Fetching the paper…
Reading the bibliography…
The rampant occurrence of cybersecurity breaches imposes substantial limitations on the progress of network infrastructures, leading to compromised data, financial losses, potential harm to individuals, and disruptions in essential services.
R. Bar-Yehuda and S. Even, “A local-ratio theorem for approximating the weighted vertex cover problem,” Annals of Discrete Mathematics , vol. 25, no. 27-46, p. 50, 1985
1985
Earlier work this paper cites.
R. Grishman and B. M. Sundheim, “Message understanding conference-6: A brief history,” in COLING 1996 Volume 1: The 16th International Conference on Computational Linguistics , 1996
1996
Earlier work this paper cites.
L. P. Swiler, C. Phillips, and T. Gaylor, “A graph-based network-vulnerability analysis system,” Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), Tech. Rep., 1998
1998
Earlier work this paper cites.
G. Zhou and J. Su, “Named entity recognition using an hmm-based chunk tagger,” in Proceedings of the 40th annual meeting of the association for computational linguistics , 2002, pp. 473–480
2002
Earlier work this paper cites.
M. Bianchini, M. Gori, and F. Scarselli, “Inside pagerank,” ACM Transactions on Internet Technology (TOIT) , vol. 5, no. 1, pp. 92–128, 2005
2005
Earlier work this paper cites.
Y. Liu and H. Man, “Network vulnerability assessment using bayesian networks,” in Data mining, intrusion detection, information assurance, and data networks security 2005 , vol. 5812. SPIE, 2005, pp. 61–71
2005
Earlier work this paper cites.
W. Li and R. B. Vaughn, “Cluster security research involving the modeling of network exploitations using exploitation graphs,” in Sixth IEEE International Symposium on Cluster Computing and the Grid (CCGRID’06) , vol. 2. IEEE, 2006, pp. 26–26
2006
Earlier work this paper cites.
D. Nadeau and S. Sekine, “A survey of named entity recognition and classification,” Lingvisticae Investigationes , vol. 30, no. 1, pp. 3–26, 2007
2007
Earlier work this paper cites.
A. Hagberg, P. Swart, and D. S Chult, “Exploring network structure, dynamics, and function using networkx,” Los Alamos National Lab.(LANL), Los Alamos, NM (United States), Tech. Rep., 2008
2008
Earlier work this paper cites.
P. M. Shishtla, K. Gali, P. Pingali, and V. Varma, “Experiments in telugu ner: A conditional random field approach,” in Proceedings of the IJCNLP-08 Workshop on Named Entity Recognition for South and South East Asian Languages , 2008
2008
Earlier work this paper cites.
L. Van der Maaten and G. Hinton, “Visualizing data using t-sne.” Journal of machine learning research , vol. 9, no. 11, 2008
2008
Earlier work this paper cites.
L. Wang, T. Islam, T. Long, A. Singhal, and S. Jajodia, “An attack graph-based probabilistic security metric,” in Data and Applications Security XXII: 22nd Annual IFIP WG 11.3 Working Conference on Data and Applications Security London, UK, July 13-16, 2008 Proceedings 22 . Springer, 2008, pp. 283–296
2008
Earlier work this paper cites.
L. Lu, R. Safavi-Naini, M. Hagenbuchner, W. Susilo, J. Horton, S. L. Yong, and A. C. Tsoi, “Ranking attack graphs with graph neural networks,” in Information Security Practice and Experience: 5th International Conference, ISPEC 2009 Xi’an, China, April 13-15, 2009 Proceedings 5 . Springer, 2009, pp. 345–359
2009
Earlier work this paper cites.
N. Idika and B. Bhargava, “Extending attack graph-based security metrics and aggregating their application,” IEEE Transactions on dependable and secure computing , vol. 9, no. 1, pp. 75–85, 2010
2010
Earlier work this paper cites.
M. Kuhlmann, C. Gómez-Rodríguez, and G. Satta, “Dynamic programming algorithms for transition-based dependency parsers,” in Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies , 2011, pp. 673–682
2011
Earlier work this paper cites.
