Intercepting a Stealthy Network

Mai Ben Adar Bessos, Amir Herzberg

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


We investigate an understudied threat: networks of stealthy routers (S-Routers), communicating across a restricted area. S-Routers use short-range, low-energy communication, detectable only by nearby devices. We examine algorithms to intercept S-Routers, using one or more mobile devices, called Interceptors. We focus on Destination-Search scenarios, in which the goal of the Interceptors is to find a (single) destination S-Router, by detecting transmissions along one or more paths from a given (single) source S-Router. We evaluate the algorithms analytically and experimentally (simulations), including against a parametric, optimized S-Routers algorithm. Our main result is an Interceptors algorithm which bounds the expected time until the destination is found to O(NB^log2(N)), where N is the number of S-Routers and B^ is the average rate of transmission.

Original languageEnglish
Title of host publicationCyber Security Cryptography and Machine Learning - Second International Symposium, CSCML 2018, Proceedings
EditorsItai Dinur, Shlomi Dolev, Sachin Lodha
PublisherSpringer Verlag
Number of pages18
ISBN (Print)9783319941462
StatePublished - 2018
Event2nd International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2018 - Beer-Sheva, Israel
Duration: 21 Jun 201822 Jun 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10879 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference2nd International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2018

Bibliographical note

Publisher Copyright:
© 2018, Springer International Publishing AG, part of Springer Nature.


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