Name
Abstract | ||
|---|---|---|
Rich and fine personal and enterprise data are being collected and recorded, so as to provide big data support for personal and enterprise credit evaluation and credit integration. In this process, the problem of data privacy is becoming more and more prominent. For example, the user's location data may be used to infer address, behavior and activity, and the user's service use records may reveal information such as gender, age and disease. How to protect data privacy while meeting the needs of credit evaluation and credit integration is one of the great challenges in the era of big data. In this paper, we propose a security privacy protection framework in artificial intelligence algorithm, analyze the possibility of privacy leakage from data privacy security, model privacy security and environment privacy security, and give the corresponding defense strategy. In addition, this paper also gives an example algorithm of data security level, which can ensure the security of data privacy. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1007/978-3-030-86130-8_23 | WIRELESS ALGORITHMS, SYSTEMS, AND APPLICATIONS, WASA 2021, PT II |
Keywords | DocType | Volume |
Privacy protection framework, Credit data, Privacy-preserved, Differential private, AI security | Conference | 12938 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Con-Gdong Lv | 1 | 0 | 0.34 |
| Xiaodong Zhang | 2 | 0 | 0.34 |
| Zhoubao Sun | 3 | 0 | 0.34 |