Research

CtxPipe: Context-aware Data Preparation Pipeline Construction for Machine Learning

Machine learning models are only as good as their training data. Simple models trained on well-chosen features extracted from the raw data often outperform complex models trained directly on the raw data. Data preparation pipelines, which clean and derive features from the data, are...

Characterizing the Performance and Cost of Blockchains on the Cloud and at the Edge

While state-of-the-art permissioned blockchains can achieve thousands of transactions per second on commodity hardware with x86/64 architecture, their performance when running on different architectures, such as ARM, is not clear. The goal of this work is to characterize the performance and cost of permissioned blockchains on different hardware systems, which is important as diverse application domains are adopting blockchains....

A Systematic Review of Fast, Scalable, and Efficient Hardware Implementations of Elliptic Curve Cryptography for Blockchain

Blockchain technology entered the enterprise domain under the name of permissioned blockchains and hybrid or verifiable database systems, as they provide a distributed solution that allows multiple distrusting parties to share common information. One drawback of these systems is the ...

Applications and Challenges for Large Language Models: From Data Management Perspective

Data management is indispensable for informed decision-making in the big data era. In the meantime, Large Language Models (LLMs), equipped with billions of model parameters and trained on extensive data corpora, have recently achieved record-breaking results in various real-world applications, such as machine translation, content generation, information retrieval, etc....

FC: Adaptive Atomic Commit via Failure Detection

Atomic commit protocols (ACPs) are crucial for ensuring transaction atomicity in distributed transaction processing. However, existing ACPs, designed specifically for fixed failure conditions, cannot work efficiently in modern environments, where failures such as node crashes and connection delays can happen anytime due to the use of commodity nodes and networks....

LBSC: A Cost-Aware Caching Framework for Cloud Databases

Caching is a crucial solution to alleviate the high latency and low bandwidth of cloud databases. However, existing caching algorithms are not suitable for cloud databases as 1) they cannot ensure the adaptability to changing workloads; 2) they are not designed with awareness of data fetching costs....

Characterizing the Performance and Cost of Blockchains on the Cloud and at the Edge

While state-of-the-art permissioned blockchains can achieve thousands of transactions per second on commodity hardware with x86/64 architecture, their performance when running on different architectures, such as ARM, is not clear. The goal of this work is to characterize the performance and cost of permissioned blockchains on different...

Secure and Verifiable Data Collaboration with Low-Cost Zero Knowledge Proofs

Organizations are increasingly recognizing the value of data collaboration for data analytics purposes. Yet, stringent data protection laws prohibit the direct exchange of raw data. To facilitate data collaboration, federated Learning (FL) emerges as a viable solution, which enables multiple clients to collaboratively train a machine learning (ML) model under ...

Are ARM Cloud Servers Ready for Database Workloads? an Experimental Study

Almost all major cloud providers offer virtual machines running on servers with 64-bit ARM CPUs. For example, Amazon Web Services (AWS) designed custom ARM-based CPUs named Graviton2 and Graviton3. Other cloud providers, such as Microsoft Azure and Google Cloud Platform (GCP), employ servers with...

Toward Intention Discovery for Early Malice Detection in Cryptocurrency

Cryptocurrency's pseudo-anonymous nature makes it vulnerable to malicious activities. However, existing deep learning solutions lack interpretability and only support retrospective analysis of specific malice types. To address these challenges, we propose Intention-Monitor for early malice detection in Bitcoin....

Managing Metaverse Data Tsunami: Actionable Insights

In the metaverse the physical space and the virtual space co-exist, and interact simultaneously. While the physical space is virtually enhanced with information, the virtual space is continuously refreshed with real-time, real-world information. To allow users to process and manipulate information seamlessly between...

From Asset Flow to Status, Action and Intention Discovery: Early Malice Detection in Cryptocurrency

Cryptocurrency has been subject to illicit activities probably more often than traditional financial assets due to the pseudo-anonymous nature of its transacting entities. An ideal detection model is expected to achieve all three critical properties of early detection, good interpretability, and versatility for...

METER: A Dynamic Concept Adaptation Framework for Online Anomaly Detection

Real-time analytics and decision-making require online anomaly detection (OAD) to handle drifts in data streams efficiently and effectively. Unfortunately, existing approaches are often constrained by their limited detection capacity and slow adaptation to evolving data streams, inhibiting their efficacy and efficiency in handling concept drift, which is...

Evolve Path Tracer: Early Detection of Malicious Addresses in Cryptocurrency

With the boom of cryptocurrency and its concomitant financial risk concerns, detecting fraudulent behaviors and associated malicious addresses has been drawing significant research effort. Most existing studies, however, rely on the full history features or full-fledged address transaction networks, both of which are unavailable in the...

MINT: Detecting Fraudulent Behaviors from Time-Series Relational Data

The e-commerce platforms, such as Shopee, have accumulated a huge volume of time-series relational data, which contains useful information on differentiating fraud users from benign users. Existing fraud behavior detection approaches typically model the time-series data with a vanilla Recurrent Neural Network (RNN) or combine the...

