A heuristics for HTTP traffic identification in measuring user dissimilarity
<p>The prevalence of HTTP web traffic on the Internet has long transcended the layer 7 classification, to layers such as layer 5 of the OSI model stack. This coupled with the integration-diversity of other layers and application layer protocols has made identification of user-initiated HTTP we...
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| مؤلفون آخرون: | , , , |
| منشور في: |
2020
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| _version_ | 1864513567044141056 |
|---|---|
| author | Adeyemi R. Ikuesan (14157123) |
| author2 | Mazleena Salleh (3383588) Hein S. Venter (3383597) Shukor Abd Razak (3383591) Steven M. Furnell (14157126) |
| author2_role | author author author author |
| author_facet | Adeyemi R. Ikuesan (14157123) Mazleena Salleh (3383588) Hein S. Venter (3383597) Shukor Abd Razak (3383591) Steven M. Furnell (14157126) |
| author_role | author |
| dc.creator.none.fl_str_mv | Adeyemi R. Ikuesan (14157123) Mazleena Salleh (3383588) Hein S. Venter (3383597) Shukor Abd Razak (3383591) Steven M. Furnell (14157126) |
| dc.date.none.fl_str_mv | 2020-06-02T18:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1007/s42454-020-00010-2 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/A_heuristics_for_HTTP_traffic_identification_in_measuring_user_dissimilarity/21601509 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Information and computing sciences Cybersecurity and privacy Distributed computing and systems software Heuristic algorithm User-initiated HTTP request GET method of HTTP request Intrinsic network features User inter-request time User identification |
| dc.title.none.fl_str_mv | A heuristics for HTTP traffic identification in measuring user dissimilarity |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p>The prevalence of HTTP web traffic on the Internet has long transcended the layer 7 classification, to layers such as layer 5 of the OSI model stack. This coupled with the integration-diversity of other layers and application layer protocols has made identification of user-initiated HTTP web traffic complex, thus increasing user anonymity on the Internet. This study reveals that, with the current complex nature of Internet and HTTP traffic, browser complexity, dynamic web programming structure, the surge in network delay, and unstable user behavior in network interaction, user-initiated requests can be accurately determined. The study utilizes HTTP request method of GET filtering, to develop a heuristic algorithm to identify user-initiated requests. The algorithm was experimentally tested on a group of users, to ascertain the certainty of identifying user-initiated requests. The result demonstrates that user-initiated HTTP requests can be reliably identified with a recall rate at 0.94 and F-measure at 0.969. Additionally, this study extends the paradigm of user identification based on the intrinsic characteristics of users, exhibited in network traffic. The application of these research findings finds relevance in user identification for insider investigation, e-commerce, and e-learning system as well as in network planning and management. Further, the findings from the study are relevant in web usage mining, where user-initiated action comprises the fundamental unit of measurement.</p><h2>Other Information</h2> <p> Published in: Human-Intelligent Systems Integration<br> License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="http://dx.doi.org/10.1007/s42454-020-00010-2" target="_blank">http://dx.doi.org/10.1007/s42454-020-00010-2</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_3541510fecb89b1b6dc7846a69766238 |
| identifier_str_mv | 10.1007/s42454-020-00010-2 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/21601509 |
| publishDate | 2020 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | A heuristics for HTTP traffic identification in measuring user dissimilarityAdeyemi R. Ikuesan (14157123)Mazleena Salleh (3383588)Hein S. Venter (3383597)Shukor Abd Razak (3383591)Steven M. Furnell (14157126)Information and computing sciencesCybersecurity and privacyDistributed computing and systems softwareHeuristic algorithmUser-initiated HTTP requestGET method of HTTP requestIntrinsic network featuresUser inter-request timeUser identification<p>The prevalence of HTTP web traffic on the Internet has long transcended the layer 7 classification, to layers such as layer 5 of the OSI model stack. This coupled with the integration-diversity of other layers and application layer protocols has made identification of user-initiated HTTP web traffic complex, thus increasing user anonymity on the Internet. This study reveals that, with the current complex nature of Internet and HTTP traffic, browser complexity, dynamic web programming structure, the surge in network delay, and unstable user behavior in network interaction, user-initiated requests can be accurately determined. The study utilizes HTTP request method of GET filtering, to develop a heuristic algorithm to identify user-initiated requests. The algorithm was experimentally tested on a group of users, to ascertain the certainty of identifying user-initiated requests. The result demonstrates that user-initiated HTTP requests can be reliably identified with a recall rate at 0.94 and F-measure at 0.969. Additionally, this study extends the paradigm of user identification based on the intrinsic characteristics of users, exhibited in network traffic. The application of these research findings finds relevance in user identification for insider investigation, e-commerce, and e-learning system as well as in network planning and management. Further, the findings from the study are relevant in web usage mining, where user-initiated action comprises the fundamental unit of measurement.</p><h2>Other Information</h2> <p> Published in: Human-Intelligent Systems Integration<br> License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="http://dx.doi.org/10.1007/s42454-020-00010-2" target="_blank">http://dx.doi.org/10.1007/s42454-020-00010-2</a></p>2020-06-02T18:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1007/s42454-020-00010-2https://figshare.com/articles/journal_contribution/A_heuristics_for_HTTP_traffic_identification_in_measuring_user_dissimilarity/21601509CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/216015092020-06-02T18:00:00Z |
| spellingShingle | A heuristics for HTTP traffic identification in measuring user dissimilarity Adeyemi R. Ikuesan (14157123) Information and computing sciences Cybersecurity and privacy Distributed computing and systems software Heuristic algorithm User-initiated HTTP request GET method of HTTP request Intrinsic network features User inter-request time User identification |
| status_str | publishedVersion |
| title | A heuristics for HTTP traffic identification in measuring user dissimilarity |
| title_full | A heuristics for HTTP traffic identification in measuring user dissimilarity |
| title_fullStr | A heuristics for HTTP traffic identification in measuring user dissimilarity |
| title_full_unstemmed | A heuristics for HTTP traffic identification in measuring user dissimilarity |
| title_short | A heuristics for HTTP traffic identification in measuring user dissimilarity |
| title_sort | A heuristics for HTTP traffic identification in measuring user dissimilarity |
| topic | Information and computing sciences Cybersecurity and privacy Distributed computing and systems software Heuristic algorithm User-initiated HTTP request GET method of HTTP request Intrinsic network features User inter-request time User identification |