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09/09/2023
Low-Quality Training Data Only? A Robust Framework for Detecting Encrypted Malicious Network Traffic
Machine learning (ML) is promising in accurately detecting malicious flo...
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09/07/2023
Learning from Limited Heterogeneous Training Data: Meta-Learning for Unsupervised Zero-Day Web Attack Detection across Web Domains
Recently unsupervised machine learning based systems have been developed...
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09/03/2023
martFL: Enabling Utility-Driven Data Marketplace with a Robust and Verifiable Federated Learning Architecture
The development of machine learning models requires a large amount of tr...
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05/28/2023
LLMs Can Understand Encrypted Prompt: Towards Privacy-Computing Friendly Transformers
Prior works have attempted to build private inference frameworks for tra...
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08/21/2021
A Hard Label Black-box Adversarial Attack Against Graph Neural Networks
Graph Neural Networks (GNNs) have achieved state-of-the-art performance ...
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08/25/2019
HyperService: Interoperability and Programmability Across Heterogeneous Blockchains
Blockchain interoperability, which allows state transitions across diffe...
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03/22/2019
Managing Recurrent Virtual Network Updates in Multi-Tenant Datacenters: A System Perspective
With the advent of software-defined networking, network configuration th...
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03/19/2019
Umbrella: Enabling ISPs to Offer Readily Deployable and Privacy-Preserving DDoS Prevention Services
Defending against distributed denial of service (DDoS) attacks in the In...
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12/19/2017
Enabling Work-conserving Bandwidth Guarantees for Multi-tenant Datacenters via Dynamic Tenant-Queue Binding
Today's cloud networks are shared among many tenants. Bandwidth guarante...
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12/19/2017
