## Abstract

Most work in heuristic search focused on path finding problems in which the cost of a path in the state space is the sum of its edges’ weights. This paper addresses a different class of path finding problems in which the cost of a path is the product of its weights. We present reductions from different classes of multiplicative path finding problems to suitable classes of additive path finding problems. As a case study, we consider the problem of finding least and most probable paths in a Markov Chain, where path cost corresponds to the probability of traversing it. The importance of this problem is demonstrated in an anomaly detection application for cyberspace security. Three novel anomaly detection metrics for Markov Chains are presented, where computing these metrics require finding least and most probable paths. The underlying Markov Chain is dynamically changing, and so fast methods for computing least and most probable paths are needed. We propose such methods based on the proposed reductions and using heuristic search algorithms.

Original language | English |
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Title of host publication | Proceedings of the 8th Annual Symposium on Combinatorial Search, SoCS 2015 |

Editors | Levi Lelis, Roni Stern |

Publisher | AAAI press |

Pages | 70-77 |

Number of pages | 8 |

ISBN (Electronic) | 9781577357322 |

State | Published - 2015 |

Externally published | Yes |

Event | 8th Annual Symposium on Combinatorial Search, SoCS 2015 - Ein Gedi, Israel Duration: 11 Jun 2015 → 13 Jun 2015 |

### Publication series

Name | Proceedings of the 8th Annual Symposium on Combinatorial Search, SoCS 2015 |
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Volume | 2015-January |

### Conference

Conference | 8th Annual Symposium on Combinatorial Search, SoCS 2015 |
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Country/Territory | Israel |

City | Ein Gedi |

Period | 11/06/15 → 13/06/15 |

### Bibliographical note

Publisher Copyright:Copyright © 2015, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

## Keywords

- Anomaly detection
- Markov Chains
- Multiplication domain search
- Network intrusion detection
- Search space monotonicity