| Title | Security Patterns from Intelligent Data: A Map of Software Vulnerability Analysis |
| Authors | Sun, Jinan Pan, Kefeng Chen, Xuefeng Zhang, Junfu |
| Affiliation | National Engineering Research Center for Software Engineering, Peking University, Beijing, China Westone Information Industry Co.,Ltd, Beijing, China Beida Software Engineering Co.,Ltd, Beijing, China |
| Issue Date | 2017 |
| Publisher | 3rd IEEE International Conference on Big Data Security on Cloud, BigDataSecurity 2017, 3rd IEEE International Conference on High Performance and Smart Computing, HPSC 2017 and 2nd IEEE International Conference on Intelligent Data and Security, IDS 2017 |
| Citation | 3rd IEEE International Conference on Big Data Security on Cloud, BigDataSecurity 2017, 3rd IEEE International Conference on High Performance and Smart Computing, HPSC 2017 and 2nd IEEE International Conference on Intelligent Data and Security, IDS 2017. 2 |
| Abstract | A significant milestone is reached when the field of software vulnerability research matures to a point warranting related security patterns represented by intelligent data. A substantial research material of empirical findings, distinctive taxonomy, theoretical models, and a set of novel or adapted detection methods justify a unifying research map. The growth interest in software vulnerability is evident from a large number of works done during the last several decades. This article briefly reviews research works in vulnerability enumeration, taxonomy, models and detection methods from the perspective of intelligent data processing and analysis. This article also draws the map which associated with specific characteristics and challenges of vulnerability research, such as vulnerability patterns representation and problem-solving strategies. ? 2017 IEEE. |
| URI | http://hdl.handle.net/20.500.11897/505037 |
| ISSN | 9781509062959 |
| DOI | 10.1109/BigDataSecurity.2017.9 |
| Indexed | EI |
| Appears in Collections: | 软件工程国家工程研究中心 |
