Clustering and ensemble based approach for securing electricity theft detectors against evasion attacks
In smart power grids, electricity theft causes huge economic losses to electrical utility
companies. Machine learning (ML), especially deep neural network (DNN) models hold …
companies. Machine learning (ML), especially deep neural network (DNN) models hold …
Ensemble learning methods of adversarial attacks and defenses in computer vision: Recent progress
Z Lu, H Hu, S Huo, S Li - 2021 International Conference on …, 2022 - ieeexplore.ieee.org
Artificial intelligence (AI) has developed rapidly in recent decades and is widely used in
many fields, such as natural language processing, voice recognition, and especially …
many fields, such as natural language processing, voice recognition, and especially …
Zero-Query Adversarial Attack on Black-box Automatic Speech Recognition Systems
In recent years, extensive research has been conducted on the vulnerability of ASR systems,
revealing that black-box adversarial example attacks pose significant threats to real-world …
revealing that black-box adversarial example attacks pose significant threats to real-world …
Securing Smart Grid False Data Detectors Against White-box Evasion Attacks Without Sacrificing Accuracy
In the realm of smart grids, smart meters can be hacked to report false data to lower the
consumers' electricity bills. While machine learning (ML) techniques have shown promise in …
consumers' electricity bills. While machine learning (ML) techniques have shown promise in …
[PDF][PDF] HARDWARE-AWARE EFFICIENT AND ROBUST DEEP LEARNING
S Krithivasan - 2022 - hammer.purdue.edu
Outside of work, I am extremely lucky in the many friendships I made along the way that
helped me evolve as a person over the years. I am ever in debt for the unconditional comfort …
helped me evolve as a person over the years. I am ever in debt for the unconditional comfort …