Is P2P dying or just hiding?
Abstract
Recent reports in the popular media suggest a significant decrease in peer-to-peer (P2P) file-sharing traffic, attributed to the public's response to legal threats. Have we reached the end of the P2P revolution? In pursuit of legitimate data to verify this hypothesis, in this paper, we embark on a more accurate measurement effort of P2P traffic at the link level. In contrast to previous efforts, we introduce two novel elements in our methodology. First, we measure traffic of all known popular P2P protocols. Second, we go beyond the "known port" limitation by reverse engineering the protocols and identifying characteristic strings in the payload. We find that, if measured accurately, P2P traffic has never declined; indeed we have never seen the proportion of P2P traffic decrease over time (any change is an increase) in any of our data sources.
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Relying solely on port numbers has been shown to be ineffective, largely due to the use of dynamic port negotiation, tunneling and misuse of port numbers assigned to well-known applications for obfuscating traffic and avoiding firewalls.
“Furthermore, relying solely on port numbers has been shown to be ineffective [125,228,320], largely due to the use of dynamic port negotiation, tunneling and misuse of port numbers assigned to well-known applications for obfuscating traffic and avoiding firewalls [54,109,176,286].”
From A comprehensive survey on machine learning for networking: Evolution, applications and research opportunities (2018) · cites this paper as [228]
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Kornycky, J., Abdul-Hameed, O., KONDOZ, A. M., & Barber, B. C. (2016) · IEEE/ACM Transactions on Networking · doi:10.1109/tnet.2016.2562259 · Cited by 34 · see citing works
Unsupervised host behavior classification from connection patterns
Dewaele, G., Himura, Y., Borgnat, P., Fukuda, K., Abry, P., Michel, O., Fontugne, R., Cho, K., & Esaki, H. (2010) · International Journal of Network Management · doi:10.1002/nem.750 · Cited by 33 · see citing works
A Packet-level Characterization of Network Traffic
Dainotti, A., Pescapè, A., & Ventre, G. (2006) · doi:10.1109/camad.2006.1649716 · Cited by 33 · see citing works
- Authors
- Karagiannis, T., Broido, A., Brownlee, N., Claffy, K. C., & Faloutsos, M.
- Affiliations
- University of California, Riverside (US)
- University of California San Diego (US)
- Venue
- IEEE Global Telecommunications Conference, 2004. GLOBECOM '04.
- Publisher
- IEEE
- Published
- 2005-04-05
- Volume
- 3
- Pages
- 1532-1538
- ISSN
- 1930-529X (ISSN-L)
- OpenAlex
- W1559810148
- Cited by
- 504
- References
- 12
- Citations by year
- 2025: 1 · 2023: 2 · 2022: 7 · 2021: 5 · 2020: 8 · 2019: 7 · 2018: 9 · 2017: 6 · 2016: 10 · 2015: 13 · 2014: 18 · 2013: 29 · 2012: 33
- FWCI
- 36.13
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Globecom (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Peer-to-Peer Network Technologies
- Social Sciences › Business, Management and Accounting › Marketing › Copyright and Intellectual Property
- Physical Sciences › Computer Science › Artificial Intelligence › Internet Traffic Analysis and Secure E-voting
- Keywords
- peer-to-peer file sharing, network traffic statistics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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