with Cryptographic Reverse Firewalls -- 1 Introduction -- 1.1 Related Work -- 1.2 Our Contribution -- 2 Preliminary -- 2.1 Bilinear Groups -- 2.2 Access Structures -- 2.3 Linear Secret Sharing Schemes -- 3 System Model -- 3.1 Security Model -- 4 Our Construction -- 5 Our Construction with CRFs -- 6 Secure Analysis -- 6.1 Proof of RH-CPABE -- 6.2 Proof of RH-CPABE-CRF -- 7 Performance -- 8 Conclusion -- References -- IoT Attacks Countermeasures: Systematic Review and Future Research Direction -- 1 Introduction -- 1.1 Background and Statistics -- 1.2 Computing Survey -- 2 IoT Attack Countermeasures Background -- 2.1 Advantages of IoT Attack Countermeasures -- 2.2 Disadvantages of IoT Attack Countermeasures -- 3 Comparative Systematic Analysis of the Study -- 3.1 Classified by Publication Type -- 3.2 Classified by Publication Year -- 4 IoT Architecture and Its Security Challenges -- 4.1 Perception Layer (PL) -- 4.2 Middle-Ware Layer (ML) -- 4.3 Application Layer (AL) -- 4.4 Network Layer (NL) -- 4.5 Security Challenges and Threat Model -- 5 Countermeasures and Threat Models for Security Attacks in IoT -- 5.1 Novel IoT Attack Countermeasures -- 6 Future Direction, Summary and Conclusion -- 6.1 Conclusion -- References -- A Bibliometric Analysis and Systematic Review of a Blockchain-Based Chain of Custody for Digital Evidence -- 1 Introduction -- 2 Literature Search and Bibliometric Network. ; 2.1 Literature Search -- 2.2 Bibliometric Analysis -- 2.3 Blockchain and Digital Forensic Bibliometric Network -- 3 Systematic Review -- 3.1 Digital Evidence -- 3.2 Chain of Custody -- 3.3 Storage Architectures -- 3.4 Blockchain Technology: Key Principles and Characteristics -- 3.5 Blockchain's Intersection with Digital Forensics -- 3.6 Blockchain in Chain of Custody for Digital Evidence -- 3.7 Existing Frameworks and Methodology -- 3.8 Open-Ended Issues -- 4 Conclusion -- References -- Main Track-Short Paper and PhD Track -- Forest Fire Prediction Using Multi-Source Deep Learning -- 1 Introduction -- 2 Literature Review -- 3 Datasets -- 4 Methodology -- 5 Experimentation and Results -- 6 Conclusion -- References -- Research on Preprocessing Process for Improved Image Generation Based on Contrast Enhancement -- 1 Introduction -- 2 Proposed Preprocessing Process -- 2.1 Extract Optimal Values -- 2.2 Generation an Image -- 2.3 Verifying the Quality of the Generated Image -- 3 Conclusion -- References -- An Auditable Framework for Evidence Sharing and Management Using Smart Lockers and Distributed Technologies: Law Enforcement Use Case -- 1 Introduction -- 1.1 Challenges of Current Evidence Management Processes -- 2 Relevant Technologies -- 2.1 Blockchain and Its Feasibility for Evidence Storage -- 2.2 Evidence Storage Architectures -- 2.3 IPFS -- 2.4 Encryption Methods (Evidence Security and Access Control) -- 3 System Overview -- 3.1 System Requirements -- 3.2 System Design and Case Study -- 4 Conclusions -- References -- SECSOC Workshop -- A Review of the Non-Fungible Tokens (NFT): Challenges and Opportunities -- 1 Introduction -- 1.1 Problem Statement -- 1.2 Our Contribution -- 2 Background Overview of Blockchain Technology -- 2.1 Ethereum -- 2.2 Smart Contract -- 3 Non-Fungible Token (NFT) -- 3.1 Protecting Digital Collectibles. ; 3.2 Boosting Gaming Industry -- 3.3 Tokenised Stock -- 3.4 Protocols -- 3.5 Standards -- 3.6 Desired Properties -- 4 NFT Challenges -- 4.1 Usability Challenges -- 4.2 Slow Confirmation -- 4.3 High Gas-Prices -- 4.4 Data Inaccessibility -- 4.5 Anonymity and Privacy -- 4.6 Governance Consideration -- 4.7 Intellectual Property (IP) Right -- 5 Security Analysis -- 5.1 Cybersecurity -- 5.2 Spoofing -- 5.3 Tampering -- 5.4 Smart Contracts Security -- 5.5 Repudiation -- 5.6 DoS -- 6 Conclusion -- References -- Author Index.
• Titolo autorizzato: Big Data Technologies and Applications
• ISBN: 3-031-52265-6
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910831008903321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering Series