Name
Abstract | ||
|---|---|---|
In the cloud computing environments, a server can handle a lot of data which an individuals cannot process. Therefore, many users upload data to the server and receive the results after computing the uploaded data. In the case of malware detection, the user uploads the suspicious file to the server and checks the file. However, if the file being examined is a document, there is a vulnerability that the data will be exposed to the server. Therefore, In this paper, we propose a computational matching algorithm in encrypted domain. We apply this technique to actual malware detection using the homomorphic encryption. And we measure the detection speed of string signatures with varying lengths and the time to detect string signatures from real malware. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ICTC46691.2019.8939880 | 2019 International Conference on Information and Communication Technology Convergence (ICTC) |
Keywords | Field | DocType |
Homomorphic Encryption,String signature,Pattern matching,Malware detection | Homomorphic encryption,Computer science,Upload,Computer network,Encryption,Malware,Pattern matching,Blossom algorithm,Cloud computing,Malware analysis | Conference |
ISSN | ISBN | Citations |
2162-1233 | 978-1-7281-0894-0 | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Taeyoon Hwang | 1 | 0 | 0.34 |
| Ji Won Yoon | 2 | 112 | 23.94 |