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Advances in Cyber Security Analytics and Decision Systems / / edited by Shishir K. Shandilya, Neal Wagner, Atulya K. Nagar
| Advances in Cyber Security Analytics and Decision Systems / / edited by Shishir K. Shandilya, Neal Wagner, Atulya K. Nagar |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (XII, 145 p. 42 illus., 36 illus. in color.) |
| Disciplina | 621.3 |
| Collana | EAI/Springer Innovations in Communication and Computing |
| Soggetto topico |
Electrical engineering
Computer security System safety Computers Communications Engineering, Networks Systems and Data Security Security Science and Technology Information Systems and Communication Service |
| ISBN | 3-030-19353-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Introduction -- Chapter 2. Security Design -- Chapter 3. Authentication -- Chapter 4. Authorization -- Chapter 5. Cryptography -- Chapter 6. Virtualization -- Chapter 7. Security principles -- Chapter 8. Malware -- Chapter 9. SQL Injection -- Chapter 10. DoS -- Chapter 11. Worms -- Chapter 12. Virus -- Chapter 13. Malicious Code -- Chapter 14. Intrusion Detection Systems -- Chapter 15. Vulnerability -- Chapter 16. Cyber Laws -- Chapter 17. Cyber Crime -- Chapter 18. Homeland Security -- Chapter 19. Cryptocurrency -- Chapter 20. BitCoin -- Chapter 21. Block chain -- Chapter 22. Phishing -- Chapter 23. Spoofing -- Chapter 24. Cyber War -- Chapter 25. Hacktivism -- Chapter 26. Distributed Denial of Service (DDoS) -- Chapter 27. Identity Fraud -- Chapter 28. Honeypot -- Chapter 29. Keylogging -- Chapter 30. Scareware -- Chapter 31. Spam -- Chapter 32. Sponsored Attacks -- Chapter 33. Sneakernet -- Chapter 34. Virtual Militray Technologies -- Chapter 35. Zero Day -- Chapter 36. Intrusion prevention system (IPS) -- Chapter 37. Macro virus -- Chapter 38. Wannacry -- Chapter 39. Conclusion. |
| Record Nr. | UNINA-9910373902103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in Nature-Inspired Computing and Applications / / edited by Shishir Kumar Shandilya, Smita Shandilya, Atulya K. Nagar
| Advances in Nature-Inspired Computing and Applications / / edited by Shishir Kumar Shandilya, Smita Shandilya, Atulya K. Nagar |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (355 pages) |
| Disciplina | 006.38 |
| Collana | EAI/Springer Innovations in Communication and Computing |
| Soggetto topico |
Electrical engineering
Computational intelligence Artificial intelligence Computational complexity Bioinformatics Communications Engineering, Networks Computational Intelligence Artificial Intelligence Complexity |
| ISBN | 3-319-96451-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Nature-inspired Decision System for Secure Cyber Network Architecture -- Optimizing Resource Allocation in Next-Generation Wireless Networks Considering Carrier Aggregation Using Evolutionary Programming -- Artificial Feeding Birds (AFB): a new metaheuristic inspired by the behavior of pigeons -- Nature – Inspired Algorithms for Medical Image Processing -- Firefly Algorithm applied to the Estimation of Parameters of Photovoltaic Systems -- Realization of PSO-based Adaptive Beamforming Algorithm for Smart Antennas -- A Multi-objective Analysis and Comparison of Bio-inspired Approaches for the Cluster-Head Selection problem in WSN -- An Energy Efficient Cluster Head Selection using Artificial Bees Colony Optimization for Wireless Sensor Networks -- Modified Krill Herd Algorithm for Global Numerical Optimization Problems -- Application of Nature-Inspired Optimization Techniques in Vessel Traffic Control -- Enhanced throughput and accelerated detection of network attacks using a membrane computing model implemented on a GPU -- Physics-based Algorithms for Boolean Target Coverage -- A Hybrid Bio- Inspired Algorithm for Protein Domain Problems -- Modeling Service Discovery over Wireless Mesh Networks. |
