Security Measure

Security measures in various domains, from AI model ownership verification to IoT device protection and federated learning, are a major focus of current research, aiming to enhance robustness against diverse attacks. Prominent approaches leverage techniques like differential privacy, zero-trust architectures, and machine learning models (including CNNs, LSTMs, and Vision Transformers) to detect and mitigate threats, often balancing security with accuracy and privacy. These advancements are crucial for ensuring the trustworthiness and reliability of increasingly interconnected systems and protecting sensitive data in a wide range of applications.

Papers

April 27, 2023

CNN based IoT Device Identification
Kahraman Kostas
Convolutional Neural Network Security Vulnerability Smart Device Security Measure IoT Device Identification

August 3, 2022

A New Implementation of Federated Learning for Privacy and Security Enhancement
Xiang Ma, Haijian Sun, Rose Qingyang Hu, Yi Qian
Membership Inference Attack Privacy Policy Local Model FedAvg Algorithm Client Model Security Measure

July 13, 2022

Enhanced Security and Privacy via Fragmented Federated Learning
Najeeb Moharram Jebreel, Josep Domingo-Ferrer, Alberto Blanco-Justicia, David Sanchez
Privacy Policy Secure Aggregation Privacy Attack Split Federated Learning Security Measure Privacy Accuracy Certified Defense

April 3, 2022

A System for Interactive Examination of Learned Security Policies
Kim Hammar, Rolf Stadler
Markov Decision Process System Description Network Intrusion Detection Reinforcement Learning Approach Security Measure

Security Measure

Papers

CNN based IoT Device Identification

A New Implementation of Federated Learning for Privacy and Security Enhancement

Enhanced Security and Privacy via Fragmented Federated Learning

A System for Interactive Examination of Learned Security Policies