Privacy-preserving targeted advertising scheme for IPTV using the cloud

Official URL: http://192.168.1.20/record=b1416990 (Table of Contents)

Targeted advertising is an emerging business area that provides effective services for advertisers and end users. Advertising agencies need information about users to send them targeted advertisements. However, uncontrolled access to users' sensitive information for advertising purposes violates the privacy of individuals. Therefore, efficient techniques must be used to not only preserve users privacy but also enable advertisers to reach right users. In this thesis, we present a privacy-preserving scheme for targeted advertising via the Internet Protocol TV (IPTV). The scheme uses a communication model involving a collection of viewers/subscribers, a content provider (IPTV), an advertiser, and a cloud server. To provide high quality directed advertising service, the advertiser can utilize not only demographic information of subscribers, but also their watching habits. The latter includes watching history, preferences for IPTV content and watching time, which are published on the cloud server periodically along with anonymized demographics (e.g. weekly). Since the published data may leak sensitive information about subscribers, it is safeguarded using cryptographic techniques in addition to the anonymization of demographics. The techniques used by the advertiser, which can be manifested in its queries to the cloud, are considered (trade) secrets and therefore are protected as well. The cloud is oblivious to the published data, the queries of the advertiser as well as its own responses to these queries. Only a legitimate advertiser, endorsed with a so-called trapdoor by the IPTV, can query the cloud and utilize the query results. The performance of the proposed scheme is evaluated with experiments, which show that the scheme is suitable for practical usage.