Publications in Scientific Journals:

F. Iglesias Vazquez, R. Annessi, T. Zseby:
"DAT detectors: uncovering TCP/IP covert channels by descriptive analytics";
Security And Communication Networks, 9 (2016), 15; 3011 - 3029.

English abstract:
Covert channels provide means to conceal information transfer between hosts and bypass security barriers in communication networks. Hidden communication is of paramount concern for governments and companies, because it can conceal data leakage and malware communication, which are crucial building blocks used in cyber crime. We propose detectors
based on descriptive analytics of traffic (DAT) to facilitate revealing network and transport layer covert channels originated
from a wide spectrum of published data-hiding techniques. DAT detectors transform communication data into flexible feature vectors that represent traffic by a set of extracted calculations and estimations. For the case of covert channels, the core of the detection is performed by the combined application of autocorrelation calculations and multimodality measures built upon kernel density estimations and Pareto charts. DAT detectors are devised to be embedded as extensions of network intrusion detection systems, being able to perform fast, lightweight analysis of numerous flows. The present paper focuses specifically on TCP/IP traffic and provides suitable classifications of TCP/IP fields and related covert channel techniques from the perspective of the statistical detection. The proposed methodology is evaluated with public traffic datasets
as well as covert channels generated according to main techniques described in the related literature.

covert channels, network security, statistical analysis

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

Electronic version of the publication:

Created from the Publication Database of the Vienna University of Technology.