Title :
Privacy in the age of big data
Author :
Cheatham, Michelle
Author_Institution :
Data Semantics Lab., Wright State Univ., Dayton, OH, USA
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;
Conference_Titel :
Collaboration Technologies and Systems (CTS), 2015 International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4673-7647-1
DOI :
10.1109/CTS.2015.7210444
