Securely outsourcing linear algebra computations

By Mikhail J. Atallah, Keith B. Frikken. ACM Asia Conference on Computer and Communications Security, 2010

317 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/28f174f66366537212e6a7b7ce00fbcaab94b882

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Srinath T. V. Setty
2. Arjun Narayan
3. Michael Walfish
4. Andrew Justin Blumberg
5. Salim el Rouayheb
6. Wenjing Lou
7. Kui Ren
8. Ariel J. Feldman

In Computational Theory and Mathematics

1. Michael Walfish
2. Srinath T. V. Setty
3. Andrew Justin Blumberg
4. Arjun Narayan
5. Xiaofeng Chen
6. Jin Li
7. Zuocheng Ren
8. Benjamin Braun

In Electrical and Electronic Engineering

1. Xinyi Huang
2. Qiang Tang
3. Kui Ren
4. Wenjing Lou
5. Jianfeng Ma
6. Parimal Parag
7. Michael Walfish
8. Xiaofeng Chen

Citations in the corpus

• Secure Outsourced Matrix Computation and Application to Neural Networks (2018, unknown): “Most of related works focus on verifiable secure outsourcing of matrix computation [4, 11, 20, 38].”
• Making argument systems for outsourced computation practical (sometimes) (2012, background): “Atallah has protocols for linear algebra (see [10] and citations therein).”
• Verifying computations with state (2013, background): “2522733 the remote hardware and use attestation [60, 63], but what if the hardware is faulty? The client could use a tailored solution [8, 13, 18, 28, 39, 58, 70, 73, 75], but such solutions are not available for all applications.”
• Securely Outsourcing Attribute-Based Encryption with Checkability (2014, background): “Atallah and Frikken [16] further studied this problem and gave improved protocols based on the so-called weak secret hiding assumption.”
• Identity-Based Encryption with Outsourced Revocation in Cloud Computing (2015, methodology): “As the result of both the practicality and utility, RDoC model recently has been widely utilized in the literature of outsourced computation [9][10][11][7][12].”
• Minimizing latency for secure distributed computing (2017, methodology): “The work that is closest to our work is the problem of distributively multiplying two private matrices under information theoretic privacy constraints in [7].”
• New Algorithms for Secure Outsourcing of Modular Exponentiations (2012, background): “Atallah and Frikken [1] further studied this problem and gave improved protocols based on the so-called weak secret hiding assumption.”
• Secure Distributed Computing With Straggling Servers Using Polynomial Codes (2019, background): “Atallah and Frikken [24] considered secure distributed matrix multiplication on confidential inputs, yet did not consider straggling effects.”
• Distributed Differential Privacy and Applications (2015, background): “However, this definition of privacy specifically ignores other settings, such as private outsourced computation (Atallah and Frikken, 2010) or transmitting private conversations (Garfinkel, 1995), where the term privacy is used in reference to hiding information from third parties entirely.”
• Secure and practical outsourcing of linear programming in cloud computing (2011, background): “protocol executions [5], or huge communication complexities [10], are involved (detailed discussions in Section VI).”