[HTML][HTML] Anomaly-based cyberattacks detection for smart homes: A systematic literature review

JII Araya, H Rifà-Pous - Internet of Things, 2023 - Elsevier
Smart homes, leveraging IoT technology to interconnect various devices and appliances to
the internet, enable remote monitoring, automation, and control. However, collecting …

[HTML][HTML] A stacking ensemble of deep learning models for IoT intrusion detection

R Lazzarini, H Tianfield, V Charissis - Knowledge-Based Systems, 2023 - Elsevier
The number of Internet of Things (IoT) devices has increased considerably in the past few
years, which resulted in an exponential growth of cyber attacks on IoT infrastructure. As a …

Anomaly Detection in Smart Environments: A Comprehensive Survey

D Fährmann, L Martín, L Sánchez, N Damer - IEEE Access, 2024 - ieeexplore.ieee.org
Anomaly detection is a critical task in ensuring the security and safety of infrastructure and
individuals in smart environments. This paper provides a comprehensive analysis of recent …

Anomaly-based intrusion detection approach for IoT networks using machine learning

P Maniriho, E Niyigaba, Z Bizimana… - 2020 international …, 2020 - ieeexplore.ieee.org
The proliferation of the Internet of Things (IoT) devices in smart environments such as smart
cities or smart home facilitate communication between various objects. Nevertheless, this …

{ARGUS}:{Context-Based} Detection of Stealthy {IoT} Infiltration Attacks

P Rieger, M Chilese, R Mohamed, M Miettinen… - 32nd USENIX Security …, 2023 - usenix.org
IoT application domains, device diversity and connectivity are rapidly growing. IoT devices
control various functions in smart homes and buildings, smart cities, and smart factories …

Hybrid Bayesian optimization hypertuned catboost approach for malicious access and anomaly detection in IoT nomalyframework

J Nayak, B Naik, PB Dash, S Vimal, S Kadry - … Computing: Informatics and …, 2022 - Elsevier
The successful applications and diversified popularity of the Internet of Things (IoT) present
various advantages and opportunities in broad characteristics of our lives. However …

Robust learning-enabled intelligence for the internet of things: A survey from the perspectives of noisy data and adversarial examples

Y Wu - IEEE Internet of Things Journal, 2020 - ieeexplore.ieee.org
The Internet of Things (IoT) has been widely adopted in a range of verticals, eg, automation,
health, energy, and manufacturing. Many of the applications in these sectors, such as self …

Ensemble-based spam detection in smart home IoT devices time series data using machine learning techniques

A Zainab, S S. Refaat, O Bouhali - Information, 2020 - mdpi.com
The number of Internet of Things (IoT) devices is growing at a fast pace in smart homes,
producing large amounts of data, which are mostly transferred over wireless communication …

Anomaly detection in IoT environment using machine learning

H Bilakanti, S Pasam, V Palakollu… - Security and …, 2024 - Wiley Online Library
This research paper delves into the security concerns within Internet of Things (IoT)
networks, emphasizing the need to safeguard the extensive data generated by …

Three-layer hybrid intrusion detection model for smart home malicious attacks

L Shi, L Wu, Z Guan - Computers & Electrical Engineering, 2021 - Elsevier
With the development of Internet of Things and the increasingly rampant malicious network
activities, higher requirements are put forward for security to detect malicious behavior and …