Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Exploiting contextual information in attacking set-generalized transactions

Shao, Jianhua ORCID: and Ong, Hoang 2017. Exploiting contextual information in attacking set-generalized transactions. ACM Transactions on Internet Technology 17 (4) , 40. 10.1145/3106165

[thumbnail of TOIT_Shao_Final-1.pdf]
PDF - Accepted Post-Print Version
Download (1MB) | Preview


Transactions are records that contain a set of items about individuals. For example, items browsed by a customer when shopping online form a transaction. Today, many activities are carried out on the Internet, resulting in a large amount of transaction data being collected. Such data are often shared and analyzed to improve business and services, but they also contain private information about individuals that must be protected. Techniques have been proposed to sanitize transaction data before their release, and set-based generalization is one such method. In this article, we study how well set-based generalization can protect transactions. We propose methods to attack set-generalized transactions by exploiting contextual information that is available within the released data. Our results show that set-based generalization may not provide adequate protection for transactions, and up to 70% of the items added into the transactions during generalization to obfuscate original data can be detected by our methods with a precision over 80%.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Additional Information: Copyright is held by the owner/author(s). Publication rights licensed to ACM
Publisher: Association for Computing Machinery (ACM)
ISSN: 1533-5399
Date of First Compliant Deposit: 15 June 2017
Date of Acceptance: 1 May 2017
Last Modified: 07 Nov 2023 04:05

Actions (repository staff only)

Edit Item Edit Item


Downloads per month over past year

View more statistics