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Titolo: |
Computing science, communication and security : second international conference, COMS2 2021, Gujarat, India, February 6-7, 2021 : revised selected papers / / Nirbhay Chaubey, Satyen Parikh, Kiran Amin (editors)
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Pubblicazione: | Cham, Switzerland : , : Springer, , [2021] |
©2021 | |
Edizione: | 1st ed. 2021. |
Descrizione fisica: | 1 online resource (XIV, 287 p. 178 illus., 132 illus. in color.) |
Disciplina: | 004 |
Soggetto topico: | Computer science |
Persona (resp. second.): | ChaubeyNirbhay Kumar <1971-> |
ParikhSatyen | |
AminKiran | |
Nota di bibliografia: | Includes bibliographical references and index. |
Nota di contenuto: | Intro -- Preface -- Organization -- Contents -- Artificial Intelligence and Machine Learning -- Data Balancing for Credit Card Fraud Detection Using Complementary Neural Networks and SMOTE Algorithm -- 1 Introduction -- 2 Literature Review -- 3 Dataset Description -- 4 Proposed Method -- 4.1 Data Balancing Network -- 4.2 Classification Algorithms -- 5 Results -- 5.1 Performance of CMTNN -- 5.2 Classification Results -- 6 Conclusions and Future Work -- References -- A Multi Class Classification for Detection of IoT Botnet Malware -- 1 Introduction -- 1.1 IoT Botnet -- 1.2 Briefing on IoT Botnet Attacks -- 2 Related Works -- 3 Data Collection and Preprocessing -- 3.1 Details About IoT-23 and MedBIoT DataSet -- 3.2 Log Extraction Using Zeek -- 3.3 Samples and Features Considered -- 3.4 KNN Imputation -- 4 Building a Classifier and Implementing GAN -- 4.1 Ensemble Approach -- 4.2 Applying Conditional Generative Adversarial Networks (CTGAN) -- 5 Results and Discussion -- 6 Conclusion and Future Work -- References -- An AI-Based Solution to Reduce Undesired Face-Touching as a Precautionary Measure for COVID-19 -- 1 Introduction -- 2 Proposed System -- 3 Methodology and Algorithmic Explanation -- 3.1 Introduction to BodyPix 2.0 -- 3.2 Working -- 4 Comparative Analysis of Existing Detection Methods -- 4.1 Available Models -- 4.2 Purpose of Choosing BodyPix 2.0 -- 5 Experimental Results -- 5.1 Accuracy Determination -- 5.2 Determining the Response Time -- 6 Conclusion -- References -- DDoS Attack Detection Using Artificial Neural Network -- 1 Introduction -- 2 Related Work -- 3 Data Set -- 3.1 Data Preparation -- 3.2 Sample Data Set -- 3.3 Feature Reduction -- 4 Normalization -- 4.1 Min-Max Algorithm -- 4.2 Label Encoding -- 4.3 Normalized Data Set -- 5 Back Propagation Neural Network -- 5.1 Algorithm -- 5.2 Back Propagation Neural Network (BPNN) Model. |
6 Results -- 7 Conclusion -- References -- Click Ad Fraud Detection Using XGBoost Gradient Boosting Algorithm -- 1 Introduction -- 1.1 World of Internet Advertising -- 1.2 Online Advertising Fraud -- 1.3 Click Fraud -- 1.4 Sources of Click Fraud -- 1.5 Problems of Detecting Click Fraud -- 2 Related Work -- 3 Proposed Solution -- 3.1 Dataset -- 3.2 Exploratory Data Analysis -- 3.3 Feature Engineering -- 4 Modelling -- 5 Results and Analysis -- 5.1 Model Evaluation -- 5.2 Comparing Results -- 5.3 Evaluating the Features Selected for Models -- 6 Conclusion and Future Work -- References -- A Natural Language Processing Approach to Mine Online Reviews Using Topic Modelling -- 1 Introduction -- 1.1 Feedback of Products -- 1.2 Recovery of Information from Unstructured Text, Collection of Functions -- 1.3 Semi-supervised Topic Modelling in Tweets Based on Topic Modelling -- 1.4 Topic Modelling for Social Media in the Restaurant Based Industry -- 2 Related Work -- 3 Method -- 4 Conclusions -- References -- An Implementation and Combining of Hybrid and Content Based and Collaborative Filtering Algorithms for the Higher Performance of Recommended Sytems -- 1 Introduction -- 2 Literature Survey -- 2.1 Content Based Recommenders (CBR) -- 2.2 Collaborative Filtering (CF) -- 3 Hybrid Recommended Systems Concept -- 4 Categorization of Hybrid Recommended Systems -- 4.1 Monolithic Hybrids -- 4.2 Parallelized Hybrids -- 4.3 Pipelined Hybrids -- 5 Similarity Metrices -- 5.1 Cosine Metrices -- 5.2 Adjusted Cosine Metrices -- 6 Road Map for Hybrid Recommended Systems -- 7 Train/Test of Dataset -- 8 Building Customized Algorithm and Evaluation on the Top of SurpriseLib -- 9 Evaluation of Recommender Systems -- 10 Step by Step Implementation and Experimental Setup of Recommender Systems Algorithm -- 11 Result and Discussions -- 12 Conclusion -- References. | |
Event-Related Potential Classification Based on EEG Data Using xDWAN with MDM and KNN -- 1 Introduction -- 2 Related Work -- 3 Data Description -- 4 Proposed Methodology -- 4.1 EEGNet Model: Compact Convolutional Neural Network (Compact-CNN) -- 4.2 xDAWN Spatial Filtering -- 4.3 xDAWAN with Riemannian Geometry -- 4.4 Classification -- 5 Result and Discussion -- 6 Conclusion and Future Work -- References -- Oil Spill Discrimination of SAR Satellite Images Using Deep Learning Based Semantic Segmentation -- 1 Introduction -- 2 Related Work -- 3 Problem Formulation -- 4 Image Datasets -- 5 Proposed Method -- 5.1 Image Preprocessing -- 5.2 Semantic Segmentation -- 6 Performance Measures -- 7 Results and Findings -- 7.1 Based on Filters -- 7.2 Based on Datasets -- 7.3 Based on Segmentation -- 8 Conclusion -- References -- Sentiment Analysis of Bangla Language Using Deep Learning Approaches -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Database Formation -- 3.2 Word Embedding -- 3.3 Convolutional Neural Network (CNN) -- 3.4 Long Short-Term Memory (LSTM) -- 3.5 CNN-LSTM -- 4 Result and Analysis -- 5 Conclusions -- References -- Networking and Communications -- Bit Error Rate Analysis of Optical Switch Buffer in Presence of Dispersion and Optical Amplifier Noise -- 1 Introduction -- 1.1 Novelty -- 1.2 Research Contributions -- 1.3 Layout -- 2 The Proposed Optical Switch Design -- 3 Performance Evaluation of the Proposed Switch -- 4 Conclusions and Future Work -- References -- Experimenting with Scalability of Software Defined Networks Using Pyretic and Frenetic -- 1 Introduction -- 2 Related Work -- 2.1 SDN - Software Defined Networks Architecture -- 2.2 Frenetic: A Network Programming Language -- 2.3 Modular SDN Programming with Pyretic -- 2.4 Research Gap and Motivation -- 3 FRENETIC and PYRETIC -- 3.1 Frenetic. | |
3.2 Pyretic (Python + Frenetic) -- 3.3 Pyretic Network Policies -- 3.4 Pyretic Features -- 4 Tools, Techniques and Simulation Environment -- 5 Experimental Procedure -- 5.1 Running Pyretic with Mininet -- 5.2 Generating Topologies -- 5.3 Traffic Generation and Logging Network Events -- 5.4 Graph Generation -- 6 Performance Metrics and Result Discussions -- 6.1 Throughput -- 6.2 Jitter -- 6.3 Latency -- 7 Conclusion -- 8 Future Work -- References -- Design and Implementation of Lightweight Dynamic Elliptic Curve Cryptography Using Schoof's Algorithm -- 1 Introduction -- 2 Design and Idea of Elliptic Curve Cryptography -- 2.1 Basic Idea Behind Elliptic Curve Cryptography -- 2.2 Limitation in Other Techniques -- 3 Preliminary Work -- 3.1 Elliptic Curves -- 3.2 Point Addition -- 3.3 Scalar Multiplication -- 3.4 Elliptic Curve Cryptography -- 3.5 Schoof's Algorithm -- 4 Proposed Dynamic Elliptic