Privacy preserving error resilient dna searching through oblivious automata
Proceedings of the 14th ACM conference on Computer and communications security
Grid's confidential outsourcing of string matching
SEPADS'07 Proceedings of the 6th WSEAS International Conference on Software Engineering, Parallel and Distributed Systems
Securely outsourcing linear algebra computations
ASIACCS '10 Proceedings of the 5th ACM Symposium on Information, Computer and Communications Security
Proceedings of the 9th annual ACM workshop on Privacy in the electronic society
Secure outsourcing of DNA searching via finite automata
DBSec'10 Proceedings of the 24th annual IFIP WG 11.3 working conference on Data and applications security and privacy
Algorithms and theory of computation handbook
Sedic: privacy-aware data intensive computing on hybrid clouds
Proceedings of the 18th ACM conference on Computer and communications security
Outsourcing encryption of attribute-based encryption with mapreduce
ICICS'12 Proceedings of the 14th international conference on Information and Communications Security
Secure and verifiable outsourcing of sequence comparisons
ICT-EurAsia'13 Proceedings of the 2013 international conference on Information and Communication Technology
New methods of secure outsourcing of scientific computations
The Journal of Supercomputing
On the (Im)possibility of privately outsourcing linear programming
Proceedings of the 2013 ACM workshop on Cloud computing security workshop
Secure outsourced computation of iris matching
Journal of Computer Security
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Internet computing technologies, like grid computing, enable a weak computational device connected to such a grid to be less limited by its inadequate local computational, storage, and bandwidth resources. However, such a weak computational device (PDA, smartcard, sensor, etc.) often cannot avail itself of the abundant resources available on the network because its data are sensitive. This motivates the design of techniques for computational outsourcing in a privacy-preserving manner, i.e., without revealing to the remote agents whose computational power is being used either one’s data or the outcome of the computation. This paper investigates such secure outsourcing for widely applicable sequence comparison problems and gives an efficient protocol for a customer to securely outsource sequence comparisons to two remote agents. The local computations done by the customer are linear in the size of the sequences, and the computational cost and amount of communication done by the external agents are close to the time complexity of the best known algorithm for solving the problem on a single machine.