| Record Nr. | UNINA-9910337471803321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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A Nature-Inspired Approach to Cryptology
| A Nature-Inspired Approach to Cryptology |
| Autore | Shandilya Shishir Kumar |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (325 pages) |
| Altri autori (Persone) |
DattaAgni
NagarAtulya K |
| Collana | Studies in Computational Intelligence Series |
| ISBN | 981-9970-81-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- "Scientia potentia est" -- Contents -- About the Authors -- List of Figures -- List of Tables -- Part I Preliminaries -- 1 Nature-inspired Algorithms -- 1.1 Introduction -- 1.2 Soft Computing -- 1.3 Nature-inspired Computing -- 1.4 Bioinformatics -- 1.5 Bio-inspired Computing -- 1.6 Relations Between the Paradigms -- 1.7 Key Concepts in Nature-inspired Algorithms -- 1.7.1 Fitness Function -- 1.7.2 Convergence and Optimization Criterion -- 1.7.3 Crossover and Mutation Operators -- 1.7.4 Selection Mechanism -- 1.7.5 Local Search -- 1.8 Taxonomy of Nature-inspired Algorithms -- 1.8.1 Physical Systems-inspired Algorithms -- 1.8.2 Swarm Intelligence Algorithms -- 1.8.3 Evolutionary Algorithms -- 1.9 Advantages and Challenges -- 1.9.1 Advantages: Optimization Efficiency and Robustness -- 1.9.2 Challenges: Parameter Tuning and Convergence -- 1.9.3 Traditional Versus Nature-inspired Algorithms -- 1.10 Applications of Nature-inspired Algorithms -- 1.11 Nature-inspired Cybersecurity -- 1.12 Future Research -- 1.13 Summary -- References -- 2 Cryptography Background -- 2.1 Introduction -- 2.2 Principles -- 2.2.1 Kerckhoffs' Principles -- 2.2.2 Provable Security -- 2.3 Objectives -- 2.3.1 Authentication -- 2.3.2 Authorization -- 2.3.3 Confidentiality -- 2.3.4 Integrity -- 2.3.5 Non-repudiation -- 2.3.6 Key Management -- 2.3.7 Cryptographic Algorithms -- 2.3.8 Continuous Evaluation and Improvement -- 2.3.9 CIA Triad -- 2.4 Preliminaries -- 2.4.1 Cryptosystem -- 2.4.2 Cipher -- 2.5 Block Versus Stream Ciphers -- 2.5.1 Block Cipher -- 2.5.2 Stream Cipher -- 2.6 Symmetric Versus Asymmetric Ciphers -- 2.7 Cryptographic Hash Function -- 2.7.1 Application: Password Storage -- 2.7.2 Application: Message Integrity -- 2.7.3 Application: Digital Signatures -- 2.7.4 Application: Blockchain -- 2.8 Cryptanalytic Attacks -- 2.9 Common Attack Mechanisms.
2.9.1 Brute-Force Attack -- 2.9.2 Man-in-the-Middle Attack -- 2.9.3 Replay Attack -- 2.9.4 Side-Channel Attack -- 2.9.5 Birthday Attack -- 2.10 Nature-Inspired Approach to Cryptography -- 2.11 Future Research -- 2.12 Summary -- Bibliography -- Part II Approaches -- 3 Learning-Based Cryptography -- 3.1 Introduction -- 3.2 Computational Learning Theory -- 3.3 CoLT and Cryptography -- 3.4 Neural Networks -- 3.5 Artificial Neural Networks -- 3.6 Types of Neural Networks -- 3.6.1 Feedforward Neural Networks (FFNNs) -- 3.6.2 Convolutional Neural Networks (CNNs) -- 3.6.3 Recurrent Neural Networks (RNNs) -- 3.6.4 Long Short-Term Memory Networks (LSTMs) -- 3.6.5 Autoencoder Networks -- 3.6.6 Generative Adversarial Networks (GANs) -- 3.7 Advantages and Limitations of Neural Networks -- 3.7.1 Advantages of Neural Networks -- 3.7.2 Limitations of Neural Networks -- 3.8 Neural Cryptography -- 3.9 Neural Cryptosystems -- 3.9.1 Wolfram's Original Proposal -- 3.9.2 Neural Protocol -- 3.9.3 Tree Parity Machine -- 3.9.4 Tree Parity Protocol -- 3.9.5 Permutation Parity Machine -- 3.9.6 Cryptosystems Based on Permutation Parity Machine -- 3.9.7 Biometric-Based Neural Cryptography -- 3.9.8 Learning Parity with Noise -- 3.9.9 Cryptosystems Based on Learning Parity with Noise -- 3.10 Future Research -- 3.10.1 Neural Network-Based Cryptanalysis -- 3.10.2 Neural Network-Based Cryptographic Primitives -- 3.10.3 Privacy-Preserving Machine Learning -- 3.11 Summary -- Bibliography -- 4 DNA-Based Cryptography -- 4.1 Introduction -- 4.2 DNA -- 4.3 DNA Computing -- 4.3.1 DNA Storage -- 4.3.2 DNA Encrypting -- 4.4 DNA Cryptography -- 4.5 DNA Encryption -- 4.5.1 GLR Cryptosystem -- 4.5.2 Verma et al. Cryptosystem -- 4.5.3 DNA XOR Cryptography -- 4.6 Future Research -- 4.7 Summary -- Bibliography -- 5 Biometric and Bio-Cryptography -- 5.1 Introduction -- 5.2 Biometrics. 