Privacy in the age of big data

Author

Cheatham, Michelle

Author_Institution

Data Semantics Lab., Wright State Univ., Dayton, OH, USA

fYear

2015

Firstpage

334

Lastpage

335

Abstract

Lately it seems that every month brings with it a new privacy breach. This can happen due to attackers breaking into a supposedly secure database, such as in the recent cases of Target, Home Depot, and the United States Postal Service, or because data has been released publicly after it has (purportedly) been anonymized. One of the most famous examples of this latter type of privacy compromise is the case of the Netflix Challenge, in which Netflix offered a million dollars to any individual or team who could use an anonymized dataset containing movies and ratings to improve the company´s recommendation system by ten percent or more. Just days after the contest began, the anonymization algorithm was broken and the viewing habits of many individuals within the dataset were revealed [1].

Keywords

Big Data; data privacy; recommender systems; Big Data; Netflix Challenge anonymization; anonymization algorithm; attackers; company recommendation system; data privacy; privacy breach; secure database; Algorithm design and analysis; Cancer; Data integration; Data privacy; Measurement; Motion pictures; Semantics;

fLanguage

English

Publisher

ieee

Conference_Titel

Collaboration Technologies and Systems (CTS), 2015 International Conference on

Conference_Location

Atlanta, GA

Print_ISBN

978-1-4673-7647-1

Type

conf

DOI

10.1109/CTS.2015.7210444

Filename

7210444