STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
Integer and combinatorial optimization
Integer and combinatorial optimization
On the value of information in distributed decision-making (extended abstract)
PODC '91 Proceedings of the tenth annual ACM symposium on Principles of distributed computing
Linear programming without the matrix
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Secure Distributed Constraint Satisfaction: Reaching Agreement without Revealing Private Information
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
An asynchronous complete method for distributed constraint optimization
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Distributed breakout algorithm for distributed constraint optimization problems -- DBArelax
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Privacy-Preserving Cooperative Scientific Computations
CSFW '01 Proceedings of the 14th IEEE workshop on Computer Security Foundations
A study of several specific secure two-party computation problems
A study of several specific secure two-party computation problems
Foundations of Cryptography: Volume 2, Basic Applications
Foundations of Cryptography: Volume 2, Basic Applications
Solving Distributed Constraint Optimization Problems Using Cooperative Mediation
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
The Effect of Policies for Selecting the Solution of a DisCSP on Privacy Loss
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
Distributed Constraint Satisfaction and Optimization with Privacy Enforcement
IAT '04 Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
Introduction to Information Technology
Introduction to Information Technology
A genetic algorithm for privacy preserving combinatorial optimization
Proceedings of the 9th annual conference on Genetic and evolutionary computation
How to generate and exchange secrets
SFCS '86 Proceedings of the 27th Annual Symposium on Foundations of Computer Science
SFCS '94 Proceedings of the 35th Annual Symposium on Foundations of Computer Science
An Approach to Securely Identifying Beneficial Collaboration in Decentralized Logistics Systems
Manufacturing & Service Operations Management
Privacy-preserving linear programming
Proceedings of the 2009 ACM symposium on Applied Computing
A Secure Revised Simplex Algorithm for Privacy-Preserving Linear Programming
AINA '09 Proceedings of the 2009 International Conference on Advanced Information Networking and Applications
Superstabilizing, fault-containing distributed combinatorial optimization
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
A scalable method for multiagent constraint optimization
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Hiccups on the road to privacy-preserving linear programming
Proceedings of the 8th ACM workshop on Privacy in the electronic society
Secure multiparty linear programming using fixed-point arithmetic
ESORICS'10 Proceedings of the 15th European conference on Research in computer security
Efficient distributed linear programming with limited disclosure
DBSec'11 Proceedings of the 25th annual IFIP WG 11.3 conference on Data and applications security and privacy
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In today's networked world, resource providers and consumers are distributed globally and locally, especially under current cloud computing environment. However, with resource constraints, optimization is necessary to ensure the best possible usage of such scarce resources. Distributed linear programming DisLP problems allow collaborative agents to jointly maximize profits or minimize costs with a linear objective function while conforming to several shared as well as local linear constraints. Since each agent's share of the global constraints and the local constraints generally refer to its private limitations or capacities, serious privacy problems may arise if such information is revealed. While there have been some solutions raised that allow secure computation of such problems, they typically rely on inefficient protocols with enormous computation and communication cost.In this paper, we study the DisLP problems where constraints are arbitrarily partitioned and every agent privately holds a set of variables, and propose secure and extremely efficient approach based on mathematical transformation in two adversary models --semi-honest and malicious model. Specifically, we first present a secure column generation SCG protocol that securely solves the above DisLP problem amongst two or more agents without any private information disclosure, assuming semi-honest behavior all agents properly follow the protocol but may be curious to derive private information from other agents. Furthermore, we discuss potential selfish actions and colluding issues in malicious model distributed agents may corrupt the protocol to gain extra benefit and propose an incentive compatible protocol to resolve such malicious behavior. To address the effectiveness of our protocols, we present security analysis for both adversary models as well as the communication/computation cost analysis. Finally, our experimental results validate the efficiency of our approach and demonstrate its scalability.