5.3 Biometric Template -- 5.4 Biometric Systems -- 5.5 Bio-Cryptography -- 5.6 Relationship with Biometrics -- 5.7 Examples of Bio-Cryptography -- 5.7.1 Explanation of Bio-Cryptography -- 5.7.2 Formalism of Bio-Cryptography -- 5.7.3 Types of Biometric Modalities -- 5.7.4 Fingerprint Recognition -- 5.7.5 Iris Recognition -- 5.7.6 Facial Recognition -- 5.7.7 Voice Recognition -- 5.7.8 Other Biometric Modalities -- 5.8 Biometric System Components -- 5.8.1 Sensor Acquisition -- 5.8.2 Feature Extraction -- 5.8.3 Matching and Verification -- 5.8.4 Template Storage and Management -- 5.8.5 System Integration -- 5.9 Biometric Template Protection -- 5.9.1 Template Encryption Techniques -- 5.9.2 Secure Storage and Transmission -- 5.9.3 Template Update and Revocation -- 5.9.4 Cryptographic Key Generation from Biometrics -- 5.10 Bio-Cryptographic Protocols and Applications -- 5.10.1 Secure Authentication -- 5.10.2 Privacy-Preserving Biometric Systems -- 5.10.3 Multi-Factor Authentication -- 5.11 Biometric System Attacks -- 5.12 Significance -- 5.13 Challenges and Concerns -- 5.13.1 Security and Privacy Problems -- 5.13.2 Performance and Usability -- 5.14 Future Directions and Research Trends -- 5.14.1 Advances in Biometric Technology -- 5.14.2 Emerging Techniques Applied to Bio-Cryptographic -- 5.14.3 Mitigating Security and Privacy Concerns -- 5.15 Summary -- Bibliography -- 6 Nature-Inspired Lightweight Cryptosystems -- 6.1 Introduction -- 6.2 Lightweight Cryptography -- 6.3 Importance of Lightweight Cryptography -- 6.4 Traditional Lightweight Cryptographic Algorithms -- 6.5 Security Analysis -- 6.5.1 Threat Model -- 6.5.2 Security Evaluation Metrics -- 6.5.3 Performance Analysis -- 6.5.4 Hardware Implementations -- 6.5.5 Software Implementations -- 6.6 Future Research -- 6.7 Summary -- Bibliography -- 7 Chaos Cryptography -- 7.1 Introduction. 7.2 Dynamical System -- 7.2.1 State Space -- 7.2.2 Time -- 7.2.3 Evolution Rule -- 7.2.4 Maps -- 7.2.5 Iterated Function System -- 7.2.6 Flows -- 7.3 Nonlinear Dynamical Systems -- 7.4 Linear Dynamical System -- 7.5 Chaos Theory -- 7.6 Chaotic Maps -- 7.7 Chaotic Systems -- 7.7.1 Butterfly Effect -- 7.8 An Example of Chaotic System: Lorenz System -- 7.9 An Example of Chaotic System: Rössler System -- 7.10 Chaos Computing -- 7.11 Chaos Cryptography -- 7.12 Logistic Maps -- 7.13 Logistic Map-Based Cryptography -- 7.14 Tent Map -- 7.15 Tent Map Cryptosystem -- 7.16 Henon Map -- 7.17 Henon Map-Based Cryptography -- 7.18 Security Evaluation of Henon Map Cryptography -- 7.18.1 Expansive Key Space -- 7.18.2 Confusion and Diffusion -- 7.18.3 Cryptographic Attacks -- 7.19 Baker's Map -- 7.20 Baker's Map-Based Cryptography -- 7.21 Chaos-Based Hash Algorithm (CHA-1) -- 7.22 Lorenz Chaotic Key Exchange -- 7.23 Future Research -- 7.24 Summary -- Bibliography. |
| Record Nr. | UNINA-9910770275703321 |
Shandilya Shishir Kumar
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| Singapore : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Proceedings of Seventh International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012) [[electronic resource] ] : Volume 2 / / edited by Jagdish C. Bansal, Pramod Kumar Singh, Kusum Deep, Millie Pant, Atulya K. Nagar
