Matches in SemOpenAlex for { <https://semopenalex.org/work/W2891865791> ?p ?o ?g. }
Showing items 1 to 98 of
98
with 100 items per page.
- W2891865791 abstract "Efficient extraction of code authorship attributes is key for successful identification. However, the extraction of such attributes is very challenging, due to various programming language specifics, the limited number of available code samples per author, and the average code lines per file, among others. To this end, this work proposes a Deep Learning-based Code Authorship Identification System (DL-CAIS) for code authorship attribution that facilitates large-scale, language-oblivious, and obfuscation-resilient code authorship identification. The deep learning architecture adopted in this work includes TF-IDF-based deep representation using multiple Recurrent Neural Network (RNN) layers and fully-connected layers dedicated to authorship attribution learning. The deep representation then feeds into a random forest classifier for scalability to de-anonymize the author. Comprehensive experiments are conducted to evaluate DL-CAIS over the entire Google Code Jam (GCJ) dataset across all years (from 2008 to 2016) and over real-world code samples from 1987 public repositories on GitHub. The results of our work show the high accuracy despite requiring a smaller number of files per author. Namely, we achieve an accuracy of 96% when experimenting with 1,600 authors for GCJ, and 94.38% for the real-world dataset for 745 C programmers. Our system also allows us to identify 8,903 authors, the largest-scale dataset used by far, with an accuracy of 92.3%. Moreover, our technique is resilient to language-specifics, and thus it can identify authors of four programming languages (e.g. C, C++, Java, and Python), and authors writing in mixed languages (e.g. Java/C++, Python/C++). Finally, our system is resistant to sophisticated obfuscation (e.g. using C Tigress) with an accuracy of 93.42% for a set of 120 authors." @default.
- W2891865791 created "2018-09-27" @default.
- W2891865791 creator A5023828527 @default.
- W2891865791 creator A5042456819 @default.
- W2891865791 creator A5077402873 @default.
- W2891865791 creator A5079230730 @default.
- W2891865791 date "2018-10-15" @default.
- W2891865791 modified "2023-09-27" @default.
- W2891865791 title "Large-Scale and Language-Oblivious Code Authorship Identification" @default.
- W2891865791 cites W13740476 @default.
- W2891865791 cites W1903025644 @default.
- W2891865791 cites W2010452235 @default.
- W2891865791 cites W2029103396 @default.
- W2891865791 cites W2044555705 @default.
- W2891865791 cites W2054126054 @default.
- W2891865791 cites W2078111377 @default.
- W2891865791 cites W2092475127 @default.
- W2891865791 cites W2104595931 @default.
- W2891865791 cites W2110127053 @default.
- W2891865791 cites W2119804197 @default.
- W2891865791 cites W2129364433 @default.
- W2891865791 cites W2129683917 @default.
- W2891865791 cites W2136922672 @default.
- W2891865791 cites W2146500806 @default.
- W2891865791 cites W2151505086 @default.
- W2891865791 cites W2163922914 @default.
- W2891865791 cites W2742948365 @default.
- W2891865791 cites W2911964244 @default.
- W2891865791 cites W3004022289 @default.
- W2891865791 cites W3004984289 @default.
- W2891865791 cites W4206031910 @default.
- W2891865791 cites W4231109964 @default.
- W2891865791 doi "https://doi.org/10.1145/3243734.3243738" @default.
- W2891865791 hasPublicationYear "2018" @default.
- W2891865791 type Work @default.
- W2891865791 sameAs 2891865791 @default.
- W2891865791 citedByCount "53" @default.
- W2891865791 countsByYear W28918657912019 @default.
- W2891865791 countsByYear W28918657912020 @default.
- W2891865791 countsByYear W28918657912021 @default.
- W2891865791 countsByYear W28918657912022 @default.
- W2891865791 countsByYear W28918657912023 @default.
- W2891865791 crossrefType "proceedings-article" @default.
- W2891865791 hasAuthorship W2891865791A5023828527 @default.
- W2891865791 hasAuthorship W2891865791A5042456819 @default.
- W2891865791 hasAuthorship W2891865791A5077402873 @default.
- W2891865791 hasAuthorship W2891865791A5079230730 @default.
- W2891865791 hasConcept C108583219 @default.
- W2891865791 hasConcept C116834253 @default.
- W2891865791 hasConcept C119857082 @default.
- W2891865791 hasConcept C154945302 @default.
- W2891865791 hasConcept C177264268 @default.
- W2891865791 hasConcept C199360897 @default.
- W2891865791 hasConcept C204321447 @default.
- W2891865791 hasConcept C23123220 @default.
- W2891865791 hasConcept C2776760102 @default.
- W2891865791 hasConcept C41008148 @default.
- W2891865791 hasConcept C48044578 @default.
- W2891865791 hasConcept C519991488 @default.
- W2891865791 hasConcept C548217200 @default.
- W2891865791 hasConcept C59822182 @default.
- W2891865791 hasConcept C77088390 @default.
- W2891865791 hasConcept C86803240 @default.
- W2891865791 hasConcept C95623464 @default.
- W2891865791 hasConceptScore W2891865791C108583219 @default.
- W2891865791 hasConceptScore W2891865791C116834253 @default.
- W2891865791 hasConceptScore W2891865791C119857082 @default.
- W2891865791 hasConceptScore W2891865791C154945302 @default.
- W2891865791 hasConceptScore W2891865791C177264268 @default.
- W2891865791 hasConceptScore W2891865791C199360897 @default.
- W2891865791 hasConceptScore W2891865791C204321447 @default.
- W2891865791 hasConceptScore W2891865791C23123220 @default.
- W2891865791 hasConceptScore W2891865791C2776760102 @default.
- W2891865791 hasConceptScore W2891865791C41008148 @default.
- W2891865791 hasConceptScore W2891865791C48044578 @default.
- W2891865791 hasConceptScore W2891865791C519991488 @default.
- W2891865791 hasConceptScore W2891865791C548217200 @default.
- W2891865791 hasConceptScore W2891865791C59822182 @default.
- W2891865791 hasConceptScore W2891865791C77088390 @default.
- W2891865791 hasConceptScore W2891865791C86803240 @default.
- W2891865791 hasConceptScore W2891865791C95623464 @default.
- W2891865791 hasLocation W28918657911 @default.
- W2891865791 hasOpenAccess W2891865791 @default.
- W2891865791 hasPrimaryLocation W28918657911 @default.
- W2891865791 hasRelatedWork W1825982205 @default.
- W2891865791 hasRelatedWork W2327204559 @default.
- W2891865791 hasRelatedWork W2529681551 @default.
- W2891865791 hasRelatedWork W3107474891 @default.
- W2891865791 hasRelatedWork W3158264953 @default.
- W2891865791 hasRelatedWork W3199434107 @default.
- W2891865791 hasRelatedWork W4223943233 @default.
- W2891865791 hasRelatedWork W4310989423 @default.
- W2891865791 hasRelatedWork W4312200629 @default.
- W2891865791 hasRelatedWork W4360585206 @default.
- W2891865791 isParatext "false" @default.
- W2891865791 isRetracted "false" @default.
- W2891865791 magId "2891865791" @default.
- W2891865791 workType "article" @default.