LEADER 12491nam 22007335 450 001 9910878069803321 005 20240727125234.0 010 $a9789819720040$b(electronic bk.) 010 $z9789819720033 024 7 $a10.1007/978-981-97-2004-0 035 $a(MiAaPQ)EBC31570060 035 $a(Au-PeEL)EBL31570060 035 $a(CKB)33469067400041 035 $a(DE-He213)978-981-97-2004-0 035 $a(EXLCZ)9933469067400041 100 $a20240727d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aApplied Soft Computing and Communication Networks $eProceedings of ACN 2023 /$fedited by Sabu M. Thampi, Jiankun Hu, Ashok Kumar Das, Jimson Mathew, Shikha Tripathi 205 $a1st ed. 2024. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2024. 215 $a1 online resource (590 pages) 225 1 $aLecture Notes in Networks and Systems,$x2367-3389 ;$v966 311 08$aPrint version: Thampi, Sabu M. Applied Soft Computing and Communication Networks Singapore : Springer,c2024 9789819720033 320 $aIncludes bibliographical references and index. 327 $aIntro -- Conference Organization -- Preface -- Contents -- Editors and Contributors -- Artificial Intelligence and Human-Computer Interaction -- Open Gaze: Open-Source Eye Tracker for Smartphone Devices Using Deep Learning -- 1 Introduction -- 2 Dataset -- 3 Data Splits -- 3.1 MIT Split -- 3.2 Exclusively Mobile Devices in All Orientations -- 3.3 Mobile Devices Used Solely in Portrait Orientation -- 3.4 Google's Data Division -- 4 Model Architecture -- 5 Training -- 5.1 Implementation -- 5.2 Refining Hyperparameters -- 6 Post-training SVR Personalization -- 6.1 Differential Impact Based on Dataset Characteristics -- 6.2 Segmentation According to 13-Point Calibration -- 6.3 Google's 70/30 Training and Testing Split Methods -- 7 Results -- 7.1 PyTorch Results -- 8 Individualization Using Transformations -- 8.1 SVR Results -- 8.2 Version of Google Split -- 8.3 Version of MIT Split -- 8.4 Unique -- 8.5 Random Data Points/Samples -- 8.6 Outcomes from MIT Split Evaluation -- 8.7 Results from Google Split Evaluation -- 9 Future Scope and Improvements -- 10 Availability of Code and Data -- References -- Comparison on the Metaverse Space Development in Spatial.io Platform and Monaverse Platform -- 1 Introduction -- 2 Background -- 2.1 Spatial.io: Platform Overview -- 2.2 Monaverse: Platform Overview -- 3 Comparative Analysis -- 3.1 Decentralization -- 3.2 Interoperability -- 3.3 Space Creation and Scalability -- 3.4 Project Setup and Space Components -- 3.5 Interaction Interface of the Metaverse Space -- 3.6 Examples of Monetization and Opportunities -- 4 Discussion and Future Work -- References -- Intelligent Holo-Assistant Avatar with Lip-Syncing -- 1 Introduction -- 2 Methodology -- 2.1 Designing of GUI of Holo-Assistant Applications -- 2.2 Developing Intelligent Assistant Avatar with Lip-Syncing. 327 $a2.3 Integrate the Intelligent Holo-Assistant Avatar with Lip-Syncing -- 3 Implementation and Results -- 4 Conclusion -- References -- Historical Analysis of Financial Fraud and Its Future -- 1 Introduction -- 2 Historical Analysis of Financial Fraud -- 2.1 Early Modern Finance -- 2.2 Industrial Revolution and Capital Market Development -- 2.3 Post World War II -- 2.4 Globalization and Financial Deregulation -- 2.5 Digital Age and FinTech -- 3 Factors Contributing to Financial Fraud -- 3.1 The Human Factor -- 3.2 Weak Internal Controls -- 3.3 The Psychological Factor -- 4 Classification and Impacts of Financial Fraud -- 4.1 Direct Impact of Financial Fraud -- 4.2 Indirect Impact of Financial Fraud -- 5 The Future of Financial Fraud -- 5.1 The Technology Advancements -- 5.2 Dynamic Economic Circumstances -- 5.3 Regulatory Responses -- 5.4 Fraudster Adaptability -- 5.5 Ethical Considerations -- 6 Conclusion -- References -- A Study on Colour-Emotion Association for Happiness Among the Indian Youth Using Artificial Intelligence -- 1 Introduction -- 2 Methodology -- 2.1 Colour Extraction from T-Shirts -- 2.2 Facial Emotion Recognition -- 2.3 Data Collection for