TY - JOUR
AU1 - Park, Andrew T.
AU2 - Peck, Nathaniel
AU3 - Dill, Richard
AU4 - Hodson, Douglas D.
AU5 - Grimaila, Michael R.
AU6 - Henry, Wayne C.
AB - Successful missions in the field often rely upon communication technologies for tactics and coordination. One middleware used in securing these communication channels is Data Distribution Service (DDS) which employs a publish-subscribe model. However, researchers have found several security vulnerabilities in DDS implementations. DDS-Cerberus (DDS-C) is a security layer implemented into DDS to mitigate impersonation attacks using Kerberos authentication and ticketing. Even with the addition of DDS-C, the real-time message sending of DDS also needs to be upheld. This paper extends our previous work to analyze DDS-C’s impact on performance in a use case implementation. The use case covers an artificial intelligence (AI) scenario that connects edge sensors across a commercial network. Specifically, it characterizes how DDS-C performs between unmanned aerial vehicles (UAV), the cloud, and video streams for facial recognition. The experiments send a set number of video frames over the network using DDS to be processed by AI and displayed on a screen. An evaluation of network traffic using DDS-C revealed that it was not statistically significant compared to DDS for the majority of the configuration runs. The results demonstrate that DDS-C provides security benefits without significantly hindering the overall performance.
TI - Distribution of DDS-cerberus authenticated facial recognition streams
JF - The Journal of Supercomputing
DO - 10.1007/s11227-022-04771-2
DA - 2023-02-01
UR - https://www.deepdyve.com/lp/springer-journals/distribution-of-dds-cerberus-authenticated-facial-recognition-streams-5O10Cx8K0p
SP - 3471
EP - 3488
VL - 79
IS - 3
DP - DeepDyve
ER -