Computing Science, Communication and Security : 6th International Conference, COMS2 2025, Gujarat, India, September 12-13, 2025, Proceedings (Communications in Computer and Information Science)

個数:
  • 予約

Computing Science, Communication and Security : 6th International Conference, COMS2 2025, Gujarat, India, September 12-13, 2025, Proceedings (Communications in Computer and Information Science)

  • 現在予約受付中です。出版後の入荷・発送となります。
    重要:表示されている発売日は予定となり、発売が延期、中止、生産限定品で商品確保ができないなどの理由により、ご注文をお取消しさせていただく場合がございます。予めご了承ください。

    ●3Dセキュア導入とクレジットカードによるお支払いについて
  • 【入荷遅延について】
    世界情勢の影響により、海外からお取り寄せとなる洋書・洋古書の入荷が、表示している標準的な納期よりも遅延する場合がございます。
    おそれいりますが、あらかじめご了承くださいますようお願い申し上げます。
  • ◆画像の表紙や帯等は実物とは異なる場合があります。
  • ◆ウェブストアでの洋書販売価格は、弊社店舗等での販売価格とは異なります。
    また、洋書販売価格は、ご注文確定時点での日本円価格となります。
    ご注文確定後に、同じ洋書の販売価格が変動しても、それは反映されません。
  • 製本 Paperback:紙装版/ペーパーバック版
  • 商品コード 9783032160379

Full Description

This book constitutes the refereed proceedings of the 6th International Conference on Computing Science, Communication and Security, COMS2 2025, held in Gujarat, India, during September 12-13, 2025. 

The 27 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 238 submissions. They are organized into the following topical sections: Network and Communication Security; and Computing Science.

Contents

.- Network and Communication Security.

.- Game-Theoretic and Formal Approaches to Securing Non-Human Accounts in Identity and Access Management.

.- IoT-Based Automated Irrigation with Machine Learning for Crop Recommendation, Soil Classification, and Disease Detection.

.- Image Steganalysis using Siamese Contrastive Learning Network and Pix2Pix GAN with Linear Predictive Coding.

.- A Reinforcement Learning-Based Energy-Aware Hy brid Routing Protocol (RL-EAHR) for Enhancing Net work Lifetime, Scalability, and Resilience in Mobile Ad Hoc Networks (MANETs).

.- A Generative Method for Steganography by Cover Synthesis with Secure System.

.- Secure and Dynamic Routing in Mobile Ad-Hoc Networks through Cryptographic Assurance.

.- Optimizing IoT Networks: Insights from Compara tive Analysis in Terrestrial and Underwater Acoustic En vironments.

.- Enhancing Privacy and Security in Blockchain-Driven NFT Marketplaces Using Zero Knowledge Proof.

.- DeepXDetect: Real-Time Sandbox Malware Detection with Explainable AI.

.- Optimizing Base Station Placement to Minimize Interference for Satellite Terrestrial Networks (STN). 

.- Grouped Photon Quantum Key Distribution: An Improvised BB84 Protocol.

.- Optimized Multi-Process Computing for Efficient Multimodal Biometric Security System.

.- Design, Implementation and Verification of UART with APB Slave Interface using Verilog.

.- An adaptive promiscuous mode-oriented watchdog mechanism with a route rater for secure and reliable route identification in VANETs.

.- Development and UVM-Based Functional Verification of a Scalable & Configurable UART VIP.

.- Design and Verification of a Modified Numerically Controlled Oscillator for Clock Recovery in a Digital SerDes Receiver on an FPGA.

.- Computing Science.

.- Behavioral Biometrics: A Comparison of Keystroke Dynamics and Mouse Trajectories for Bot Detection.

.- A Chaos-Based Technique with Reversible Data Hiding for Enhanced Security of Medical Data.

.- Quantum-Resistant Image Encryption Using Adaptive Signal Transform and Generative Learning.

.- An Exhaustive Analysis of Machine Learning and Deep Learning for Credit Card Fraud Detection: Methodologies, Performance, and Challenges.

.- Real-time Path Deviation Detection System Using Blockchain Technology for Mission Critical Applications.

.- Secure Post-Quantum Authentication for Wearable Healthcare Devices.

.- Optimizing GIF Steganography with Deep Learning for Superior Image Concealment.

.- Deep Learning-Enhanced Boosting-Based Ensemble Model for Phishing Detection.

.- Securing Collaboration: Federated Learning with Homomorphic Encryption.

.- Decentralized Identity Federation Using Blockchain for Cross-Organizational Access.

.- Dynamic GCN-TCN-CapsNet: A Lightweight Hybrid Model for Real-Time Gait Recognition.

.- Smart Lab Optimization using Digital Twins and Ubiquitous Computing.

最近チェックした商品