Network computer security hidden dangers and vulnerability mining technology Article Swipe
Chao Wang
,
Tianyu Ren
,
Qun Li
,
Xiaohu Wang
,
Guangxin Guo
,
Jiahan Dong
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1088/1757-899x/750/1/012155
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1088/1757-899x/750/1/012155
With the development of computer technology and communication technology, computer network will increasingly become an important means of information exchange, and permeate into every field of social life. However, the network has the potential threat and the reality existence each kind of security question, therefore we must take the strong security policy to ensure the network security. The purpose of this paper is to study the network computer security hidden trouble and vulnerability mining technology. In this paper, the types of security hidden dangers are analyzed, and the vulnerability detection technology Fuzzing technology is deeply studied. Then, the inspection and test time is analyzed for the existing vulnerability detection tools. The experimental results prove that vulnerability detection technology can protect network security with high efficiency of vulnerability detection. In this paper, three vulnerability detection tools WS Fuzzer, Web Fuzz and Webvul Scan were used to analyze the detection time of open source system, personal blog, shopping mall and forum. The average detection time was 1.9s, 8.7s, 20.5s and 59.7s, respectively. It can be seen that the vulnerability mining technology has a certain practical role.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1757-899x/750/1/012155
- OA Status
- diamond
- Cited By
- 5
- References
- 14
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3013322370
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3013322370Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1088/1757-899x/750/1/012155Digital Object Identifier
- Title
-
Network computer security hidden dangers and vulnerability mining technologyWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-02-01Full publication date if available
- Authors
-
Chao Wang, Tianyu Ren, Qun Li, Xiaohu Wang, Guangxin Guo, Jiahan DongList of authors in order
- Landing page
-
https://doi.org/10.1088/1757-899x/750/1/012155Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1088/1757-899x/750/1/012155Direct OA link when available
- Concepts
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Vulnerability (computing), Vulnerability management, Computer security, Vulnerability assessment, Computer science, Fuzz testing, Network security, Field (mathematics), Information security, Software, Programming language, Pure mathematics, Psychological resilience, Psychology, Mathematics, PsychotherapistTop concepts (fields/topics) attached by OpenAlex
- Cited by
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5Total citation count in OpenAlex
- Citations by year (recent)
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2024: 2, 2023: 1, 2022: 1, 2021: 1Per-year citation counts (last 5 years)
- References (count)
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14Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.ensure | 54 |
| abstract_inverted_index.forum. | 159 |
| abstract_inverted_index.hidden | 70, 83 |
| abstract_inverted_index.mining | 74, 178 |
| abstract_inverted_index.paper, | 78, 131 |
| abstract_inverted_index.policy | 52 |
| abstract_inverted_index.social | 27 |
| abstract_inverted_index.source | 152 |
| abstract_inverted_index.strong | 50 |
| abstract_inverted_index.threat | 35 |
| abstract_inverted_index.tools. | 110 |
| abstract_inverted_index.Fuzzer, | 137 |
| abstract_inverted_index.Fuzzing | 92 |
| abstract_inverted_index.analyze | 146 |
| abstract_inverted_index.average | 161 |
| abstract_inverted_index.certain | 182 |
| abstract_inverted_index.dangers | 84 |
| abstract_inverted_index.network | 11, 31, 56, 67, 121 |
| abstract_inverted_index.protect | 120 |
| abstract_inverted_index.purpose | 59 |
| abstract_inverted_index.reality | 38 |
| abstract_inverted_index.results | 113 |
| abstract_inverted_index.system, | 153 |
| abstract_inverted_index.trouble | 71 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.However, | 29 |
| abstract_inverted_index.analyzed | 104 |
| abstract_inverted_index.computer | 5, 10, 68 |
| abstract_inverted_index.existing | 107 |
| abstract_inverted_index.permeate | 22 |
| abstract_inverted_index.personal | 154 |
| abstract_inverted_index.security | 43, 51, 69, 82, 122 |
| abstract_inverted_index.shopping | 156 |
| abstract_inverted_index.studied. | 96 |
| abstract_inverted_index.analyzed, | 86 |
| abstract_inverted_index.detection | 90, 109, 117, 134, 148, 162 |
| abstract_inverted_index.exchange, | 20 |
| abstract_inverted_index.existence | 39 |
| abstract_inverted_index.important | 16 |
| abstract_inverted_index.potential | 34 |
| abstract_inverted_index.practical | 183 |
| abstract_inverted_index.question, | 44 |
| abstract_inverted_index.security. | 57 |
| abstract_inverted_index.therefore | 45 |
| abstract_inverted_index.detection. | 128 |
| abstract_inverted_index.efficiency | 125 |
| abstract_inverted_index.inspection | 99 |
| abstract_inverted_index.technology | 6, 91, 93, 118, 179 |
| abstract_inverted_index.development | 3 |
| abstract_inverted_index.information | 19 |
| abstract_inverted_index.technology, | 9 |
| abstract_inverted_index.technology. | 75 |
| abstract_inverted_index.experimental | 112 |
| abstract_inverted_index.increasingly | 13 |
| abstract_inverted_index.communication | 8 |
| abstract_inverted_index.respectively. | 170 |
| abstract_inverted_index.vulnerability | 73, 89, 108, 116, 127, 133, 177 |
| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5075922236, https://openalex.org/A5100730344 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile.value | 0.59701493 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |