Výsledky vyhledávání - Malicious JavaScript code detection*

Detection Approach of Malicious JavaScript Code Based on deep learning

Autoři: Liyuan Zheng Dongcheng Zhang Xin Xie a další

Zdroj: 2023 IEEE 3rd International Conference on Information Technology, Big Data and Artificial Intelligence (ICIBA). :1075-1079

Research on Evasion and Detection of Malicious JavaScript Code

Autoři: Yujie Ma Haokai Wu Yu-an Tan a další

Zdroj: Lecture Notes in Computer Science ISBN: 9789819724574

Detection of Obfuscated Malicious JavaScript Code

Autoři: Ammar Alazab Ansam Khraisat Moutaz Alazab a další

Zdroj: Future Internet, Vol 14, Iss 8, p 217 (2022)

Témata: malware detection, intrusion detection, obfuscated malicious, machine learning, malicious JavaScript, Information technology, T58.5-58.64

Popis souboru: electronic resource

Relation: https://www.mdpi.com/1999-5903/14/8/217; https://doaj.org/toc/1999-5903

Přístupová URL adresa: https://doaj.org/article/e2fa7807e7e643e98d2b76506dbc7dd6

Detecting Malicious JavaScript Using Structure-Based Analysis of Graph Representation

Autoři: Muhammad Fakhrur Rozi Tao Ban Seiichi Ozawa a další

Zdroj: IEEE Access, Vol 11, Pp 102727-102745 (2023)

Témata: source code representation, cyber security, graph neural network, Abstract syntax tree, Electrical engineering. Electronics. Nuclear engineering, malicious JavaScript detection, TK1-9971

Přístupová URL adresa: https://doaj.org/article/96b921f1abd0426fa01fe22f24802029

Malicious JavaScript Code Detection Based on Hybrid Analysis

Autoři: Chunliu Cha Xincheng He Lei Xu

Zdroj: 2018 25th Asia-Pacific Software Engineering Conference (APSEC). :365-374

Témata: 13. Climate action, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 7. Clean energy

Přístupová URL adresa: http://dblp.uni-trier.de/db/conf/apsec/apsec2018.html#He0C18
https://dblp.uni-trier.de/db/conf/apsec/apsec2018.html#He0C18

Detection of Obfuscated Malicious JavaScript Code.

Autoři: Alazab, Ammar Khraisat, Ansam Alazab, Moutaz a další

Zdroj: Future Internet. Aug2022, Vol. 14 Issue 8, p217-N.PAG. 15p.

Témata: *JavaScript programming language, *Machine learning, *Internet users, *Cyberterrorism, *Malware, *Websites, Intrusion detection systems (Computer security)

Research on Malicious JavaScript Detection Technology Based on LSTM

Autoři: Yong Fang Cheng Huang Liang Liu a další

Zdroj: IEEE Access, Vol 6, Pp 59118-59125 (2018)

Témata: JavaScript, 0202 electrical engineering, electronic engineering, information engineering, bytecode, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, malicious code detection, LSTM, word vector, TK1-9971

Přístupová URL adresa: https://doaj.org/article/10eaad4b416443e996b2dfbad65517e4
https://doaj.org/article/10eaad4b416443e996b2dfbad65517e4
https://ieeexplore.ieee.org/document/8482113
https://dblp.uni-trier.de/db/journals/access/access6.html#FangHLX18

Detection of Malicious JavaScript Code in Web Pages

Autoři: D. R. Patil J. B. Patil

Zdroj: Indian Journal of Science and Technology. 10:1-12

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: http://www.indjst.org/index.php/indjst/article/view/114828
https://indjst.org/articles/detection-of-malicious-javascript-code-in-web-pages
http://www.i-scholar.in/index.php/indjst/article/view/151075

Breaking Obfuscation: Cluster-Aware Graph with LLM-Aided Recovery for Malicious JavaScript Detection

Autoři: Liang, Zhihong Wang, Xin Hu, Zhenhuang a další

Témata: Machine Learning, FOS: Computer and information sciences, Cryptography and Security, Cryptography and Security (cs.CR), Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2507.22447

Lux0R: Detection of Malicious PDF-embedded JavaScript code through Discriminant Analysis of API References

Autoři: CORONA, IGINO MAIORCA, DAVIDE ARIU, DAVIDE a další

Zdroj: Proceedings of the 2014 Workshop on Artificial Intelligent and Security Workshop. :47-57

Témata: 13. Climate action, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 3. Good health

Přístupová URL adresa: https://iris.unica.it/handle/11584/104201
http://pralab.diee.unica.it/sites/default/files/aisec09f-corona_0.pdf
https://dl.acm.org/doi/10.1145/2666652.2666657
https://dl.acm.org/citation.cfm?doid=2666652.2666657
https://dblp.uni-trier.de/db/conf/ccs/aisec2014.html#CoronaMAG14
https://hdl.handle.net/11584/104201
https://doi.org/10.1145/2666652.2666657

JSPRE: A Large-Scale Detection of Malicious JavaScript Code Based on Pre-filter

Autoři: Bixin Liu Jiaping Yu Zhiping Cai a další

Zdroj: Lecture Notes in Computer Science ISBN: 9783030000202

Přístupová URL adresa: https://dblp.uni-trier.de/db/conf/icccsec/icccsec2018-6.html#HouYLC18
https://link.springer.com/chapter/10.1007%2F978-3-030-00021-9_52
https://rd.springer.com/chapter/10.1007/978-3-030-00021-9_52

Malicious Javascript Detection based on Clustering Techniques

Autoři: Nguyen Hong Son Dung, Ha Thanh

Zdroj: International Journal of Network Security & Its Applications. 13:11-21

Témata: Malicious JavaScript, Detection model, Prediction support parameter, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, K-means clustering algorithm