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg et al. , “Scikit-learn: Machine learning in python,” the Journal of machine Learning research , vol. 12, pp. 2825–2830, 2011
2011
Earlier work this paper cites.
R. Rehurek and P. Sojka, “Gensim–python framework for vector space modelling,” NLP Centre, Faculty of Informatics, Masaryk University, Brno, Czech Republic , vol. 3, no. 2, 2011
2011
Earlier work this paper cites.
M. Urbanska, I. Ray, A. E. Howe, and M. Roberts, “Structuring a vulnerability description for comprehensive single system security analysis,” Rocky Mountain Celebration of Women in Computing, Fort Collins, CO, USA , 2012
2012
Earlier work this paper cites.
H. Booth, D. Rike, and G. A. Witte, “The national vulnerability database (nvd): Overview,” 2013
2013
Earlier work this paper cites.
2013
Earlier work this paper cites.
2013
Earlier work this paper cites.
T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean, “Distributed representations of words and phrases and their compositionality,” Advances in neural information processing systems , vol. 26, 2013
2013
Cited alongside, same era.
J. J. Miller, “Graph database applications and concepts with neo4j,” in Proceedings of the southern association for information systems conference, Atlanta, GA, USA , vol. 2324, no. 36, 2013
2013
Cited alongside, same era.
S. Abraham and S. Nair, “Cyber security analytics: a stochastic model for security quantification using absorbing markov chains,” Journal of Communications , vol. 9, no. 12, pp. 899–907, 2014
2014
Cited alongside, same era.
J. Pennington, R. Socher, and C. D. Manning, “Glove: Global vectors for word representation,” in Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP) , 2014, pp. 1532–1543
2014
Cited alongside, same era.
B. Wang, A. Wang, F. Chen, Y. Wang, and C.-C. J. Kuo, “Evaluating word embedding models: Methods and experimental results,” APSIPA transactions on signal and information processing , vol. 8, p. e19, 2019
2019
Later among the works it cites.
K. Xu, Z. Yang, P. Kang, Q. Wang, and W. Liu, “Document-level attention-based bilstm-crf incorporating disease dictionary for disease named entity recognition,” Computers in biology and medicine , vol. 108, pp. 122–132, 2019
2019
Later among the works it cites.
R. Corizzo, E. Zdravevski, M. Russell, A. Vagliano, and N. Japkowicz, “Feature extraction based on word embedding models for intrusion detection in network traffic,” Journal of Surveillance, Security and Safety , 2020
2020
Later among the works it cites.
J. Fan, Y. Li, S. Wang, and T. N. Nguyen, “Ac/c++ code vulnerability dataset with code changes and cve summaries,” in Proceedings of the 17th International Conference on Mining Software Repositories , 2020, pp. 508–512
2020
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
S. Weerawardhana, S. Mukherjee, I. Ray, and A. Howe, “Automated extraction of vulnerability information for home computer security,” in International Symposium on Foundations and Practice of Security . Springer, 2014, pp. 356–366
2014
Cited alongside, same era.
C. L. Jones, R. A. Bridges, K. M. Huffer, and J. R. Goodall, “Towards a relation extraction framework for cyber-security concepts,” in Proceedings of the 10th Annual Cyber and Information Security Research Conference , 2015, pp. 1–4
2015
Cited alongside, same era.
——, “Automated extraction of vulnerability information for home computer security,” in Foundations and Practice of Security: 7th International Symposium, FPS 2014, Montreal, QC, Canada, November 3-5, 2014. Revised Selected Papers 7 . Springer, 2015, pp. 356–366
2015
Cited alongside, same era.
M. Naili, A. H. Chaibi, and H. H. B. Ghezala, “Comparative study of word embedding methods in topic segmentation,” Procedia computer science , vol. 112, pp. 340–349, 2017
2017
Cited alongside, same era.
M. U. Aksu, K. Bicakci, M. H. Dilek, A. M. Ozbayoglu, and E. ı. Tatli, “Automated generation of attack graphs using nvd,” in Proceedings of the Eighth ACM Conference on Data and Application Security and Privacy , 2018, pp. 135–142
2018
Cited alongside, same era.
