Towards Unsupervised Learning based Denoising of Cyber Physical System Data to Mitigate Security Concerns. (arXiv:2303.07530v1 [eess.SP])

A dataset, collected under an industrial setting, often contains a
significant portion of noises. In many cases, using trivial filters is not
enough to retrieve useful information i.e., accurate value without the noise.
One such data is time-series sensor readings collected from moving vehicles
containing fuel information. Due to the noisy dynamics and mobile environment,
the sensor readings can be very noisy. Denoising such a dataset is a
prerequisite for any useful application and security issues. Security is a
primitive …

cases cyber cyber physical data environment fuel industrial information mobile moving noise physical security sensor series system under unsupervised learning value vehicles