Curve Cryptography -- 4.1 Randomising the Constants -- 4.2 Counting the Points of Elliptic Curve -- 4.3 Randomly Choosing a Generator Point -- 4.4 Flowchart -- 5 Results -- 6 Conclusion -- References -- QRP: QPSO Based Routing Protocol for Energy Efficiency in Wireless Body Area Networks -- 1 Introduction -- 2 Related Work -- 2.1 Novelty -- 3 Preliminaries -- 3.1 Particle Swarm Optimization -- 3.2 Quantum-Inspired Particle Swarm Optimization -- 4 Materials and Methods -- 4.1 Networking Model -- 4.2 Energy Model -- 4.3 Path-Loss Model -- 4.4 Proposed Approach -- 5 Results and Discussions -- 5.1 Throughput -- 5.2 Residual Energy -- 5.3 Network Lifetime -- 5.4 Packets Sent to Sink -- 5.5 Packet Dropped -- 5.6 Path-Loss -- 6 Conclusion and Future Scope -- References -- Investigation of Alibaba Cloud Data Set for Resource Management in Cloud Computing -- 1 Introduction -- 2 Understanding Ali Baba Dataset -- 2.1 Resource Utilization Information. | |
2.2 Online Service (Container) -- 2.3 Online Request Table (Containerevent.csv) -- 2.4 Batch Workload -- 3 Data Analysis -- 3.1 Utilization and Summary of Data -- 3.2 Overall Utilization -- 3.3 Characterized Workload -- 3.4 Recent Research for the Dataset -- 4 Conclusion -- References -- A Hybrid Approach Based on ACO and Firefly Algorithm for Routing in FANETs -- 1 Introduction -- 2 Literature Review -- 3 Existing Algorithm -- 3.1 Ant Colony Optimization (ACO) -- 3.2 Firefly Algorithm -- 4 Proposed Algorithm -- 5 Parameters and Methods -- 5.1 Simulation Platform -- 5.2 Simulation Parameters -- 5.3 Performance Parameters -- 6 Results and Discussion -- 7 Conclusion -- References -- RC-Security Mechanism to Prevent Attacks on IoT Smart Switch -- 1 Introduction -- 1.1 Impacts of Attack -- 2 Review on IoT Security Solutions -- 2.1 Classification Hierarchy of DOS -- 3 Methodology -- 3.1 Experimental Setup for the IoT Smart Switch -- 3.2 Flow of the Experimental Setup -- 3.3 Request Capturing Security Mechanism (RCSM) -- 4 Results and Experiments -- 4.1 Attack Scenario -- 4.2 Mitigating Attacks -- 5 Conclusion and Future Work -- References -- Identifying the Impacts of Node Mobility on Network Layer Based Active and Passive Attacks in Mobile Ad Hoc Networks: A Simulation Perspective -- 1 Introduction -- 2 Literature Review -- 3 State of the Art -- 4 Methodology -- 5 Results and Discussion -- 6 Conclusion and Future Works -- References -- Simulated Analysis of Double-Gate MOSFET and FinFET Structure Using High-k Materials -- 1 Introduction -- 2 Short Channel Effects (SCEs) -- 3 Double-Gate MOSFET Device Structure -- 4 FinFET Device Structure -- 5 Performance Evaluation by High-k Materials -- 5.1 Concept of High-k Dielectrics -- 5.2 Choice of High-k Oxide -- 5.3 The Observed Design -- 6 Implementation -- 7 Simulation Results -- 8 Conclusion -- 9 Future Scope. | |
References. | |
Sommario/riassunto: | This book constitutes revised selected papers of the Second International Conference on Computing Science, Communication and Security, COMS2 2021, held in Gandhinagar, India, in February 2021. Due to the COVID-19 pandemic the conference was held virtually. The 19 full papers were thoroughly reveiwed and selected from 105 submissions. Papers are organised according to the topical sections on artificial intelligence and machine learning; networking and communications. |
Titolo autorizzato: | Computing Science, Communication and Security ![]() |
ISBN: | 3-030-76776-0 |
Formato: | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910483760803321 |
Lo trovi qui: | Univ. Federico II |
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