SemesterFall Semester, 2017
DepartmentSocial Networks and Human-Centered Computing, First Year
Course NameMobile Social Networks
Instructor
Credit3.0
Course TypeSelectively
Prerequisite
Course Objective
Course Description
Course Schedule
Teaching Methods
Teaching Assistant

TBA


Requirement/Grading

Each student's assigned paper reading and presentation 80%



Question and Answer (Q&A) 20%


Textbook & Reference

  • Aslett, J. M., L., et al., Encrypted statistical machine learning: new privacy reserving methods. arXiv preprint arXiv:1508.06845v1, 27 Aug 2015.

  • Aslett, J. M., L., et al., A review of homomorphic encryption and software tools for encrypted statistical machine learning. arXiv preprint arXiv:1508.06574v1, 26 Aug 2015.

  • Bost, R., Machine learning classification over encrypted data. NDSS'15, Feb. 2015.

  • Ciriani, V., et al., Microdata protection. Secure Data Management in Decentralized Systems, Springer, pp. 291-322, 2007.

  • Dwork, C., A firm foundation for private data analysis. CACM, 54(1), 2011

  • Fan, J. and F. Vercauteren, Somewhat practically fully homomorphic encryption. ICAR Cryptology ePrint archive.

  • Fernades, A. B. D., et al., Security issues in cloud environments: a survey. International Journal Information Security,13, pp. 113-170, Springer, 2014.

  • Graepel, T., et al., ML confidential: machine learning on encrypted data. Informationl  Security and Cryptology ? ICISC, LNCS, Springer, 2012.

  • Ji, Z., et al., Differential privacy and machine learning: a survey and review. ArXiv preprint 

          arXiv:1412.7584v1, 24 Dec. 2014.

  • Lauter, K., et al., Can homomorphic encryption be practical? Proc. of the 3rd ACM workshop on cloud computing security, ACM, pp113-124, 2011.

  • Mohan, P., et al., GUPT: privacy preserving data analysis made easy. SIMOD'12, 2012.

  • Papernot, N., et al., SoK: towards the science of security and privacy in machine learning, arXiv preprint arXiv:1611.03814v1, 11 Nov. 2016.

  • Popa, Ad. R., et al., CryptDB: protecting confidentiality with encrypted query processing. SOSP'11, ACM, 2011.

  • Samarati, P. and S. De C. di Vimercati, Data protection in outsourcing scenarios: issues and

            directions. ASIACCS'10, 2010.

  • Samarati, P. and S. De C. di Viemrcati, Cloud security: issues and concerns. Encyclopedia  on Cloud Computing, Wiley, 2016.

  • Sarwate, D. A. and K. Chaudhuri, Signal processing and machine learning with differential privacy: 

    algorithms and challenges for continuous data. IEEE Signal Processing Magazine. Sep. 2013.

  • Vimercati, di S. De C., et al., Practical techniques building on encryption for protecting 

    and managing data in the cloud. The New Codebrakers, Vol. 9100, LNCS, Springer, 2015.


Urls about Course
Attachment

keynote17_hu_slides_.pdf