TY - GEN
T1 - Differential Privacy Protection with Group Onion Routing based on AI-based URL Classification
AU - Liu, I. Hsien
AU - Chang, Yung Lin
AU - Li, Jung Shian
AU - Liu, Chuan Gang
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/12/12
Y1 - 2020/12/12
N2 - Due to the rapid spread of tablet computers, smartphones, and other mobile information devices, wireless communication technology is fully developed and deployed widely. Mobile Internet access has been a main and important way to communicate the world in daily and it privacy protection also catches much attentions. The Onion Router, better known as Tor, is a technique for anonymous communication over internet without regional restrictions for privacy protection. Apart from this, Tor can reach sites that normal search engine cannot search. As the opinion of Tor, the transmitted data has been encrypted layer by layer, just like onion, before it reaching server. Our research proposed a system predicting URL's category with the use of machine learning technique before visiting. According to the category prediction, we represent different privacy level with three kinds of RSA key lengths on onion routing. Depending on various situations, our system can obtain the balance between security and time cost. Hence, our proposed scheme can make onion routing more flexible and efficiently.
AB - Due to the rapid spread of tablet computers, smartphones, and other mobile information devices, wireless communication technology is fully developed and deployed widely. Mobile Internet access has been a main and important way to communicate the world in daily and it privacy protection also catches much attentions. The Onion Router, better known as Tor, is a technique for anonymous communication over internet without regional restrictions for privacy protection. Apart from this, Tor can reach sites that normal search engine cannot search. As the opinion of Tor, the transmitted data has been encrypted layer by layer, just like onion, before it reaching server. Our research proposed a system predicting URL's category with the use of machine learning technique before visiting. According to the category prediction, we represent different privacy level with three kinds of RSA key lengths on onion routing. Depending on various situations, our system can obtain the balance between security and time cost. Hence, our proposed scheme can make onion routing more flexible and efficiently.
UR - http://www.scopus.com/inward/record.url?scp=85116625664&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85116625664&partnerID=8YFLogxK
U2 - 10.1145/3440943.3444717
DO - 10.1145/3440943.3444717
M3 - Conference contribution
AN - SCOPUS:85116625664
T3 - ACM International Conference Proceeding Series
BT - Proceedings of 2020 ACM International Conference on Intelligent Computing and its Emerging Applications, ICEA 2020
PB - Association for Computing Machinery
T2 - 2020 ACM International Conference on Intelligent Computing and its Emerging Applications, ICEA 2020
Y2 - 12 December 2020 through 15 December 2020
ER -