Colour-Emotion Mapping -- 3 Discussion -- 4 Conclusion and Future Directions -- References -- Comparative Analysis of Chicken Swarm Optimization and IbI Logics Algorithm for Multiobjective Optimization in kk-Coverage and mm-Connectivity Problem -- 1 Introduction -- 2 Related Works -- 3 Problem Formulation -- 3.1 Multiobjective Optimization Formulation -- 4 Proposed Algorithm -- 4.1 ILA Versus CSO -- 4.2 Fitness Function for both Algorithm -- 5 Simulation Results -- 6 Conclusion -- References -- Security and Privacy in Emerging Technologies -- Machine Learning-Based Detection of Attacks and Anomalies in Industrial Internet of Things (IIoT) Networks -- 1 Introduction. 327 $a1.1 IIoT Network Security Challenges -- 1.2 Attack Detection and Anomaly Identification Using Machine Learning -- 2 Literature Review -- 2.1 Existing IDS Systems Based on GANs -- 2.2 G-IDS Proposal -- 3 Dataset Information -- 4 Proposed System -- 4.1 Data Preprocessing -- 4.2 Feature Selection Algorithm -- 4.3 Generative Adversarial Networks -- 5 Results and Discussion -- 6 Conclusion -- References -- Privacy in Data Handling in Agile Development Environments -- 1 Introduction -- 1.1 Motivation -- 1.2 Problem and Target Audience -- 2 Theoretical Reference -- 3 Related Work -- 4 Proposal Presentation -- 4.1 Methodological Structure -- 4.2 Setting Security and Privacy Controls -- 4.3 Proposed Instruction Set -- 5 Practical Application -- 6 Final Considerations -- References -- Feature Enriched Framework for Rumor Detection Using Tweets -- 1 Introduction -- 2 Related Work -- 2.1 Machine Learning Models/Techniques -- 2.2 Deep Learning Models/Techniques -- 2.3 Hybrid Techniques -- 2.4 Word/Contextual Embedding Techniques and Transformer Models -- 3 Research Design -- 3.1 Feature Enriched Rumor Detection Framework -- 3.2 Perspectives Used for Rumor Modeling -- 4 Methodology -- 4.1 Models Used for Experimentation -- 4.2 Rumor Dataset Description -- 4.3 Experimentation -- 4.4 Evaluation Results -- 5 Analysis and Discussion -- 6 Conclusion -- References -- Enhancing KYC Verification: A Secure and Efficient Approach Utilizing Blockchain Technology -- 1 Introduction -- 2 Background -- 2.1 Traditional KYC Verification -- 2.2 Blockchain -- 2.3 KYC and Blockchain -- 3 Related Work -- 4 Enhancements -- 5 Proposed Approach -- 5.1 System Architecture -- 5.2 Proposed Algorithms -- 6 Results and Discussion -- 6.1 Scalability -- 6.2 Flexibility -- 6.3 Transparency -- 6.4 Privacy -- 6.5 History Tracking -- 7 Future Scope -- 8 Conclusion -- References. 327 $aA Smartphone Data Steganography Framework Based on K-mean Image Selection and Random Embedding in Three Image Channels -- 1 Introduction -- 2 Related Works -- 3 K-mean Select Random Insert (KSRI) Framework -- 3.1 The K-mean Selector Layer -- 3.2 The Random Inserter Layer -- 4 Experiment -- 4.1 The K-means Model Validation -- 4.2 The Data Embedding in Cover Images -- 5 Conclusion -- References -- Communication and Network Technologies -- Comparative Analysis of LSTM and GRU for Uplink Data Rate Prediction in 5G Networks -- 1 Introduction -- 2 Background and State of the Art -- 3 Data and Methods -- 3.1 Data Collection -- 3.2 RNN Variants-LSTM and GRU -- 3.3 Performance Measures -- 4 Proposed Approach -- 4.1 Data Preparation -- 4.2 Experiments -- 4.3 Evaluation -- 5 Conclusion -- References -- Scheduling in Time-Sensitive Networks Using Deep Reinforcement Learning -- 1 Introduction -- 2 Related Work -- 3 The Solution Approach -- 3.1 Reinforcement Learning -- 3.2 Simulation -- 4 Results and Discussions -- 5 Conclusion and Future Work -- References -- Power Control for Collaborative Sensors in Internet of Things Environments Using upper KK-means Approach -- 1 Introduction -- 2 Channel and Signal Modeling of Collaborative Sensors -- 3 Power Control Strategy of Collaborative Sensors -- 3.1 Energy Consumption Model -- 3.2 Power Control Strategy -- 4 Implementing K-means -- 5 Simulation and Results -- 6 Conclusion -- References -- Optimizing the EDFA Gain for Optical WDM Network Using Simulation Method -- 1 Introduction -- 2 Simulative Setup -- 3 Results and Discussion -- 4 Conclusion -- References -- RFID-Based Smart Trolley with Mobile Application -- 1 Introduction -- 2 Literature Survey -- 3 Materials and Methods -- 3.1 Arduino UNO -- 3.2 EM-18 Reader Module -- 3.3 Bluetooth Module (HC-05) -- 3.4 RFID Tags -- 3.5 Voltage Divider Circuit. 