| Proceedings of Seventh International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012) [[electronic resource] ] : Volume 2 / / edited by Jagdish C. Bansal, Pramod Kumar Singh, Kusum Deep, Millie Pant, Atulya K. Nagar |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | New Delhi : , : Springer India : , : Imprint : Springer, , 2013 |
| Descrizione fisica | 1 online resource (539 p.) |
| Disciplina | 621.39/9 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Computational intelligence
Artificial intelligence Data mining Computational Intelligence Artificial Intelligence Data Mining and Knowledge Discovery |
| ISBN |
1-283-93575-9
81-322-1041-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- Table of Contents -- About the Editors -- Organizing Committee -- Papers -- Author Index. |
| Record Nr. | UNINA-9910437909103321 |
| New Delhi : , : Springer India : , : Imprint : Springer, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Proceedings of Seventh International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012) [[electronic resource] ] : Volume 1 / / edited by Jagdish C. Bansal, Pramod Singh, Kusum Deep, Millie Pant, Atulya K. Nagar
| Proceedings of Seventh International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012) [[electronic resource] ] : Volume 1 / / edited by Jagdish C. Bansal, Pramod Singh, Kusum Deep, Millie Pant, Atulya K. Nagar |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | New Delhi : , : Springer India : , : Imprint : Springer, , 2013 |
| Descrizione fisica | 1 online resource (558 p.) |
| Disciplina | 621.39/9 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Computational intelligence
Artificial intelligence Data mining Computational Intelligence Artificial Intelligence Data Mining and Knowledge Discovery |
| ISBN |
1-283-93574-0
81-322-1038-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- Table of Contents -- About the editors -- Organizing Committee -- Papers -- Author Index. |
| Record Nr. | UNINA-9910437908103321 |
| New Delhi : , : Springer India : , : Imprint : Springer, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Proceedings of Sixth International Conference on Soft Computing for Problem Solving [[electronic resource] ] : SocProS 2016, Volume 2 / / edited by Kusum Deep, Jagdish Chand Bansal, Kedar Nath Das, Arvind Kumar Lal, Harish Garg, Atulya K. Nagar, Millie Pant
| Proceedings of Sixth International Conference on Soft Computing for Problem Solving [[electronic resource] ] : SocProS 2016, Volume 2 / / edited by Kusum Deep, Jagdish Chand Bansal, Kedar Nath Das, Arvind Kumar Lal, Harish Garg, Atulya K. Nagar, Millie Pant |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (X, 406 p. 172 illus.) |
| Disciplina | 006.3 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Computational intelligence
Signal processing Image processing Speech processing systems Artificial intelligence Computational Intelligence Signal, Image and Speech Processing Artificial Intelligence |
| ISBN | 981-10-3325-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Spammer Classification using Ensemble Methods over Content-Based Features -- A Modified BPDHE Enhancement Algorithm for Low Resolution Images -- Opposition aided Artificial Bee Colony Algorithm for Digital IIR Filter Design -- Cost Optimization of 2-Way Ribbed Slab Using Hybrid Self Organizing Migrating Algorithm -- A Complete Ontological survey of Cloud Forensic in the area of Cloud Computing -- Optimal Path Determination in a Survivable Virtual Topology of an Optical Network using Ant Colony Optimization -- Parameter Optimization for H.265/HEVC encoder using NSGA II -- PSO Based Context Sensitive Thresholding Technique for Automatic Image Segmentation -- Script Identification from Offline Handwritten Characters using Combination of Features -- Multi-Parameter Retrieval in a Porous Fin using Bi-nary-Coded