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How To Cook The Fragmented Rug Pull?
Minh Trung Tran, Nasrin Sohrabi, Zahir Tari +1
Existing rug pull detectors assume a simple workflow: the deployer keeps liquidity pool (LP) tokens and performs one or a few large sells (within a day) that collapse the pool and…
Proof-Carrying Fair Ordering: Asymmetric Verification for BFT via Incremental Graphs
Pengkun Ren, Hai Dong, Nasrin Sohrabi +2
Byzantine Fault-Tolerant (BFT) consensus protocols ensure agreement on transaction ordering despite malicious actors, but unconstrained ordering power enables sophisticated value e…
FedLAD: A Linear Algebra Based Data Poisoning Defence for Federated Learning
Qi Xiong, Hai Dong, Nasrin Sohrabi +1
Sybil attacks pose a significant threat to federated learning, as malicious nodes can collaborate and gain a majority, thereby overwhelming the system. Therefore, it is essential t…
Univariate to Multivariate: LLMs as Zero-Shot Predictors for Time-Series Forecasting
Chamara Madarasingha, Nasrin Sohrabi, Zahir Tari
Time-series prediction or forecasting is critical across many real-world dynamic systems, and recent studies have proposed using Large Language Models (LLMs) for this task due to t…
Slow is Fast! Dissecting Ethereum's Slow Liquidity Drain Scams
Minh Trung Tran, Nasrin Sohrabi, Zahir Tari +3
We identify the slow liquidity drain (SLID) scam, an insidious and highly profitable threat to decentralized finance (DeFi), posing a large-scale, persistent, and growing risk to t…