838 citations · 906 across the 27 of their papers we have counts for
29 papers
zkSAS: Practical Zero-Knowledge Proofs for Verifiable Spectrum Access Management
Nishat F. Purbasha, Ifteher Alom, Eric W. Burger +3
Dynamic Spectrum Access (DSA) through the Spectrum Access Systems (SAS) elevates spectral efficiency, yet existing centralized models face allocation logic opaqueness and a lack of…
Privacy-Preserving Split Learning for Federated LLM Fine-Tuning
Heng Jin, Chaoyu Zhang, Hexuan Yu +2
Fine-tuning large language models (LLMs) on domain-specific data is essential for downstream adaptation. In many deployments, a participant cannot hold the complete model locally.…
Skynet: Workflow-Level Anomaly Detection for Agentic AI via Semantic and Structural Modeling
Chaoyu Zhang, Hexuan Yu, Heng Jin +6
Agentic AI systems execute complex tasks through long-horizon workflows of planning, tool use, and multi-agent coordination. Task failures in these systems often originate from a s…
Enabling Emergency Communication via Semantic Radar-Centric ISAC
Mohaimin Al Barat, Chaoyu Zhang, Hexuan Yu +3
Combat aircraft and other modern military platforms field two co-located RF assets: a radar for sensing and a dedicated radio for communication. In contested battlefield environmen…
SpexPay: A Privacy-Preserving Pay-As-You-Go System for Dynamic Spectrum Sharing
Mohaimin Al Barat, Hexuan Yu, Shaoyu Li +5
Dynamic Spectrum Sharing (DSS) is a cornerstone of next-generation wireless systems, yet existing solutions such as Spectrum Access Systems (SAS) rely on centralized administrators…
From Efficiency to Leakage -- Privacy Backdoor in Federated Language Model Fine-Tuning
Shanghao Shi, Chaoyu Zhang, Heng Jin +6
Federated learning (FL) enables multiple parties to collaboratively fine-tune language models for domain-specific tasks without sharing raw data. Since full model fine-tuning is of…
Minim: Privacy-Aware Minimal View for Agents via Trusted Local Sanitization
Hexuan Yu, Chaoyu Zhang, Heng Jin +4
Modern LLM-powered autonomous agents increasingly rely on rich user interface (UI) state observations to achieve reliable action grounding in complex digital environments. However,…
Demystifying Deep Reinforcement Learning: A Neuro-Symbolic Framework for Interpretable Open RAN Automation
Jie Lu, Peihao Yan, Pang-Ning Tan +2
Open Radio Access Networks (O-RAN) are increasingly adopting data-driven control through Deep Reinforcement Learning (DRL) to optimize complex tasks such as network slicing and mob…
ARMOR 2025: A Military-Aligned Benchmark for Evaluating Large Language Model Safety Beyond Civilian Contexts
Sydney Johns, Heng Jin, Chaoyu Zhang +2
Large language models (LLMs) are now being explored for defense applications that require reliable and legally compliant decision support. They also hold significant potential to e…
ClawCoin: An Agentic AI-Native Cryptocurrency for Decentralized Agent Economies
Shaoyu Li, Chaoyu Zhang, Hexuan Yu +2
Autonomous AI agents live or die by the API tokens they consume: without paid inference capacity they cannot reason, act, or delegate. Compute-token cost has become the binding res…
Trusting What You Cannot See: Auditable Fine-Tuning and Inference for Proprietary AI
Heng Jin, Chaoyu Zhang, Hexuan Yu +4
Cloud-based infrastructure has become the dominant platform for deploying large models, particularly large language models (LLMs). Fine-tuning and inference are increasingly delega…
IU-GUARD: Privacy-Preserving Spectrum Coordination for Incumbent Users under Dynamic Spectrum Sharing
Shaoyu Li, Hexuan Yu, Shanghao Shi +4
With the growing demand for wireless spectrum, dynamic spectrum sharing (DSS) frameworks such as the Citizens Broadband Radio Service (CBRS) have emerged as practical solutions to…
