Cong Wang

Uncertain Data Stream Classification with Concept Drift

2016

In big data era, the data on the Internet is growing at an exponential rate. The uncertainty of data due to privacy protection, data loss, network errors and so on is very common. In data …

Tutorial: Building Secure and Trustworthy Blockchain Applications

2018

Beyond cryptocurrencies, blockchain technologies have shown great potential in enabling a wealth of decentralized applications (DApps), including but not limited to trustworthy auction, election, autonomous organization. While public blockchains are well recognized to allow participants …

Optimize Scheduling of Federated Learning on Battery-powered Mobile Devices

2020

Federated learning learns a collaborative model by aggregating locally-computed updates from mobile devices for privacy preservation. While current research typically prioritizing the minimization of communication overhead, we demonstrate from an empirical study, that computation heterogeneity …

Can Differential Privacy Practically Protect Collaborative Deep Learning Inference for the Internet of Things?

2021 · arXiv (Cornell University)

Collaborative inference has recently emerged as an attractive framework for applying deep learning to Internet of Things (IoT) applications by splitting a DNN model into several subpart models among resource-constrained IoT devices and the cloud. …

Aggregation Service for Federated Learning: An Efficient, Secure, and More Resilient Realization

2022 · IEEE Transactions on Dependable and Secure Computing

Federated learning has recently emerged as a paradigm promising the benefits of harnessing rich data from diverse sources to train high quality models, with the salient features that training datasets never leave local devices. Only …

Hijacking Attacks against Neural Networks by Analyzing Training Data

2024 · arXiv (Cornell University)

Backdoors and adversarial examples are the two primary threats currently faced by deep neural networks (DNNs). Both attacks attempt to hijack the model behaviors with unintended outputs by introducing (small) perturbations to the inputs. Backdoor …

Blockchain Adoption or Not? Analysis of Demand Information Sharing in Maritime Supply Chain

2025 · Information

This study examines whether adopting blockchain technology can enhance maritime supply chain performance by improving information sharing in the presence of mismatches between service capacity and demand. We analyze a maritime supply chain with one …

Binary Neural Networks for Large Language Model: A Survey

2025 · arXiv (Cornell University)

Large language models (LLMs) have wide applications in the field of natural language processing(NLP), such as GPT-4 and Llama. However, with the exponential growth of model parameter sizes, LLMs bring significant resource overheads. Low-bit quantization, …