With the emergence of online social networks and the growing popularity of digital communication, more and more information about individuals is becoming available on the Internet. While much of this information is not sensitive, it is not uncommon for users to publish sensitive information online, especially on social networking sites. The availability of this publicly accessible and potentially sensitive data can lead to abuse and expose users to stalking and identity theft. An adversary can digitally "stalk" a victim (a Web user) and discover as much information as possible about the victim, either through direct observation of posted information or by inferring knowledge using simple inference logic.

Information retrieval and information privacy/security are two fast-growing computer science disciplines. Information retrieval provides a set of information seeking, organization, analysis, and decision-making techniques. Information privacy/security defends information from unauthorized or malicious use, disclosure, modification, attack, and destruction. The two disciplines often appear as two areas with opposite goals: one is to seek information from large amounts of materials, the other is to protect (sensitive) information from being found out. On the other hand, there are many synergies and connections between these two disciplines. For example, information retrieval researchers or practitioners often need to consider privacy or security issues in designing solutions of information processing and management, while researchers in information privacy and security often utilize information retrieval techniques when they build the adversary models to simulate how the adversary can actively seek sensitive information. However, there have been very limited efforts to connect the two important disciplines.

In addition, due to lack of mature techniques in privacy-preserving information retrieval, concerns about information privacy and security have become serious obstacles that prevent valuable user data to be used in IR research such as studies about query logs, social media, tweets, session analysis, and medical record retrieval. For instance, the recent TREC Medical Record Retrieval Tracks are halted because of the privacy issue and the TREC Microblog Tracks could not provide participants with a standard testbed of tweets for system development. The situation needs to be improved in a timely manner. All these motivate us to propose this "privacy-preserving IR" workshop in SIGIR.

In SIGIR 2014, we have organized the first privacy-preserving information retrieval workshop (PIR 2014). Last year's workshop focused on mitigating privacy threats in information retrieval by novel algorithms and tools that enable web users to better understand associated privacy risks.