FC-GUARD: Enabling Anonymous yet Compliant Fiat-to-Cryptocurrency Exchanges
Shaoyu Li, Hexuan Yu, Md Mohaimin Al Barat +3
With the rise of decentralized finance, fiat-to-cryptocurrency exchange platforms have become popular entry points into the cryptocurrency ecosystem. However, these platforms frequ…
Closing the Visibility Gap: A Monitoring Framework for Verifiable Open RAN Operations
Hexuan Yu, Md Mohaimin Al Barat, Yang Xiao +2
Open Radio Access Network (Open RAN) is reshaping mobile network architecture by promoting openness, disaggregation, and cross-vendor interoperability. However, this architectural…
Enabling Trustworthy Federated Learning via Remote Attestation for Mitigating Byzantine Threats
Chaoyu Zhang, Heng Jin, Shanghao Shi +4
Federated Learning (FL) has gained significant attention for its privacy-preserving capabilities, enabling distributed devices to collaboratively train a global model without shari…
Temporal Misalignment Attacks against Multimodal Perception in Autonomous Driving
Md Hasan Shahriar, Md Mohaimin Al Barat, Harshavardhan Sundar +4
Multimodal fusion (MMF) plays a critical role in the perception of autonomous driving, which primarily fuses camera and LiDAR streams for a comprehensive and efficient scene unders…
Cyrus+: A DRL-based Puncturing Solution to URLLC/eMBB Multiplexing in O-RAN
Ehsan Ghoreishi, Bahman Abolhassani, Yan Huang +3
Puncturing is a promising technique in 3GPP to multiplex Enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low Latency Communications (URLLC) traffic on the same 5G New Radio (NR…
StarCast: A Secure and Spectrum-Efficient Group Communication Scheme for LEO Satellite Networks
Chaoyu Zhang, Hexuan Yu, Shanghao Shi +5
Low Earth Orbit (LEO) satellite networks serve as a cornerstone infrastructure for providing ubiquitous connectivity in areas where terrestrial infrastructure is unavailable. With…
BoBa: Boosting Backdoor Detection through Data Distribution Inference in Federated Learning
Zhengyuan Jiang, Xingyu Lyu, Shanghao Shi +5
Federated learning, while being a promising approach for collaborative model training, is susceptible to backdoor attacks due to its decentralized nature. Backdoor attacks have sho…
Let the Noise Speak: Harnessing Noise for a Unified Defense Against Adversarial and Backdoor Attacks
Md Hasan Shahriar, Ning Wang, Naren Ramakrishnan +2
The exponential adoption of machine learning (ML) is propelling the world into a future of distributed and intelligent automation and data-driven solutions. However, the proliferat…
SoK: Public Blockchain Sharding
Md Mohaimin Al Barat, Shaoyu Li, Changlai Du +2
Blockchain's decentralization, transparency, and tamper-resistance properties have facilitated the system's use in various application fields. However, the low throughput and high…
ProFLingo: A Fingerprinting-based Intellectual Property Protection Scheme for Large Language Models
Heng Jin, Chaoyu Zhang, Shanghao Shi +2
Large language models (LLMs) have attracted significant attention in recent years. Due to their "Large" nature, training LLMs from scratch consumes immense computational resources.…
Learning-augmented Online Minimization of Age of Information and Transmission Costs
Zhongdong Liu, Keyuan Zhang, Bin Li +3
We consider a discrete-time system where a resource-constrained source (e.g., a small sensor) transmits its time-sensitive data to a destination over a time-varying wireless channe…
AoI-minimizing Scheduling in UAV-relayed IoT Networks
Biplav Choudhury, Vijay K. Shah, Aidin Ferdowsi +2
Due to flexibility, autonomy and low operational cost, unmanned aerial vehicles (UAVs), as fixed aerial base stations, are increasingly being used as \textit{relays} to collect tim…