TY - GEN
T1 - Cryptographic Techniques for Data Processing
AU - Sharma, Shantanu
AU - Mehrotra, Sharad
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022/1/8
Y1 - 2022/1/8
N2 - This tutorial focuses on two principal lines of research aimed to provide secure data processing cloud-based data outsourcing - encryption and secret-sharing-based approaches that have been developed over the last two decades. The tutorial compares these techniques based on efficiency and information leakage. We discuss that existing cryptographic techniques are not sufficient alone to achieve the goal of efficient as well as secure data processing. To overcome the limitation of efficient and secure data processing, a new line of work that combines software and hardware mechanisms is required. We discuss an orthogonal approach designed around the concept of data partitioning, i.e., splitting the data processing into cryptographically secure and non-secure parts. Finally, we will discuss some open questions in designing secure cryptographic techniques that can process large-sized data efficiently.
AB - This tutorial focuses on two principal lines of research aimed to provide secure data processing cloud-based data outsourcing - encryption and secret-sharing-based approaches that have been developed over the last two decades. The tutorial compares these techniques based on efficiency and information leakage. We discuss that existing cryptographic techniques are not sufficient alone to achieve the goal of efficient as well as secure data processing. To overcome the limitation of efficient and secure data processing, a new line of work that combines software and hardware mechanisms is required. We discuss an orthogonal approach designed around the concept of data partitioning, i.e., splitting the data processing into cryptographically secure and non-secure parts. Finally, we will discuss some open questions in designing secure cryptographic techniques that can process large-sized data efficiently.
UR - http://www.scopus.com/inward/record.url?scp=85122702001&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85122702001&partnerID=8YFLogxK
U2 - 10.1145/3493700.3493771
DO - 10.1145/3493700.3493771
M3 - Conference contribution
AN - SCOPUS:85122702001
T3 - ACM International Conference Proceeding Series
SP - 344
EP - 347
BT - CODS-COMAD 2022 - Proceedings of the 5th Joint International Conference on Data Science and Management of Data (9th ACM IKDD CODS and 27th COMAD)
PB - Association for Computing Machinery
T2 - 5th ACM India Joint 9th ACM IKDD Conference on Data Science and 27th International Conference on Management of Data, CODS-COMAD 2022
Y2 - 7 January 2022 through 10 January 2022
ER -