327 $a3.6 Android Studio -- 3.7 Radio Frequency Identification -- 4 Results and Discussions -- 5 Conclusion and Future Scope -- References -- Secure Authentication and Key Management -- SAKM-ITS: Secure Authentication and Key Management Protocol Concerning Intelligent Transportation Systems -- 1 Introduction -- 2 Related Work -- 3 Threat Model -- 4 Proposed Model -- 4.1 Registration of Entities -- 4.2 Authentication and Key Exchange Phase -- 5 Security Analysis -- 5.1 Formal Verification Using Scyther -- 5.2 Formal Verification Using Tamarin Prover -- 5.3 Informal Security Analysis -- 6 Comparative Analysis -- 6.1 Communication Cost -- 6.2 Computation Cost -- 7 Conclusion -- References -- Addressing Single Point of Failure in Group Communication of Constrained Environments -- 1 Introduction -- 2 Background -- 2.1 Shamir's Secret Sharing -- 2.2 Lagrange Interpolation -- 2.3 ECC and ECDH -- 3 The Proposed Scheme -- 3.1 Sharing Shares -- 4 Analysis of the Scheme -- 5 Conclusion -- References -- An RFID-Based Authentication Protocol for Smart Healthcare Applications -- 1 Introduction -- 1.1 Motivation and Contribution -- 1.2 Organization of the Paper -- 2 Preliminaries -- 2.1 Basic Concept of Elliptic Curve over a Prime Field GF(p) -- 2.2 Cryptographic Hash Function -- 2.3 Threat Model -- 3 Proposed Protocol -- 3.1 Initialization Phase -- 3.2 Registration Phase -- 3.3 Login and Mutual Authentication Phase -- 4 Security and Performance Analysis -- 4.1 Formal Security Verification Using AVISPA Tool -- 4.2 Security Features Comparison -- 4.3 Performance Analysis -- 5 Conclusion -- References -- Advanced Threat Detection and Mitigation -- On Credit Card Fraud Detection Using Machine Learning Techniques -- 1 Introduction -- 2 Machine Learning Techniques -- 2.1 Decision Tree -- 2.2 Random Forest -- 2.3 Isolation Forest -- 2.4 Support Vector Machine. 327 $a3 Experimental Results. 330 $aThis book constitutes thoroughly refereed post-conference proceedings of the International Applied Soft Computing and Communication Networks (ACN 2023) held at PES University, Bangalore, India, during December 18?20, 2023. The research papers presented were carefully reviewed and selected from several initial submissions. The papers are organized in topical sections on security and privacy, network management and software-defined networks, Internet of Things (IoT) and cyber-physical systems, intelligent distributed systems, mobile computing and vehicle communications, and emerging topics. The book is directed to the researchers and scientists engaged in various fields of intelligent systems. 410 0$aLecture Notes in Networks and Systems,$x2367-3389 ;$v966 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aTelecommunication 606 $aSignal processing 606 $aBig data 606 $aComputational Intelligence 606 $aArtificial Intelligence 606 $aCommunications Engineering, Networks 606 $aDigital and Analog Signal Processing 606 $aBig Data 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 0$aTelecommunication. 615 0$aSignal processing. 615 0$aBig data. 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 615 24$aCommunications Engineering, Networks. 615 24$aDigital and Analog Signal Processing. 615 24$aBig Data. 676 $a006.3 702 $aThampi$b Sabu M. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910878069803321 996 $aApplied Soft Computing and Communication Networks$92046956 997 $aUNINA