Journal article 87 views
SVScanner: Detecting smart contract vulnerabilities via deep semantic extraction
Journal of Information Security and Applications, Volume: 75, Start page: 103484
Swansea University Author: Yang Liu
Full text not available from this repository: check for access using links below.
DOI (Published version): 10.1016/j.jisa.2023.103484
Abstract
SVScanner: Detecting smart contract vulnerabilities via deep semantic extraction
Published in: | Journal of Information Security and Applications |
---|---|
ISSN: | 2214-2126 |
Published: |
Elsevier BV
2023
|
Online Access: |
Check full text
|
URI: | https://cronfa.swan.ac.uk/Record/cronfa67209 |
first_indexed |
2024-08-27T16:11:41Z |
---|---|
last_indexed |
2024-11-25T14:19:43Z |
id |
cronfa67209 |
recordtype |
SURis |
fullrecord |
<?xml version="1.0"?><rfc1807><datestamp>2024-08-27T17:11:56.7751362</datestamp><bib-version>v2</bib-version><id>67209</id><entry>2024-07-29</entry><title>SVScanner: Detecting smart contract vulnerabilities via deep semantic extraction</title><swanseaauthors><author><sid>ba37dab58c9093dc63c79001565b75d4</sid><ORCID>0000-0003-2486-5765</ORCID><firstname>Yang</firstname><surname>Liu</surname><name>Yang Liu</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2024-07-29</date><deptcode>MACS</deptcode><abstract/><type>Journal Article</type><journal>Journal of Information Security and Applications</journal><volume>75</volume><journalNumber/><paginationStart>103484</paginationStart><paginationEnd/><publisher>Elsevier BV</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>2214-2126</issnPrint><issnElectronic/><keywords>Blockchain; Smart contract; Vulnerability detection; Deep learning; Deep semantic extraction</keywords><publishedDay>1</publishedDay><publishedMonth>6</publishedMonth><publishedYear>2023</publishedYear><publishedDate>2023-06-01</publishedDate><doi>10.1016/j.jisa.2023.103484</doi><url/><notes/><college>COLLEGE NANME</college><department>Mathematics and Computer Science School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>MACS</DepartmentCode><institution>Swansea University</institution><apcterm/><funders>This work was supported in part by the Shenzhen Colleges and Universities Stable Support Program No.
GXWD20220817124251002, the Fundamental Research Funds for the Central Universities under Grant HIT.OCEF.2021007, the Joint Funds of the National Natural Science Foundation of China (Grant No. U22A2036), the Shenzhen Science and Technology Research and Development Fundation No.
JCYJ20190806143418198, and the Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies (2022B1212010005).</funders><projectreference/><lastEdited>2024-08-27T17:11:56.7751362</lastEdited><Created>2024-07-29T12:50:12.3834661</Created><path><level id="1">Faculty of Science and Engineering</level><level id="2">School of Mathematics and Computer Science - Computer Science</level></path><authors><author><firstname>Hengyan</firstname><surname>Zhang</surname><order>1</order></author><author><firstname>Weizhe</firstname><surname>Zhang</surname><orcid>0000-0003-4783-876x</orcid><order>2</order></author><author><firstname>Yuming</firstname><surname>Feng</surname><orcid>0000-0001-8922-0496</orcid><order>3</order></author><author><firstname>Yang</firstname><surname>Liu</surname><orcid>0000-0003-2486-5765</orcid><order>4</order></author></authors><documents/><OutputDurs/></rfc1807> |
spelling |
2024-08-27T17:11:56.7751362 v2 67209 2024-07-29 SVScanner: Detecting smart contract vulnerabilities via deep semantic extraction ba37dab58c9093dc63c79001565b75d4 0000-0003-2486-5765 Yang Liu Yang Liu true false 2024-07-29 MACS Journal Article Journal of Information Security and Applications 75 103484 Elsevier BV 2214-2126 Blockchain; Smart contract; Vulnerability detection; Deep learning; Deep semantic extraction 1 6 2023 2023-06-01 10.1016/j.jisa.2023.103484 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University This work was supported in part by the Shenzhen Colleges and Universities Stable Support Program No. GXWD20220817124251002, the Fundamental Research Funds for the Central Universities under Grant HIT.OCEF.2021007, the Joint Funds of the National Natural Science Foundation of China (Grant No. U22A2036), the Shenzhen Science and Technology Research and Development Fundation No. JCYJ20190806143418198, and the Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies (2022B1212010005). 2024-08-27T17:11:56.7751362 2024-07-29T12:50:12.3834661 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Hengyan Zhang 1 Weizhe Zhang 0000-0003-4783-876x 2 Yuming Feng 0000-0001-8922-0496 3 Yang Liu 0000-0003-2486-5765 4 |
title |
SVScanner: Detecting smart contract vulnerabilities via deep semantic extraction |
spellingShingle |
SVScanner: Detecting smart contract vulnerabilities via deep semantic extraction Yang Liu |
title_short |
SVScanner: Detecting smart contract vulnerabilities via deep semantic extraction |
title_full |
SVScanner: Detecting smart contract vulnerabilities via deep semantic extraction |
title_fullStr |
SVScanner: Detecting smart contract vulnerabilities via deep semantic extraction |
title_full_unstemmed |
SVScanner: Detecting smart contract vulnerabilities via deep semantic extraction |
title_sort |
SVScanner: Detecting smart contract vulnerabilities via deep semantic extraction |
author_id_str_mv |
ba37dab58c9093dc63c79001565b75d4 |
author_id_fullname_str_mv |
ba37dab58c9093dc63c79001565b75d4_***_Yang Liu |
author |
Yang Liu |
author2 |
Hengyan Zhang Weizhe Zhang Yuming Feng Yang Liu |
format |
Journal article |
container_title |
Journal of Information Security and Applications |
container_volume |
75 |
container_start_page |
103484 |
publishDate |
2023 |
institution |
Swansea University |
issn |
2214-2126 |
doi_str_mv |
10.1016/j.jisa.2023.103484 |
publisher |
Elsevier BV |
college_str |
Faculty of Science and Engineering |
hierarchytype |
|
hierarchy_top_id |
facultyofscienceandengineering |
hierarchy_top_title |
Faculty of Science and Engineering |
hierarchy_parent_id |
facultyofscienceandengineering |
hierarchy_parent_title |
Faculty of Science and Engineering |
department_str |
School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science |
document_store_str |
0 |
active_str |
0 |
published_date |
2023-06-01T05:33:32Z |
_version_ |
1821291800656084992 |
score |
11.390808 |