"Alatalo, Janne" - Selaus tekijän mukaan Julkaisut
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Anomaly-Based Network Intrusion Detection Using Wavelets and Adversarial Autoencoders
Lecture Notes in Computer Science book series (Springer, 2019)The number of intrusions and attacks against data networks and networked systems increases constantly, while encryption has made it more difficult to inspect network traffic and classify it as malicious. In this paper, an ... -
Artificial Intelligence in the IoT Era: A Review of Edge AI Hardware and Software
Proceedings of the 31st Conference of Open Innovations Association FRUCT : 1 (FRUCT, 2022)The modern trend of moving artificial intelligence computation near to the origin of data sources has increased the demand for new hardware and software suitable for such environments. We carried out a scoping study to ... -
Chromatic and Spatial Analysis of One-Pixel Attacks Against an Image Classifier
Networked Systems (Springer International Publishing, 2022) -
Detecting One-Pixel Attacks Using Variational Autoencoders
Lecture notes in networks and systems (Springer, 2022) -
Food supply chain cyber threats: a scoping review
Lecture notes in networks and systems (Springer Nature, 2024) -
Improved Difference Images for Change Detection Classifiers in SAR Imagery Using Deep Learning
IEEE Transactions on Geoscience and Remote Sensing (Institute of Electrical and Electronics Engineers (IEEE), 2023) -
Network anomaly detection based on WaveNet
(Springer, 2019)Increasing amount of attacks and intrusions against networked systems and data networks requires sensor capability. Data in modern networks, including the Internet, is often encrypted, making classical traffic analysis ... -
Predicting the electricity consumption of Finland
Automaatiopäivät - Automation Days Proceedings (Suomen automaatioseura, 2023) -
Statistical evaluation of artificial intelligence -based intrusion detection system
(Springer, 2020)Training neural networks with captured real-world network data may fail to ascertain whether or not the network architecture is capable of learning the types of correlations expected to be present in real data. In this ...