Genetic Algorithm -- Effectiveness of Constrained Laplacian Biogeography Based Optimization for solving Structural Engineering Design Problems -- Soft Computing Based Software Testing – A Concise Travelogue -- Detection and Mitigation of spoofing attacks by using SDN in LAN -- Landslide Early Warning System Development using Statistical Analysis ofSensors’ Data at Tangni Landslide, Uttarakhand, India -- Wearable Haptic Based Pattern Feedback Sleeve System -- Job Scheduling algorithm in cloud environment considering the priority and cost of job -- Automatic Location of Blood Vessel Bifurcations in Digital Eye Fundus Images -- Recommendation System with Sentiment Analysis as Feedback Component -- A second order non-uniform mesh discretization for the numerical treatment of singular two-point boundary value problems with integral forcing function. |
| Record Nr. | UNINA-9910254326503321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Proceedings of Sixth International Conference on Soft Computing for Problem Solving [[electronic resource] ] : SocProS 2016, Volume 1 / / edited by Kusum Deep, Jagdish Chand Bansal, Kedar Nath Das, Arvind Kumar Lal, Harish Garg, Atulya K. Nagar, Millie Pant
| Proceedings of Sixth International Conference on Soft Computing for Problem Solving [[electronic resource] ] : SocProS 2016, Volume 1 / / edited by Kusum Deep, Jagdish Chand Bansal, Kedar Nath Das, Arvind Kumar Lal, Harish Garg, Atulya K. Nagar, Millie Pant |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (X, 362 p. 138 illus.) |
| Disciplina | 620 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Computational intelligence
Signal processing Image processing Speech processing systems Artificial intelligence Computational Intelligence Signal, Image and Speech Processing Artificial Intelligence |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Adaptive Scale Factor based Differential Evolution Algorithm -- Adaptive Balance Factor in Particle Swarm Optimization -- Community detection in complex networks: a novel approach based on ant lion optimizer -- Hybrid SOMA: A Tool for Optimizing TMD Parameters -- Fast Convergent Spider Monkey Optimization Algorithm -- Bi-level problem and SMD Assessment Delinquent for Single Impartial Bi-level Optimization -- An Adaptive Firefly Algorithm for Load Balancing in Cloud Computing -- Review on Inertia Weight Strategies for Particle Swarm Optimization -- Hybridized Gravitational Search Algorithms with Real Coded Genetic Algorithms for Integer and Mixed Integer Optimization Problems -- Spider Monkey Optimization Algorithm based on Metropolis principle -- An Analysis of modeling and optimization production cost through fuzzy linear programming problem with symmetric and right angle Triangular fuzzy number -- A New Intuitionistic Fuzzy Entropy of Order- With Applications in Multiple Attribute Decision Making -- The relationship between intuitionistic fuzzy programming and goal programming -- Implementation of Fuzzy Logic on FORTRAN Coded Free Convection around Vertical Tube -- Availability analysis of the Butter Oil Processing Plant using intuitionistic fuzzy differential equations. |
| Record Nr. | UNINA-9910254164803321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Proceedings of World Conference on Artificial Intelligence : Wcaiaa 2023
| Proceedings of World Conference on Artificial Intelligence : Wcaiaa 2023 |
| Autore | Tripathi Ashish Kumar |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2023 |
| Descrizione fisica | 1 online resource (543 pages) |
| Altri autori (Persone) |
AnandDarpan
NagarAtulya K |
| Collana | Algorithms for Intelligent Systems Series |
