| 1. |
- Chen, Weili, et al.
(författare)
-
Detecting Ponzi Schemes on Ethereum : Towards Healthier Blockchain Technology
- 2018
-
Ingår i: WWW '18. - New York, New York, USA : ACM Digital Library. - 9781450356398 ; , s. 1409-1418
-
Konferensbidrag (refereegranskat)abstract
- Blockchain technology becomes increasingly popular. It also attracts scams, for example, Ponzi scheme, a classic fraud, has been found making a notable amount of money on Blockchain, which has a very negative impact. To help dealing with this issue, this paper proposes an approach to detect Ponzi schemes on blockchain by using data mining and machine learning methods. By verifying smart contracts on Ethereum, we first extract features from user accounts and operation codes of the smart contracts and then build a classification model to detect latent Ponzi schemes implemented as smart contracts. The experimental results show that the proposed approach can achieve high accuracy for practical use. More importantly, the approach can be used to detect Ponzi schemes even at the moment of its creation. By using the proposed approach, we estimate that there are more than 400 Ponzi schemes running on Ethereum. Based on these results, we propose to build a uniform platform to evaluate and monitor every created smart contract for early warning of scams.
|
|
| 2. |
- Hartig, Olaf, et al.
(författare)
-
Semantics and Complexity of GraphQL
- 2018
-
Ingår i: WEB CONFERENCE 2018: PROCEEDINGS OF THE WORLD WIDE WEB CONFERENCE (WWW2018). - New York, New York, USA : ASSOC COMPUTING MACHINERY. - 9781450356398 ; , s. 1155-1164
-
Konferensbidrag (refereegranskat)abstract
- GraphQL is a recently proposed, and increasingly adopted, conceptual framework for providing a new type of data access interface on the Web. The framework includes a new graph query language whose semantics has been specified informally only. This has prevented the formal study of the main properties of the language. We embark on the formalization and study of GraphQL. To this end, we first formalize the semantics of GraphQL queries based on a labeled-graph data model. Thereafter, we analyze the language and show that it admits really efficient evaluation methods. In particular, we prove that the complexity of the GraphQL evaluation problem is NL-complete. Moreover, we show that the enumeration problem can be solved with constant delay. This implies that a server can answer a GraphQL query and send the response byte-by-byte while spending just a constant amount of time between every byte sent. Despite these positive results, we prove that the size of a GraphQL response might be prohibitively large for an internet scenario. We present experiments showing that current practical implementations suffer from this issue. We provide a solution to cope with this problem by showing that the total size of a GraphQL response can be computed in polynomial time. Our results on polynomial-time size computation plus the constant-delay enumeration can help developers to provide more robust GraphQL interfaces on the Web.
|
|
