TY - JOUR
T1 - Profile Aware ObScure Logging (PaOSLo)
T2 - a web search privacy-preserving protocol to mitigate digital traces
AU - Ullah, Mohib
AU - Khan, Rafi Ullah
AU - Khan, Irfan Ullah
AU - Aslam, Nida
AU - Aljameel, Sumayh S.
AU - Ul Haq, Muhammad Inam
AU - Islam, Muhammad Arshad
N1 - Copyright the Author(s) 2022. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.
PY - 2022
Y1 - 2022
N2 - Web search querying is an inevitable activity of any Internet user. The web search engine (WSE) is the easiest way to search and retrieve data from the Internet. The WSE stores the user's search queries to retrieve the personalized search result in a form of query log. A user often leaves digital traces and sensitive information in the query log. WSE is known to sell the query log to a third party to generate revenue. However, the release of the query log can compromise the security and privacy of a user. In this work, we propose a Profile Aware ObScure Logging (PaOSLo) Web search privacy-preserving protocol that mitigates the digital traces a user leaves in Web searching. PaOSLo systematically groups users based on profile similarity. The primary objective of this work is to evaluate the impact of the systematic group compared to random grouping. We first computed the similarity between the users' profiles and then clustered them using the K-mean algorithm to group the users systematically. Unlikability and indistinguishability are the two dimensions in which we have measured the privacy of a user. To compute the impact of systematic grouping on a user's privacy, we have experimented with and compared the performance of PaOSLo with modern distributed protocols like OSLo and UUP(e). Results show that, at the top degree of the ODP hierarchy, PaOSLo preserved 10% and 3% better profile privacy than the modern distributed protocols mentioned above. In addition, the PaOSLo has less profile exposure for any group size and at each degree of the ODP hierarchy.
AB - Web search querying is an inevitable activity of any Internet user. The web search engine (WSE) is the easiest way to search and retrieve data from the Internet. The WSE stores the user's search queries to retrieve the personalized search result in a form of query log. A user often leaves digital traces and sensitive information in the query log. WSE is known to sell the query log to a third party to generate revenue. However, the release of the query log can compromise the security and privacy of a user. In this work, we propose a Profile Aware ObScure Logging (PaOSLo) Web search privacy-preserving protocol that mitigates the digital traces a user leaves in Web searching. PaOSLo systematically groups users based on profile similarity. The primary objective of this work is to evaluate the impact of the systematic group compared to random grouping. We first computed the similarity between the users' profiles and then clustered them using the K-mean algorithm to group the users systematically. Unlikability and indistinguishability are the two dimensions in which we have measured the privacy of a user. To compute the impact of systematic grouping on a user's privacy, we have experimented with and compared the performance of PaOSLo with modern distributed protocols like OSLo and UUP(e). Results show that, at the top degree of the ODP hierarchy, PaOSLo preserved 10% and 3% better profile privacy than the modern distributed protocols mentioned above. In addition, the PaOSLo has less profile exposure for any group size and at each degree of the ODP hierarchy.
UR - http://www.scopus.com/inward/record.url?scp=85139801459&partnerID=8YFLogxK
U2 - 10.1155/2022/2109024
DO - 10.1155/2022/2109024
M3 - Article
SN - 1939-0114
VL - 2022
SP - 1
EP - 13
JO - Security and Communication Networks
JF - Security and Communication Networks
M1 - 2109024
ER -