| ISBN | 981-9958-81-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- About the Editors -- 1 A Pragmatic Study of Machine Learning Models Used During Data Retrieval: An Empirical Perspective -- 1 Introduction -- 2 Literature Review -- 3 Pragmatic Analysis and Comparison -- 4 Conclusion and Future Scope -- References -- 2 Smart Knowledge Management for IT Services -- 1 Introduction -- 2 Literature Review -- 3 Objective -- 4 Methodology -- 4.1 Business Understanding -- 4.2 Problem Description -- 4.3 Proposed Solution -- 5 Data Understanding and Preparation -- 6 Data Modeling and Evaluation -- 6.1 Modeling -- 6.2 Evaluation -- 7 Deployment, Analysis, and Results -- 8 Conclusion and Future Scope -- References -- 3 Patient-Centric Electronic Health Records Management System Using Blockchain Based on Liquid Proof of Stake -- 1 Introduction -- 1.1 Blockchain -- 1.2 Cryptography -- 1.3 InterPlanetary File System (IPFS) -- 2 Literature Review -- 3 Proposed Model -- 4 Conclusion -- References -- 4 AI Driving Game Changing Trends in Project Delivery and Enterprise Performance -- 1 Introduction -- 2 Motivation of the Study -- 3 Organization Trends -- 4 Contribution of AI -- 5 Literature Review -- 6 Areas of Application of AI in Project Management -- 7 Conceptual Framework -- 8 Methodology -- 8.1 Hypothesis -- 8.2 Analysis and Discussion -- 8.3 Limitations of the Study -- 9 Impact on Project Managers -- 10 Conclusion -- References -- 5 Prediction of Children Age Range Based on Book Synopsis -- 1 Introduction -- 2 Review of Literature -- 3 Proposed System -- 3.1 Data Collection -- 3.2 Data Cleaning -- 3.3 Splitting of Dataset -- 3.4 Feature Extraction -- 3.5 Classification Models -- 4 Results -- 4.1 KNN -- 4.2 SVM -- 4.3 XGBoost -- 4.4 MLP -- 5 Conclusion and Future Recommendations -- References.
6 Predicting Credit Card Churn Using Support Vector Machine Tuned by Modified Reptile Search Algorithm -- 1 Introduction -- 2 Background and Related Works -- 2.1 Support Vector Machine (SVM) -- 2.2 Swarm Intelligence -- 3 Proposed Method -- 3.1 Original Reptile Search Algorithm -- 3.2 Modified RSA -- 4 Experiments and Discussion -- 4.1 Dataset Description -- 4.2 Experimental Setup and Solutions Encoding -- 4.3 Results and Discussion -- 5 Conclusion -- References -- 7 Comparison of Deep Learning Approaches for DNA-Binding Protein Classification Using CNN and Hybrid Models -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Collection -- 3.2 Data Pre-processing -- 3.3 Classification Models -- 4 Result and Discussion -- 5 Conclusion -- References -- 8 Exploring Jaccard Similarity and Cosine Similarity for Developing an Assamese Question-Answering System -- 1 Introduction -- 2 Related Study -- 3 Background -- 3.1 Tokenization -- 3.2 Stop Word Removal -- 3.3 Cosine Similarity -- 3.4 Jaccard Similarity -- 4 Proposed Work -- 5 Pre-processing -- 6 Establishment of Relationship -- 6.1 Jaccard Similarity -- 6.2 Cosine Similarity -- 7 Experiments -- 7.1 Data Preparation -- 7.2 Experimental Setup -- 7.3 Result and Analysis -- 7.4 Comparison Between English Chatbot and AQAS -- 8 Conclusion and Future Work -- References -- 9 Artificial Neural Network Modelling for Simulating Catchment Runoff: A Case Study of East Melbourne -- 1 Introduction -- 2 Study Area -- 3 Methodology -- 3.1 Description of Datasets -- 3.2 Datasets Preprocessing -- 3.3 Data Normalisation -- 3.4 Development of ANN Model -- 4 Results and Discussion -- 5 Future Works -- 6 Conclusion -- References -- 10 Effective Decision Making Through Skyline Visuals -- 1 Introduction -- 2 Related Work -- 3 Visualizing the Skyline -- 3.1 Skyline Visuals -- 3.2 Creating the Skyline Visuals. 