{"title":"Nitin Naik","description":null,"products":[{"product_id":"contributions-presented-at-the-international-conference-on-computing-communicati-ebook","title":"Contributions Presented at the International Conference on Computing, Communication, Cybersecurity \u0026 AI, July 10-11, 2025, Birmingham, UK","description":"\u003cp\u003ePart 1: Cybersecurity track 1.- When cybersecurity becomes cyberbiosecurity: Understanding cyberbiosecurity, its principles, components, importance, and challenges.- Hacking the organism through digital technology: Exploring cyberbiosecurity vulnerabilities, threats, risks and their mitigations.- Dynamic defense strategies for optical communication networks: Mitigating adversarial attacks through multi-scale diagnostics.- Ethical and security implications of generative AI in E-government: A study of data protection, model security and responsible AI.- When generative AI gets hacked: A comprehensive classification of cyberattacks on Large Language Models (LLMs) and their mitigation techniques.- Part 2: AI Track 1.- AI-based fundus screening for automated severity prediction of diabetic retinopathy.- ADR: Interpretability-guided adversarial perturbation removal for 3D point clouds via geometric completion.- An AI-enabled wearable system for tactical sign language recognition and secure data transmission.- X-Swin: A robust hierarchical vision transformer with explainable attention mechanisms for dementia severity classification from structural MRI.- Agentic AI for emergency response and comparative analysis of SmolAgents, LangGraph, AutoGen, Agno AGI and CrewAI for crisis solution.- An AI study investigating the relationship between air quality and COVID-19.- Performance evaluation of female students through SAW-based multi-criteria evaluation and unsupervised clustering.- A novel machine learning techniques for crime report classification to identify Indian penal code sections.- Comparative analysis of Federated Learning (FL), Reinforcement Learning (RL) and Evolution Strategy (ES) in gaming environments.- Part 3: Communication Track 1.- Malware detection - A comparative analysis of RISC-V and ARM architectures.- Secure and energy efficient inference optimisation for consumer GPUs in edge computing environments.- Investigation of security challenges and analysis of evaluation tools for IoT devices.- Lightweight end-to-end message-level encryption in Apache Kafka using ChaCha20 stream Cipher.- An approach towards open-source security solutions for information systems: Profiling attacker's behavior and communication patterns post-compromise.- Towards a real-time webcam feed narrator using multimodal language models and speech synthesis.- Part 4: Computing Track 1.- Gamified learning analytics: Predicting student success in blended education environments through machine learning classification models.- Maali: An intelligent gardening companion for plant care management.- How can ChatGPT help humans improve their capabilities: Understanding the key capabilities of ChatGPT.- The AI engine of creation: Exploring the capabilities of AI Chatbots based on generative AI, large language models and large multimodal models.- AI App behaviour monitor development for children with ALNS.- Justification of a set of parameters for software source code analysis.- Forecasting economic trends with generative AI: A Python framework for policy analysis.- Academic influencer for eLearning systems sponsorship and collaboration platform.- Community detection using enhanced non-weighted fuzzy C-means approach in online social network.- Part 5: Cybersecurity Track 2.- When generative AI prompts bite back: Investigating different types of prompt injection attacks on Large Language Models (LLMs) and their prevention methods.- Weaponising generative AI through data poisoning: Analysing various data poisoning attacks on Large Language Models (LLMs) and their countermeasures.- Literal Genie problem of generative AI: Understanding cyberattacks on generative AI models in the context of Large Language Models (LLMs) and their defence strategies.- Insecure output handling in Large Language Models (LLMs) and approaches to enhance output security, including prevention of LLM-based web application attacks.- Towards real-time anomaly detection and quarantine framework for cybersecurity systems.- A comprehensive threat modeling framework for SaaS-based E-commerce platforms.- A lightweight machine learning framework for DDoS attack detection in SDN.- Intelligent detection system with a machine learning extension to Suricata.- Threat landscape of adversarial attacks on generative AI and Large Language Models (LLMs): Exploring different types of adversarial attacks, associated risks, and mitigation strategies.- Uncovering advanced persistent threats via fuzzy logic-based DNS analysis.- Ransomware detection for securing hybrid learning environments in educational institutions.\u003c\/p\u003e","brand":"Nitin Naik","offers":[{"title":"Default Title","offer_id":53939292832071,"sku":"9783032167910","price":213.99,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0920\/5455\/2903\/files\/contributions-presented-at-the-international-confe-ebook-cover.webp?v=1779127448"}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0920\/5455\/2903\/collections\/nitin-naik-autor-kollektion.webp?v=1779127446","url":"https:\/\/www.cinebuch.de\/collections\/nitin-naik.oembed","provider":"CineBuch","version":"1.0","type":"link"}