Mitigating stealthy collision attack in energy harvesting motivated networks

Cong Pu, Sunho Lim, Byungkwan Jung, Manki Min

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

14 Scopus citations


Energy harvesting motivated networks (EHNets) are rapidly emerging as a major part of ubiquitous computing and communication infrastructure in the presence of Internet-of-Things (IoT). A set of self-sustainable nodes equipped with energy harvesting capabilities can effectively exploit ambient energy and convert it into electric energy, but it is admittedly vulnerable to a Denial-of-Service (DoS) attack that primarily targets service availability, often witnessed in wireless multi-hop networks. In this paper, we propose an adaptive acknowledgment-based approach, called AAA, to detect the stealthy collision attack caused by multiple malicious nodes in the realm of EHNets, where two malicious nodes coordinate their packet transmissions simultaneously to create the packet collision at a legitimate node. In the AAA, each node forwards a Data packet, monitors the subsequent packet transmission of its one-hop downstream node and waits for an explicit acknowledgment (Ack) packet from its two-hop downstream node, and then detects the stealthy collision attack in EHNets. We conduct extensive simulation experiments using OMNeT++ for performance evaluation and comparison. The simulation results indicate that the proposed countermeasure can provide higher detection rate and packet delivery ratio but lower detection latency compared to the existing scheme, MCC.

Original languageEnglish
Title of host publicationMILCOM 2017 - 2017 IEEE Military Communications Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781538605950
StatePublished - Dec 7 2017
Event2017 IEEE Military Communications Conference, MILCOM 2017 - Baltimore, United States
Duration: Oct 23 2017Oct 25 2017

Publication series

NameProceedings - IEEE Military Communications Conference MILCOM


Conference2017 IEEE Military Communications Conference, MILCOM 2017
Country/TerritoryUnited States


  • Acknowledgment-based detection
  • colluding collision
  • energy harvesting motivated networks


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