5 research outputs found
An Empirical Study of AI-based Smart Contract Creation
The introduction of large language models (LLMs) like ChatGPT and Google
Palm2 for smart contract generation seems to be the first well-established
instance of an AI pair programmer. LLMs have access to a large number of
open-source smart contracts, enabling them to utilize more extensive code in
Solidity than other code generation tools. Although the initial and informal
assessments of LLMs for smart contract generation are promising, a systematic
evaluation is needed to explore the limits and benefits of these models. The
main objective of this study is to assess the quality of generated code
provided by LLMs for smart contracts. We also aim to evaluate the impact of the
quality and variety of input parameters fed to LLMs. To achieve this aim, we
created an experimental setup for evaluating the generated code in terms of
validity, correctness, and efficiency. Our study finds crucial evidence of
security bugs getting introduced in the generated smart contracts as well as
the overall quality and correctness of the code getting impacted. However, we
also identified the areas where it can be improved. The paper also proposes
several potential research directions to improve the process, quality and
safety of generated smart contract codes.Comment: Updated to address issue
On Conditional Cryptocurrency With Privacy
In this paper, we present the design and imple-mentation of a conditional cryptocurrency system with privacy protection. Unlike the existing approaches that often depend on smart contracts where cryptocurrencies are first locked in a vault, and then released according to event triggers, the conditional cryptocurrency system encodes event outcome as part of a cryptocurrency note in a UTXO based system. Without relying on any triggering mechanism, the proposed system separates event processing from conditional coin transaction processing where conditional cryptocurrency notes can be transferred freely in an asynchronous manner, only with their asset values conditional to the linked event outcomes. The main advantage of such design is that it enables free trade of conditional assets and prevents assets from being locked. In this work, we demonstrate a method of confidential conditional coin by extending the Zerocoin data model and protocol. The system is implemented and evaluated using xJsnark
TPU as Cryptographic Accelerator
Polynomials defined on specific rings are heavily involved in various
cryptographic schemes, and the corresponding operations are usually the
computation bottleneck of the whole scheme.
We propose to utilize TPU, an emerging hardware designed for AI applications,
to speed up polynomial operations and convert TPU to a cryptographic
accelerator.
We also conduct preliminary evaluation and discuss the limitations of current
work and future plan
Decentralized Translator of Trust: Supporting Heterogeneous TEE for Critical Infrastructure Protection
Trusted execution environment (TEE) technology has found many applications in
mitigating various security risks in an efficient manner, which is attractive
for critical infrastructure protection. First, the natural of critical
infrastructure requires it to be well protected from various cyber attacks.
Second, performance is usually important for critical infrastructure and it
cannot afford an expensive protection mechanism. While a large number of
TEE-based critical infrastructure protection systems have been proposed to
address various security challenges (e.g., secure sensing and reliable
control), most existing works ignore one important feature, i.e., devices
comprised the critical infrastructure may be equipped with multiple
incompatible TEE technologies and belongs to different owners. This feature
makes it hard for these devices to establish mutual trust and form a unified
TEE environment. To address these challenges and fully unleash the potential of
TEE technology for critical infrastructure protection, we propose DHTee, a
decentralized coordination mechanism. DHTee uses blockchain technology to
support key TEE functions in a heterogeneous TEE environment, especially the
attestation service. A Device equipped with one TEE can interact securely with
the blockchain to verify whether another potential collaborating device
claiming to have a different TEE meets the security requirements. DHTee is also
flexible and can support new TEE schemes without affecting devices using
existing TEEs that have been supported by the system.Comment: Appeared in ACM BSCI'2
EDSC: An Event-Driven Smart Contract Platform
This paper presents EDSC, a novel smart contract platform design based on the
event-driven execution model as opposed to the traditionally employed
transaction-driven execution model. We reason that such a design is a better
fit for many emerging smart contract applications and is better positioned to
address the scalability and performance challenges plaguing the smart contract
ecosystem. We propose EDSC's design under the Ethereum framework, and the
design can be easily adapted for other existing smart contract platforms. We
have conducted implementation using Ethereum client and experiments where
performance modeling results show on average 2.2 to 4.6 times reduced total
latency of event triggered smart contracts, which demonstrates its
effectiveness for supporting contracts that demand timely execution based on
events. In addition, we discuss example use cases to demonstrate the design's
utility and comment on its potential security dynamics.Comment: 11 page