4 Conclusion and Future Scope -- References -- 11 A Review Paper on the Integration of Blockchain Technology with IoT -- 1 Introduction -- 2 Literature Review -- 3 Background -- 3.1 Internet of Things -- 3.2 Architecture of IoT -- 3.3 Applications of IoT -- 3.4 Security Aspects of IoT -- 3.5 Attacks and Vulnerabilities in IoT -- 4 Blockchain Technology -- 4.1 Types of Blockchain -- 4.2 Structure of Blockchain -- 5 Integration of Blockchain and IoT -- 5.1 Blockchain Solution to IoT -- 5.2 Blockchain Scalability to IoT -- 5.3 Security in Blockchain and IoT -- 5.4 A Comparative Study -- 6 Conclusion -- References -- 12 Survey and Analysis of Epidemic Diseases Using Regression Algorithms -- 1 Introduction -- 2 Literature Review -- 2.1 Dengue -- 2.2 Influenza -- 2.3 Malaria -- 2.4 COVID-19 -- 2.5 Impact of Dengue, Malaria, and Influenza on COVID-19 -- 3 Data and Methods -- 4 Conclusion and Future Work -- References -- 13 Hybrid Pre-trained CNN for Multi-classification of Rice Plants -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 3.1 Dataset Description -- 3.2 Preprocessing -- 3.3 Classification -- 4 Results and Discussions -- 5 Conclusion -- References -- 14 Cauliflower Plant Disease Prediction Using Deep Learning Techniques -- 1 Introduction -- 2 Study on Plant Disease Prediction -- 3 Merits and Demerits of an Existing Method -- 4 Analysis and Performance Comparisons -- 5 Conclusion -- References -- 15 Disease Detection and Prediction in Plants Through Leaves Using Convolutional Neural Networks -- 1 Introduction -- 2 Literature Survey -- 3 Proposed Methodology -- 4 Implementation -- 5 Experiments and Results -- 6 Conclusion -- References -- 16 Classification of Breast Cancer Using Machine Learning: An In-Depth Analysis -- 1 Introduction -- 2 Several Levels of Classification. 2.1 Data Acquisition: Techniques for the Accumulation of Information -- 2.2 Data Preprocessing or Image Preprocessing -- 2.3 Segmentation -- 3 Features Extraction and Selection -- 3.1 Features Selection -- 3.2 Classification Using Machine Learning Algorithms -- 4 Literature Review -- 5 Conclusion and Discussion -- References -- 17 Prediction of Age, Gender, and Ethnicity Using Haar Cascade Algorithm in Convolutional Neural Networks -- 1 Introduction -- 2 Method -- 2.1 VGG Model -- 2.2 CNN Model -- 3 Proposed System -- 3.1 Implementation -- 3.2 Preprocessing -- 3.3 System Architecture -- 4 Results and Discussion -- 4.1 Transfer Learning Using VGG Face Model -- 4.2 Three Convolution Layer Model -- 4.3 Four Convolution Layer Model -- 4.4 Five Convolution Layer Model -- 4.5 Output Images and Classification -- 5 Conclusion -- References -- 18 Augmentation of Green and Clean Environment by Employing Automated Solar Lawn Mower for Exquisite Garden Design -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Introduction -- 4 Components Used -- 5 Results and Discussion -- 5.1 Implementation Process -- 6 Results -- 6.1 Comparative Study -- 7 Conclusion and Recommendation -- 7.1 Conclusion -- 7.2 Future Scope -- References -- 19 A Lightweight Solution to Intrusion Detection and Non-intrusive Data Encryption -- 1 Introduction -- 2 Methodology -- 2.1 Proposed System -- 2.2 Used Dataset and Preprocessing -- 2.3 Feature Extraction -- 2.4 Model Training -- 2.5 ECC Encryption -- 3 Result Analysis -- 4 Conclusion -- References -- 20 Efficiency of Cellular Automata Filters for Noise Reduction in Digital Images -- 1 Introduction -- 2 Cellular Automata -- 3 Noise and Its Types -- 4 Noise Reduction Techniques -- 4.1 Linear and Nonlinear Filters -- 4.2 Cellular Automata-Based Noise Reduction Filters -- 5 Methodology for Output Image Analysis. 