JStill: mostly static detection of obfuscated malicious JavaScript code

Autoři: Sencun Zhu Fangfang Zhang Wei Xu

Zdroj: Proceedings of the third ACM conference on Data and application security and privacy. :117-128

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 3. Good health

Přístupová URL adresa: https://dblp.uni-trier.de/db/conf/codaspy/codaspy2013.html#XuZZ13
https://dl.acm.org/doi/10.1145/2435349.2435364
http://www.cse.psu.edu/~sxz16/papers/JStill.pdf
https://doi.org/10.1145/2435349.2435364
https://dl.acm.org/citation.cfm?doid=2435349.2435364
https://pennstate.pure.elsevier.com/en/publications/jstill-mostly-static-detection-of-obfuscated-malicious-javascript

Early detection of malicious behavior in JavaScript code

Autoři: Alexander Bikadorov Konrad Rieck Marius Kloft a další

Zdroj: Proceedings of the 5th ACM workshop on Security and artificial intelligence. :15-24

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: http://user.informatik.uni-goettingen.de/%7Ekrieck/docs/2012b-aisec.pdf
https://dblp.uni-trier.de/db/conf/ccs/aisec2012.html#SchuttKBR12
https://dl.acm.org/doi/10.1145/2381896.2381901
http://www2.informatik.hu-berlin.de/~kloft/publications/earlybird.pdf
https://prosec-project.org/docs/2012b-aisec.pdf
http://user.informatik.uni-goettingen.de/~krieck/docs/2012b-aisec.pdf

Detection and analysis of drive-by-download attacks and malicious JavaScript code

Autoři: Christopher Kruegel Marco Cova Giovanni Vigna

Zdroj: Proceedings of the 19th international conference on World wide web. :281-290

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: http://www.site.uottawa.ca/~nelkadri/CSI5389/Papers/40-Cova_et_al_WWW2010.pdf
https://doi.acm.org/10.1145/1772690.1772720
https://cs.ucsb.edu/~vigna/publications/2010_cova_kruegel_vigna_Wepawet.pdf
https://dl.acm.org/doi/10.1145/1772690.1772720
https://www.site.uottawa.ca/~nelkadri/CSI5389/Papers/40-Cova_et_al_WWW2010.pdf
https://core.ac.uk/display/21387414

Behavior Analysis Usage with Behavior Tures Adoption for Malicious Code Detection on JAVASCRIPT Scenarios Example

Autoři: Y. M. Tumanov S.V. Gavrilyuk

Zdroj: Безопасность информационных технологий, Vol 17, Iss 1, Pp 115-117 (2010)

Témata: malicious code detection, behavior analysis, behavior signature, Information technology, T58.5-58.64, Information theory, Q350-390

Popis souboru: electronic resource

Relation: https://bit.mephi.ru/index.php/bit/article/view/791; https://doaj.org/toc/2074-7128; https://doaj.org/toc/2074-7136

Přístupová URL adresa: https://doaj.org/article/1ee7b69964a2440c926708454e78aada

AMA: Static Code Analysis of Web Page for the Detection of Malicious Scripts

Autoři: Prabhu Seshagiri Padmamala Sriram Anu Vazhayil

Zdroj: Procedia Computer Science. 93:768-773

Témata: JavaScript, Obfuscation, Static Detection, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, Probable Plaintext attack

Přístupová URL adresa: https://www.amrita.edu/publication/ama-static-code-analysis-web-page-detection-malicious-scripts
https://core.ac.uk/display/82037002
https://www.sciencedirect.com/science/article/pii/S187705091631537X
https://www.sciencedirect.com/science/article/abs/pii/S187705091631537X

Polymorphic Malicious JavaScript Code Detection for APT Attack Defence

Autoři: Choi,Junho Choi,Chang You,Ilsun a další

Zdroj: JUCS-Journal of Universal Computer Science 21(3): 369-383

Témata: conceptual graph, 0202 electrical engineering, electronic engineering, information engineering, 0102 computer and information sciences, 02 engineering and technology, malicious code detection, APT attack defence, 01 natural sciences

Popis souboru: text/html

Přístupová URL adresa: http://www.jucs.org/jucs_21_3/polymorphic_malicious_javascript_code/jucs_21_03_0369_0383_choi.pdf
https://www.jucs.org/jucs_21_3/polymorphic_malicious_javascript_code/jucs_21_03_0369_0383_choi.pdf
http://www.jucs.org/doi?doi=10.3217/jucs-021-03-0369
https://dblp.uni-trier.de/db/journals/jucs/jucs21.html#ChoiCYK15
https://lib.jucs.org/article/23035
https://lib.jucs.org/article/23035/download/pdf/
https://lib.jucs.org/article/23035/
https://lib.jucs.org/article/23035/download/pdf/
https://doi.org/10.3217/jucs-021-03-0369

JACLNet:Application of adaptive code length network in JavaScript malicious code detection.

Autoři: Zhang Z Wan L Chu K a další

Zdroj: PloS one [PLoS One] 2022 Dec 14; Vol. 17 (12), pp. e0277891. Date of Electronic Publication: 2022 Dec 14 (Print Publication: 2022).

Způsob vydávání: Journal Article; Research Support, Non-U.S. Gov't

Informace o časopise: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Výrazy ze slovníku MeSH: Algorithms* , Computer Security*

An improved bytecode similarity measurement for malicious JavaScript code detection

一個改良位元組碼相似度計算之JavaScript惡意程式偵測方法

Autoři: Jun-Xu Yang 楊鈞旭

Thesis Advisors: Jun-Xu Yang 楊鈞旭

Popis souboru: 31

Dostupnost: http://ndltd.ncl.edu.tw/handle/dyhtkn