IDAC: Federated Learning-Based Intrusion Detection Using Autonomously Extracted Anomalies in IoT

T Ohtani, R Yamamoto, S Ohzahata - Sensors, 2024 - mdpi.com
The recent rapid growth in Internet of Things (IoT) technologies is enriching our daily lives
but significant information security risks in IoT fields have become apparent. In fact, there …

[图书][B] Security Framework for The Internet of Things Applications

SA Hamad, QZ Sheng, WE Zhang - 2024 - books.google.com
The text highlights a comprehensive survey that focuses on all security aspects and
challenges facing the Internet of Things systems, including outsourcing techniques for partial …

Toward improving the security of IoT and CPS devices: An AI approach

A Albasir, K Naik, R Manzano - Digital Threats: Research and Practice, 2023 - dl.acm.org
Detecting anomalously behaving devices in security-and-safety-critical applications is an
important challenge. This article presents an off-device methodology for detecting the …

Dynamic System Diversification for Securing Cloud-based IoT Subnetworks

H Almohri, L Watson, D Evans, S Billups - ACM Transactions on …, 2022 - dl.acm.org
Remote exploitation attacks use software vulnerabilities to penetrate through a network of
Internet of Things (IoT) devices. This work addresses defending against remote exploitation …

Detection of threats to IoT devices using scalable VPN-forwarded honeypots

A Tambe, YL Aung, R Sridharan, M Ochoa… - Proceedings of the …, 2019 - dl.acm.org
Attacks on Internet of Things (IoT) devices, exploiting inherent vulnerabilities, have
intensified over the last few years. Recent large-scale attacks, such as Persirai, Hakai, etc …

HADES-IoT: A practical host-based anomaly detection system for IoT devices

D Breitenbacher, I Homoliak, YL Aung… - Proceedings of the …, 2019 - dl.acm.org
Internet of Things (IoT) devices have become ubiquitous and spread across many
application domains including the industry, transportation, healthcare, and households …

CICADA: Cloud-based intelligent classification and active defense approach for IoT security

RL Neupane, T Zobrist, K Neupane… - … -IEEE Conference on …, 2023 - ieeexplore.ieee.org
Internet of Things (IoT) devices capture and process sensitive personally identifiable
information such as eg, camera feeds/health data from enterprises and households. These …

Score-VAE: Root Cause Analysis for Federated-Learning-Based IoT Anomaly Detection

J Fan, G Tang, K Wu, Z Zhao, Y Zhou… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Root cause analysis is the process of identifying the underlying factors responsible for
triggering anomaly detection alarms. In the context of anomaly detection for Internet of …

Similarity-Based Selective Federated Learning for Distributed Device-Specific Anomaly Detection

C Lübben, MO Pahl - … 2024-2024 IEEE Network Operations and …, 2024 - ieeexplore.ieee.org
Resource constraints and heterogeneity make securing the IoT a challenge. Device-specific
AD can address these challenges. Depending on the algorithm used, training device …

Network security for home iot devices must involve the user: a position paper

L De Carli, A Mignano - Foundations and Practice of Security: 13th …, 2021 - Springer
Many home IoT devices suffer from poor security design and confusing interfaces, lowering
the bar for successful cyberattacks. A popular approach to identify compromised IoT devices …