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Found 8 papers, 2 papers with code
TRLS: A Time Series Representation Learning Framework via Spectrogram for Medical Signal Processing
Representation learning frameworks in unlabeled time series have been proposed for medical signal processing.
SHISRCNet: Super-resolution And Classification Network For Low-resolution Breast Cancer Histopathology Image
CF module extracts and fuses the multi-scale features of SR images for classification.
Histopathological Image Classification
Image Classification
+1
Text-to-Image Diffusion Models can be Easily Backdoored through Multimodal Data Poisoning
To gain a better understanding of the training process and potential risks of text-to-image synthesis, we perform a systematic investigation of backdoor attack on text-to-image diffusion models and propose BadT2I, a general multimodal backdoor attack framework that tampers with image synthesis in diverse semantic levels.
NCL: Textual Backdoor Defense Using Noise-augmented Contrastive Learning
At present, backdoor attacks attract attention as they do great harm to deep learning models.
Apple of Sodom: Hidden Backdoors in Superior Sentence Embeddings via Contrastive Learning
This paper finds that contrastive learning can produce superior sentence embeddings for pre-trained models but is also vulnerable to backdoor attacks.
Kallima: A Clean-label Framework for Textual Backdoor Attacks
Although Deep Neural Network (DNN) has led to unprecedented progress in various natural language processing (NLP) tasks, research shows that deep models are extremely vulnerable to backdoor attacks.
BadNL: Backdoor Attacks against NLP Models with Semantic-preserving Improvements
In this paper, we perform a systematic investigation of backdoor attack on NLP models, and propose BadNL, a general NLP backdoor attack framework including novel attack methods.
KASR: A Reliable and Practical Approach to Attack Surface Reduction of Commodity OS Kernels
In this paper, we propose a reliable and practical system, named KASR, which transparently reduces attack surfaces of commodity OS kernels at runtime without requiring their source code.
Cryptography and Security Operating Systems
