SecMon: end-to-end quality and security monitoring system

Tomasz Ciszkowski, Charlott Eliasson, Markus Fiedler, Zbigniew Kotulski, Radu Lupu, Wojciech Mazurczyk

Abstract


The Voice over Internet Protocol (VoIP) is becoming a more available and popular way of communication for the Internet users. This also applies to the Peer-to-Peer (P2P) systems and merging these two have already proven to be successful (e.g. Skype). Even the existing standards of VoIP provide an assurance of security and Quality of Service (QoS), however, these features are usually optional and supported by a limited number of implementations. As a result, the lack of mandatory and widely applicable QoS and security guarantee makes the contemporary VoIP systems vulnerable to attacks and network disturbances. In this paper we are facing these issues and propose the SecMon system, which simultaneously provides a lightweight security mechanism and improves quality parameters of the call. SecMon is intended specially for VoIP service over P2P networks and its main advantage is that it provides authentication, data integrity services, adaptive QoS and (D)DoS attack detection. Moreover, the SecMon approach represents a lowbandwidth consumption solution that is transparent to the users and possesses a self-organizing capability. The above-mentioned features are accomplished mainly by utilizing two information hiding techniques: digital audio watermarking and network steganography. These techniques are used to create covert channels that serve as transport channels for lightweight QoS measurement results. Furthermore, these metrics are aggregated in a reputation system that enables best route path selection in the P2P network. The reputation system helps also to mitigate (D)DoS attacks, maximize performance and increase transmission efficiency in the network.

Full Text:

PDF


DOI: http://dx.doi.org/10.2478/v10065-008-0018-0
Date of publication: 2008-01-01 00:00:00
Date of submission: 2016-04-27 11:02:52


Statistics


Total abstract view - 560
Downloads (from 2020-06-17) - PDF - 0

Indicators



Refbacks

  • There are currently no refbacks.


Copyright (c) 2015 Annales UMCS Sectio AI Informatica

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.