2018
Cited alongside, same era.
Y. Li and T. Yang, “Word embedding for understanding natural language: a survey,” in Guide to big data applications . Springer, 2018, pp. 83–104
2018
Cited alongside, same era.
B. E. Strom, A. Applebaum, D. P. Miller, K. C. Nickels, A. G. Pennington, and C. B. Thomas, “Mitre att&ck: Design and philosophy,” in Technical report . The MITRE Corporation, 2018
2018
Cited alongside, same era.
Later among the works it cites.
M. Honnibal, I. Montani, S. Van Landeghem, A. Boyd et al. , “spacy: Industrial-strength natural language processing in python,” 2020
2020
Later among the works it cites.
Y. Jin, J. Lim, I. Yun, and T. Kim, “Compromising the macOS kernel through Safari by chaining six vulnerabilities,” in Black Hat USA Briefings (Black Hat USA) , Las Vegas, NV, Aug. 2020
2020
Later among the works it cites.
J. Li, A. Sun, J. Han, and C. Li, “A survey on deep learning for named entity recognition,” IEEE Transactions on Knowledge and Data Engineering , vol. 34, no. 1, pp. 50–70, 2020
2020
Later among the works it cites.
K. Simran, S. Sriram, R. Vinayakumar, and K. Soman, “Deep learning approach for intelligent named entity recognition of cyber security,” in Advances in Signal Processing and Intelligent Recognition Systems: 5th International Symposium, SIRS 2019, Trivandrum, India, December 18–21, 2019, Revised Selected Papers 5 . Springer, 2020, pp. 163–172
2020
Later among the works it cites.
H. Binyamini, R. Bitton, M. Inokuchi, T. Yagyu, Y. Elovici, and A. Shabtai, “A framework for modeling cyber attack techniques from security vulnerability descriptions,” in Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining , 2021, pp. 2574–2583
2021
Later among the works it cites.
“2022 official cybercrime report,” 2022, https://www.esentire.com/resources/library/2022-official-cybercrime-report
2022
Later among the works it cites.
Z. Fang, H. Fu, T. Gu, P. Hu, J. Song, T. Jaeger, and P. Mohapatra, “Iota: A framework for analyzing system-level security of iots,” in 2022 IEEE/ACM Seventh International Conference on Internet-of-Things Design and Implementation (IoTDI) . IEEE, 2022, pp. 143–155
2022
Later among the works it cites.
H. Guo, S. Chen, Z. Xing, X. Li, Y. Bai, and J. Sun, “Detecting and augmenting missing key aspects in vulnerability descriptions,” ACM Transactions on Software Engineering and Methodology (TOSEM) , vol. 31, no. 3, pp. 1–27, 2022
2022
Later among the works it cites.
2022
Later among the works it cites.
X. Jin, S. Manandhar, K. Kafle, Z. Lin, and A. Nadkarni, “Understanding iot security from a market-scale perspective,” in Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security , 2022, pp. 1615–1629
2022
Later among the works it cites.
X. Jin, K. Pei, J. Y. Won, and Z. Lin, “Symlm: Predicting function names in stripped binaries via context-sensitive execution-aware code embeddings,” in Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security , 2022, pp. 1631–1645
2022
Later among the works it cites.
(2022) Key details phrasing. [Online]. Available: https://cveproject.github.io/docs/content/key-details-phrasing.pdf
2022
Later among the works it cites.
P. Liu, Y. Guo, F. Wang, and G. Li, “Chinese named entity recognition: The state of the art,” Neurocomputing , vol. 473, pp. 37–53, 2022
2022
Later among the works it cites.
B. Wu, S. Liu, R. Feng, X. Xie, J. Siow, and S.-W. Lin, “Enhancing security patch identification by capturing structures in commits,” IEEE Transactions on Dependable and Secure Computing , 2022
2022
Later among the works it cites.
2023
Closest in time.
2023
Closest in time.
S. Srivastava, B. Paul, and D. Gupta, “Study of word embeddings for enhanced cyber security named entity recognition,” Procedia Computer Science , vol. 218, pp. 449–460, 2023
2023
Closest in time.