Transport layer identification of P2P traffic
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
BLINC: multilevel traffic classification in the dark
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
Traffic classification using clustering algorithms
Proceedings of the 2006 SIGCOMM workshop on Mining network data
On Inferring Application Protocol Behaviors in Encrypted Network Traffic
The Journal of Machine Learning Research
A markovian signature-based approach to IP traffic classification
Proceedings of the 3rd annual ACM workshop on Mining network data
BTM - An Automated Rule-based BT Monitoring System for Piracy Detection
ICIMP '07 Proceedings of the Second International Conference on Internet Monitoring and Protection
A Management Platform for Tracking Cyber Predators in Peer-to-Peer Networks
ICIMP '07 Proceedings of the Second International Conference on Internet Monitoring and Protection
Identifying BT-like P2P Traffic by the Discreteness of Remote Hosts
LCN '07 Proceedings of the 32nd IEEE Conference on Local Computer Networks
File Marshal: Automatic extraction of peer-to-peer data
Digital Investigation: The International Journal of Digital Forensics & Incident Response
Wireless telemedicine and m-health: technologies, applications and research issues
International Journal of Sensor Networks
A survey of security visualization for computer network logs
Security and Communication Networks
Security and Communication Networks
Hi-index | 0.00 |
This paper presents a Field Programmable Gate Array (FPGA)-based tool designed to process file transfers using the BitTorrent Peer-to-Peer (P2P) protocol and VoIP phone calls made using the Session Initiation Protocol (SIP). The tool searches selected control messages in real time and compares the unique identifier of the shared file or phone number against a list of known contraband files or phone numbers. Results show the FPGA tool processes P2P packets of interest 92% faster than a software-only configuration and is 97.6% accurate at capturing and processing messages at a traffic load of 89.6 Mbps.