Results 101 to 110 of about 2,210 (159)

TinyML Security: Exploring Vulnerabilities in Resource-Constrained Machine Learning Systems

Tiny Machine Learning (TinyML) systems, which enable machine learning inference on highly resource-constrained devices, are transforming edge computing but encounter unique security challenges. These devices, restricted by RAM and CPU capabilities two to
Beerel, Peter A., Huckelberry, Jacob, Zhang, Yuke, Mickens, James, Sansone, Allison, Reddi, Vijay Janapa   +5 more
core  

Lightweight Real-Time Navigation for Autonomous Driving Using TinyML and Few-Shot Learning. [PDF]

Sensors (Basel)
Ali W, Iqbal A, Wadood A, Park H, Kang BO.   +4 more
europepmc   +1 more source

A privacy preserving optimized intelligent security framework for smart homes using zero trust architecture and explainability. [PDF]

Sci Rep
Gupta A, Gupta S, Sharma S, Singh J, Ali F, Kwak D.   +5 more
europepmc   +1 more source

Extreme Edge Computing for Secure and Private Multimodal Biometric Identification in Intelligent IoT Systems. [PDF]

Sensors (Basel)
de la Torre JA, Rincón F, Escolar S, Caruso A, Caba J, Barba J.   +5 more
europepmc   +1 more source

Cyber resilience across domains: an in-depth exploration of cybersecurity practices and paradigms from the home environment to Operational Technology (OT). [PDF]

Sci Rep
Sakthivel T, Balasubramanian K.
europepmc   +1 more source

A Sensor-Based TinyML Acoustic Monitoring System for Edge-Side Animal Sound Recognition on Resource-Constrained Microcontrollers. [PDF]

Sensors (Basel)
Wang Z, Yu G.
europepmc   +1 more source

Smart Energy Management in Agricultural Wireless Sensor Nodes Using TinyML-Based Adaptive Sampling. [PDF]

Sensors (Basel)
Hinostroza A, Tarrillo J, Nuñez M.
europepmc   +1 more source

A Federated Approach for Adaptive Urban Sound Classification on TinyML Edge Devices. [PDF]

Sensors (Basel)
Trigkas A, Piromalis D, Papageorgas P.
europepmc   +1 more source

Streamlining TinyML Lifecycle with Large Language Models: A Framework for Automation

Tiny Machine Learning (TinyML) has gained popularity in recent years as a way to deploy machine learning models on resource-constrained devices. Despite the increasing use of TinyML, its lifecycle management, which includes phases such as data processing,
Wu, Guanghan
core  

Intrusion Detection in the Internet of Things: A Comprehensive Review of Techniques, Architectures, Datasets, and Emerging Trends. [PDF]

Sensors (Basel)
Komal A, Li S.
europepmc   +1 more source