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A survey on intelligent Internet of Things: Applications, security, privacy, and future directions
The rapid advances in the Internet of Things (IoT) have promoted a revolution in
communication technology and offered various customer services. Artificial intelligence (AI) …
communication technology and offered various customer services. Artificial intelligence (AI) …
A survey on differential privacy for unstructured data content
Huge amounts of unstructured data including image, video, audio, and text are ubiquitously
generated and shared, and it is a challenge to protect sensitive personal information in …
generated and shared, and it is a challenge to protect sensitive personal information in …
Sigma: Secure gpt inference with function secret sharing
Abstract Secure 2-party computation (2PC) enables secure inference that offers protection
for both proprietary machine learning (ML) models and sensitive inputs to them. However …
for both proprietary machine learning (ML) models and sensitive inputs to them. However …
Piranha: A {GPU} platform for secure computation
Secure multi-party computation (MPC) is an essential tool for privacy-preserving machine
learning (ML). However, secure training of large-scale ML models currently requires a …
learning (ML). However, secure training of large-scale ML models currently requires a …
Orca: FSS-based secure training and inference with GPUs
Secure Two-party Computation (2PC) allows two parties to compute any function on their
private inputs without revealing their inputs to each other. In the offline/on-line model for …
private inputs without revealing their inputs to each other. In the offline/on-line model for …
Honeycomb: Secure and efficient {GPU} executions via static validation
Graphics Processing Units (GPUs) unlock emerging use cases like large language models
and autonomous driving. They process a large amount of sensitive data, where security is of …
and autonomous driving. They process a large amount of sensitive data, where security is of …
Gemel: Model merging for {Memory-Efficient},{Real-Time} video analytics at the edge
Video analytics pipelines have steadily shifted to edge deployments to reduce bandwidth
overheads and privacy violations, but in doing so, face an ever-growing resource tension …
overheads and privacy violations, but in doing so, face an ever-growing resource tension …
Securely outsourcing neural network inference to the cloud with lightweight techniques
Neural network (NN) inference services enrich many applications, like image classification,
object recognition, facial verification, and more. These NN inference services are …
object recognition, facial verification, and more. These NN inference services are …
" Get in Researchers; We're Measuring Reproducibility": A Reproducibility Study of Machine Learning Papers in Tier 1 Security Conferences
Reproducibility is crucial to the advancement of science; it strengthens confidence in
seemingly contradictory results and expands the boundaries of known discoveries …
seemingly contradictory results and expands the boundaries of known discoveries …
PECAM: Privacy-enhanced video streaming and analytics via securely-reversible transformation
As Video Streaming and Analytics (VSA) systems become increasingly popular, serious
privacy concerns have risen on exposing too much unnecessary private information to the …
privacy concerns have risen on exposing too much unnecessary private information to the …