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Papers tagged with "Federated Learning"
A Privacy-Preserving Federated Learning Framework With Dual Explainability For Hybrid CNN–LSTM Based Anomaly Detection In IoT Network Traffic
Intrusion Detection Systems (IDS) For The Internet Of Things Face A Three-way Tension: Deep Models Detect Attacks Accurately But Behave As Opaque Black Boxes, Centralised Training Pipelines Require Raw Traffic To Be Exported From Every Devi...
Federated Learning And Explainable Artificial Intelligence For Intrusion Detection In IoT Networks: A Review
The Rapid Enlargement Of The Internet Of Things Has Turned Billions Of Weakly Protected Devices Into An Attractive Attack Surface, And Machine-learning Intrusion Detection Has Become The Default Defensive Answer. Three Difficulties, However...
AI Cardiologist: Advancements In Supervised Learning For Heart Disease Prediction
Cardiovascular Disease (CVD) Continues To Pose A Significant Global Health Challenge, Demanding Innovative Approaches For Early Detection And Prevention. This Paper Presents An AI Cardiologist System That Leverages Supervised Machine Learni...
AI-Driven Banking Security Monitoring System
Banking Environments Consistently Rank Among The Most Security-critical Operational Domains, Where Institutions Must Safeguard Financial Assets, Sensitive Customer Information, And Personnel Against Theft, Fraud, And Unauthorized Access. Em...
Privacy-Preserving Multiple Payment Fraud Detection Using LSTM-based Federated Learning.
This Paper Presents A Privacy-preserving Framework For Multiple Payment Fraud Detection Using Long Short-Term Memory (LSTM) And Federated Learning. The Model Captures Temporal Patterns In Transaction Data To Identify Fraudulent Activities E...
Brain Tumor Disease Detection Using Federated Learning With FedAvg
Federated Learning (FL) Has Emerged As A Critical Paradigm For Collaborative Model Training In Privacy-constrained Domains, Particularly In Healthcare. This Study Presents A Comprehensive FedAvg-based Framework For Brain Tumor Detection Fro...
DDOS DETECTION IN SOFTWARE DEFINED NETWORK USING FEDERATED LEARNING
Distributed Denial Of Service Attacks Have Become A Great Concern For Security In Software Defined Networking(SDN), As They Mostly Overload Centralized Security Mechanisms. In This Work, A Federated Learning-Based Intrusion Detection System...
A REVIEW PAPER ON INTELLIGENT ENERGY MANAGEMENTSYSTEM DESIGN AND SIMULATION FOR ELECTRIC VEHICLECHARGING STATION
Using Artificial Intelligence (AI), Machine Learning, And Advanced Security, This Paper Presents An Intelligent Energy Management System (IEMS) For Electric Vehicle (EV) Charging Stations. By Integrating Renewable Sources, Allocating Energy...
FEDERATED LEARNING METHOD TO TRAIN MACHINE LEARNING MODEL WITH DATA PRIVACY
Companies Are Constantly Looking For New Technology For Data Accessibility In Such A Way That Data Is Encrypted. One Such Is The Federated Learning. Federated Learning Is A Closed Loop System Involving The Statistical Training Of Models Kee...
Image captioning system
Image Captioning Has Been One Of The Major Problem Statements Over The Past Few Years In The Machine Learning World. The Major Problem Of The Image Captioning System Is That The Object To Be Identified Is Unknown I.e. There May Be Many Obje...