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Found 8 papers, 5 papers with code
Manipulating Transfer Learning for Property Inference
We demonstrate attacks in which an adversary can manipulate the upstream model to conduct highly effective and specific property inference attacks (AUC score $> 0. 9$), without incurring significant performance loss on the main task.
Towards Practical and Efficient Long Video Summary
Recently, video summarization (VS) techniques are widely used to alleviate huge processing pressure brought by numerous long videos.
Self-supervised Incremental Deep Graph Learning for Ethereum Phishing Scam Detection
In our model, two pretext tasks designed from spatial and temporal perspectives help us effectively learn useful node embedding from the huge amount of unlabelled transaction data.
Stealthy Backdoors as Compression Artifacts
In a backdoor attack on a machine learning model, an adversary produces a model that performs well on normal inputs but outputs targeted misclassifications on inputs containing a small trigger pattern.
LEAP: TrustZone Based Developer-Friendly TEE for Intelligent Mobile Apps
ARM TrustZone is widely deployed on commercial-off-the-shelf mobile devices for secure execution.
Cryptography and Security
A System for Efficiently Hunting for Cyber Threats in Computer Systems Using Threat Intelligence
Log-based cyber threat hunting has emerged as an important solution to counter sophisticated cyber attacks.
Enabling Efficient Cyber Threat Hunting With Cyber Threat Intelligence
Log-based cyber threat hunting has emerged as an important solution to counter sophisticated attacks.
Graph-to-Tree Neural Networks for Learning Structured Input-Output Translation with Applications to Semantic Parsing and Math Word Problem
In particular, we investigated our model for solving two problems, neural semantic parsing and math word problem.
