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[HTML][HTML] CPS-GUARD: Intrusion detection for cyber-physical systems and IoT devices using outlier-aware deep autoencoders
Abstract Detecting attacks to Cyber-Physical Systems (CPSs) is of utmost importance, due to
their increasingly frequent use in many critical assets. Intrusion detection in CPSs and other …
their increasingly frequent use in many critical assets. Intrusion detection in CPSs and other …
[HTML][HTML] Trustworthy artificial intelligence methods for users' physical and environmental security: A comprehensive review
Artificial Intelligence is an indispensable element of the modern world, constantly evolving
and contributing to the emergence of new technologies. We meet it in everyday applications …
and contributing to the emergence of new technologies. We meet it in everyday applications …
A deep learning method for lightweight and cross-device IoT botnet detection
Ensuring security of Internet of Things (IoT) devices in the face of threats and attacks is a
primary concern. IoT plays an increasingly key role in cyber–physical systems. Many …
primary concern. IoT plays an increasingly key role in cyber–physical systems. Many …
[HTML][HTML] Internet of Things botnets: A survey on Artificial Intelligence based detection techniques
Abstract The Internet of Things (IoT) is a game changer when it comes to digitization across
industries. The Fourth Industrial Revolution (4IR), brought about a paradigm shift indeed …
industries. The Fourth Industrial Revolution (4IR), brought about a paradigm shift indeed …
Towards realistic problem-space adversarial attacks against machine learning in network intrusion detection
Current trends in network intrusion detection systems (NIDS) capitalize on the extraction of
features from network traffic and the use of up-to-date machine and deep learning …
features from network traffic and the use of up-to-date machine and deep learning …
Traditional vs Federated Learning with Deep Autoencoders: A Study in IoT Intrusion Detection
Security of Internet of Things (IoT) devices and networks is a primary concern. Many
intrusion detection systems (IDS) proposals in the IoT leverage machine and deep learning …
intrusion detection systems (IDS) proposals in the IoT leverage machine and deep learning …
IoT security: A deep learning-based approach for intrusion detection and prevention
B Kauhsik, H Nandanwar… - … Algorithms and Soft …, 2023 - ieeexplore.ieee.org
The size and market worth of the Internet of Things (IoT) have expanded, but unfortunately,
the likelihood of user data being compromised has also risen. This presents a notable …
the likelihood of user data being compromised has also risen. This presents a notable …
[PDF][PDF] Improvement detection system on complex network using hybrid deep belief network and selection features
The challenge for intrusion detection system on internet of things networks (IDS-IoT) as a
complex networks is the constant evolution of both large and small attack techniques and …
complex networks is the constant evolution of both large and small attack techniques and …
AutoBots: A Botnet Intrusion Detection Scheme Using Deep Autoencoders
Recently, with the massive exchange of data over Internet of Things (IoT) ecosystems,
attacks surfaces have also intensified. In IoT, connected devices share data over open …
attacks surfaces have also intensified. In IoT, connected devices share data over open …
Autoencoder-Based Botnet Detection for Enhanced IoT Security
Abstract The Internet of Things (IoT) has revolutionized various industries by connecting
everyday objects to the internet, enabling them to collect and share data. However, the rapid …
everyday objects to the internet, enabling them to collect and share data. However, the rapid …