Baldur: A Hybrid Blockchain Database with FPGA or GPU Acceleration

In the last decade, blockchain technologies have entered the enterprise space in the form of permissioned blockchains, verifiable databases, and hybrid blockchain database systems (HBDB). The core of these blockchain technologies is represented by cryptography operations such as secure hashing typically with SHA-3 algorithms...

BBSF: Blockchain Benchmarking Standardized Framework

In this paper, we propose the Blockchain Benchmark Standardized Format (BBSF), a framework for standardized, transparent, and fair benchmarks for blockchains. BBSF enables users and developers to compare blockchain platforms using metrics derived from realistic workloads....

VeDB: A Software and Hardware Enabled Trusted Relational Database

Blockchain-like ledger databases emerge in recent years as a more efficient alternative to permissioned blockchains. Conventional ledger databases mostly rely on authenticated structures such as the Merkle tree and transparency logs for supporting auditability, and hence they suffer from the performance problem....

Enabling Secure and Efficient Data Analytics Pipeline Evolution with Trusted Execution Environment

Modern data analytics pipelines are highly dynamic, as they are constantly monitored and fine-tuned by both data engineers and scientists. Recent systems managing pipelines ease creating, deploying, and tracking their evolution. ...

FEAST: A Communication-efficient Federated Feature Selection Framework for Relational Data

Vertical federated learning (VFL) is an emerging paradigm for cross-silo organizations to build more accurate machine learning (ML) models. In this setting, multiple organizations (i.e., parties) hold the same set of samples with different features....

Robust and Transferable Log-based Anomaly Detection

Anomalies or failures in large computer systems, such as the cloud, have an impact on a large number of users that communicate, compute, and store information. Therefore, timely and accurate anomaly detection is necessary for reliability, security, safe operation, and mitigation of losses in these increasingly important systems...

Interoperability in Blockchain: A Survey

This paper presents a systematic and comprehensive survey on blockchain interoperability, where interoperability is defined as the ability of blockchains to flexibly transfer assets, share data, and invoke smart contracts across a mix of public, private, and consortium blockchains without any changes to the underlying blockchain systems. ...

VeriBench: Analyzing the Performance of Database Systems with Verifiability

Database systems are paying more attention to data security in recent years. Immutable systems such as blockchains, verifiable databases, and ledger databases are equipped with various verifiability mechanisms to protect data....

GlassDB: An Efficient Verifiable Ledger Database System Through Transparency

Verifiable ledger databases protect data history against malicious tampering. Existing systems, such as blockchains and certificate transparency, are based on transparency logs --- a simple abstraction allowing users to verify that a log maintained by an untrusted server is append-only. ...

ARENA: Enhancing Abstract Refinement for Neural Network Verification

As neural networks have taken on a critical role in real-world applications, formal verification is earnestly needed to guarantee the safety properties of the networks. However, it remains challenging to balance the trade-off between precision and efficiency in abstract interpretation based verification methods. In this paper, we propose an abstract refinement process that leverages the convex hull techniques to improve the analysis efficiency....

The Metaverse Data Deluge: What Can We Do About It?

In the Metaverse, the physical space and the virtual space co-exist, and interact simultaneously. While the physical space is virtually enhanced with information, the virtual space is continuously refreshed with real-time, real-world information. To allow users to process and manipulate information seamlessly between the real and digital spaces, novel technologies must be developed. ...

LedgerView: Access-Control Views on Hyperledger Fabric

We present LedgerView -- a system that adds access control views to permissioned blockchains. The approach is motivated by an AT&T application of tracking refurbished devices. A blockchain is a decentralized tamper-resistant ledger managed by a group of peers....

Hybrid Blockchain Database Systems: Design and Performance

With the emergence of hybrid blockchain database systems, we aim to provide an in-depth analysis of the performance and trade-offs among a few representative systems. To achieve this goal, we implement Veritas and BlockchainDB from scratch....

Blockchains vs. Distributed Databases: Dichotomy and Fusion

Blockchain has come a long way - a system that was initially proposed specifically for cryptocurrencies is now being adapted and adopted as a general-purpose transactional system. As blockchain evolves into another data management system...

Automated Repair of Heap-Manipulating Programs Using Deductive Synthesis

We propose a novel method to automatically repairing buggy heap-manipulating programs using constraint solving and deductive synthesis. Given an input program C and its formal specification in the form of a Hoare triple: {P}C{Q} , we use a separation-logic-based verifier to verify if program C is correct w.r.t. its specifications. If program C is found buggy, we then repair it in the following steps....

Blockchains: Decentralized and Verifiable Data Systems

This book takes readers through the sensational history of blockchains and their potential to revolutionize database systems of the future. In order to demystify blockchains, the book capitalizes on decades of research and field testing of existing database and distributed systems and applies these familiar concepts to the novel blockchain system.

The Anatomy of Blockchain Database Systems

In a traditional enterprise information system, the database is the final source of truth. The data in the database are closely guarded by access controls and integrity checking. Privacy regulations often apply to the use of data (examples include the U.S. HIPPA and FERPA regulations for health and education records respectively).