Near optimal secret sharing for information leakage maximization

Frank Yeong Sung Lin, Kuo Chung Chu, Pei Yu Chen, Guan Wei Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a mathematical programming model to describe an offense-defense scenario. In the offense problem, the objective of attackers is to compromise nodes in order to steal information. Therefore, the attackers try to recover secrets through compromising certain nodes and to maximize the information leakage as much as possible. During the attack actions, the attacker must allocate a limited budget to collect a large enough number of shares and decrypted keys through compromising certain nodes. Therefore, we advocate Lagrangean Relaxation algorithms and the proposed heuristics to find a near optimal solution. Through solutions from the perspective of the attacker, we then induce some efficient defense mechanisms for the network operators.

Original languageEnglish (US)
Title of host publicationTrends in Applied Intelligent Systems - 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2010, Proceedings
Pages189-198
Number of pages10
EditionPART 3
DOIs
StatePublished - 2010
Externally publishedYes
Event23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligence Systems, IEA/AIE 2010 - Cordoba, Spain
Duration: Jun 1 2010Jun 4 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume6098 LNAI

Other

Other23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligence Systems, IEA/AIE 2010
Country/TerritorySpain
CityCordoba
Period6/1/106/4/10

Keywords

  • Information Security
  • Lagrangean Relaxation
  • Network Planning
  • Optimization
  • Reliability
  • Resource Allocation
  • Secret Sharing
  • Survivability

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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