Self-supervised learning for time series analysis: Taxonomy, progress, and prospects
Self-supervised learning (SSL) has recently achieved impressive performance on various
time series tasks. The most prominent advantage of SSL is that it reduces the dependence …
time series tasks. The most prominent advantage of SSL is that it reduces the dependence …
Machine learning and blockchain technologies for cybersecurity in connected vehicles
Future connected and autonomous vehicles (CAVs) must be secured against cyberattacks
for their everyday functions on the road so that safety of passengers and vehicles can be …
for their everyday functions on the road so that safety of passengers and vehicles can be …
Neural polarizer: A lightweight and effective backdoor defense via purifying poisoned features
Recent studies have demonstrated the susceptibility of deep neural networks to backdoor
attacks. Given a backdoored model, its prediction of a poisoned sample with trigger will be …
attacks. Given a backdoored model, its prediction of a poisoned sample with trigger will be …
Static and sequential malicious attacks in the context of selective forgetting
With the growing demand for the right to be forgotten, there is an increasing need for
machine learning models to forget sensitive data and its impact. To address this, the …
machine learning models to forget sensitive data and its impact. To address this, the …
Apollon: a robust defense system against adversarial machine learning attacks in intrusion detection systems
Abstract The rise of Adversarial Machine Learning (AML) attacks is presenting a significant
challenge to Intrusion Detection Systems (IDS) and their ability to detect threats. To address …
challenge to Intrusion Detection Systems (IDS) and their ability to detect threats. To address …
Observation of seven astrophysical tau neutrino candidates with IceCube
R Abbasi, M Ackermann, J Adams, SK Agarwalla… - Physical review …, 2024 - APS
We report on a measurement of astrophysical tau neutrinos with 9.7 yr of IceCube data.
Using convolutional neural networks trained on images derived from simulated events …
Using convolutional neural networks trained on images derived from simulated events …
A survey of robustness and safety of 2d and 3d deep learning models against adversarial attacks
Benefiting from the rapid development of deep learning, 2D and 3D computer vision
applications are deployed in many safe-critical systems, such as autopilot and identity …
applications are deployed in many safe-critical systems, such as autopilot and identity …
Trustworthy distributed ai systems: Robustness, privacy, and governance
Emerging Distributed AI systems are revolutionizing big data computing and data
processing capabilities with growing economic and societal impact. However, recent studies …
processing capabilities with growing economic and societal impact. However, recent studies …
A review on visual privacy preservation techniques for active and assisted living
This paper reviews the state of the art in visual privacy protection techniques, with particular
attention paid to techniques applicable to the field of Active and Assisted Living (AAL). A …
attention paid to techniques applicable to the field of Active and Assisted Living (AAL). A …
A Survey of strategy-driven evasion methods for PE malware: transformation, concealment, and attack
The continuous proliferation of malware poses a formidable threat to the cyberspace
landscape. Researchers have proffered a multitude of sophisticated defense mechanisms …
landscape. Researchers have proffered a multitude of sophisticated defense mechanisms …