6 Result and Discussion -- 7 Conclusion -- References -- 21 Effective Mutants' Classification for Mutation Testing of Smart Contracts -- 1 Introduction -- 1.1 Organization of Paper -- 2 Background -- 2.1 Smart Contract Features -- 2.2 Software Testing and Mutation Testing -- 2.3 Smart Contract Testing -- 2.4 Prioritizing Mutants in Mutation Testing -- 3 Problem Statement -- 4 Proposed Methodology -- 4.1 Mutant Classification -- 4.2 Dataset -- 4.3 Machine Learning-Based Evaluation of the Utility of Mutants -- 4.4 Features Selection for Characterizing Mutants -- 5 Results and Discussion -- 5.1 Feature Importance -- 5.2 Machine Learning Approach -- 5.3 Classification Report -- 6 Conclusion -- References -- 22 Scheming of Silver Nickel Magnopsor for Magneto-Plasmonic (MP) Activity -- 1 Introduction -- 2 Design Logic of the Device -- 3 Results and Discussion -- 4 Conclusion -- 5 Competing Interests -- References -- 23 Heart Stroke Prediction Using Different Machine Learning Algorithms -- 1 Introduction -- 2 Methodology -- 2.1 Proposed Method for Prediction -- 2.2 Input Data -- 2.3 Data Pre-processing -- 2.4 Split Data -- 2.5 Train Data -- 2.6 Test Data -- 2.7 Algorithms -- 3 Result Analysis -- 3.1 Precision -- 3.2 Recall -- 3.3 F-Measure -- 3.4 Accuracy -- 4 Conclusion -- References -- 24 Credit Card Fraud Detection Using Hybrid Machine Learning Algorithm -- 1 Introduction -- 2 Problem Statement -- 3 Related Work -- 4 Material and Methods -- 4.1 Decision Tree Algorithm -- 4.2 Random Forest Algorithm -- 4.3 Honey Bee Algorithm -- 4.4 Synthetic Minority Oversampling Technique (SMOTE) -- 4.5 Confusion Matrix and Related Metrics -- 5 Proposed Model -- 5.1 Credit Card Fraud Detection Using Hybrid Machine Learning Algorithm -- 6 Results and Discussion -- 7 Conclusions and Future Work -- References. 25 Smart Air Pollution Monitoring System for Hospital Environment Using Wireless Sensor and LabVIEW. |
| Record Nr. | UNINA-9910760291403321 |
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Tripathi Ashish Kumar
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| Singapore : , : Springer Singapore Pte. Limited, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Sine Cosine Algorithm for Optimization [[electronic resource] /] / by Jagdish Chand Bansal, Prathu Bajpai, Anjali Rawat, Atulya K. Nagar
| Sine Cosine Algorithm for Optimization [[electronic resource] /] / by Jagdish Chand Bansal, Prathu Bajpai, Anjali Rawat, Atulya K. Nagar |
| Autore | Bansal Jagdish Chand |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (114 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
BajpaiPrathu
RawatAnjali NagarAtulya K |
| Collana | SpringerBriefs in Computational Intelligence |
| Soggetto topico |
Computational intelligence
Mathematical optimization Algorithms Computational Intelligence Optimization |
| ISBN | 981-19-9722-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Sine Cosine Algorithm -- Sine Cosine Algorithm for Multi-Objective Optimization -- Sine Cosine Algorithm for Discrete Optimization Problems -- Advancements in the Sine Cosine Algorithm -- Conclusion and Further Research Directions. |
| Record Nr. | UNINA-9910645978903321 |
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Bansal Jagdish Chand
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Smart Trends in Systems, Security and Sustainability [[electronic resource] ] : Proceedings of WS4 2017 / / edited by Xin-She Yang, Atulya K. Nagar, Amit Joshi
| Smart Trends in Systems, Security and Sustainability [[electronic resource] ] : Proceedings of WS4 2017 / / edited by Xin-She Yang, Atulya K. Nagar, Amit Joshi |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XX, 348 p. 127 illus.) |
| Disciplina | 004.6 |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Electrical engineering
Computer security Data mining Big data Communications Engineering, Networks Systems and Data Security Data Mining and Knowledge Discovery Big Data |
| ISBN | 981-10-6916-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- Organizing Committee -- About the Editors -- Table of Contents -- 31 papers -- Author Index. |
| Record Nr. | UNINA-9910299583503321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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