- San Francisco CA, US Ray Zhang - San Jose CA, US
Assignee:
Dropbox, Inc - San Francisco CA
International Classification:
G06F 21/56 H04L 29/06
Abstract:
Disclosed are systems, methods, and non-transitory computer-readable storage media for identifying malware based on content item identifiers. For example, a system for detecting malware can be made more efficient by reducing the number of content items that are scanned or analyzed for malicious software code or computer instructions. The number of content items that need to be scanned can be reduced by identifying suspicious content items based on tokens (e.g., strings of characters) commonly used by malware in the identifiers of malware related content items and then analyzing the identified suspicious content items for malicious content (e.g., malicious software instructions) using the anti-malware software.
Identifying Malware Based On Content Item Identifiers
- San Francisco CA, US Ray Zhang - San Jose CA, US
International Classification:
G06F 21/56 H04L 29/06
Abstract:
Disclosed are systems, methods, and non-transitory computer-readable storage media for identifying malware based on content item identifiers. For example, a system for detecting malware can be made more efficient by reducing the number of content items that are scanned or analyzed for malicious software code or computer instructions. The number of content items that need to be scanned can be reduced by identifying suspicious content items based on tokens (e.g., strings of characters) commonly used by malware in the identifiers of malware related content items and then analyzing the identified suspicious content items for malicious content (e.g., malicious software instructions) using the anti-malware software.
- San Francisco CA, US Anton MITYAGIN - San Francisco CA, US Ray ZHANG - San Jose CA, US Sam KELLER - Millbrae CA, US Stacey SERN - Edison NJ, US
International Classification:
G06F 21/56 G06F 9/44
Abstract:
Disclosed are systems, methods, and non-transitory computer-readable storage media for malware detection and content item recovery. For example, a content management system can receive information describing changes made to content items stored on a user device. The content management system can analyze the information to determine if the described changes are related to malicious software on the user device. When the changes are related to malicious software, the content management system can determine which content items are effected by the malicious software and/or determine when the malicious software first started making changes to the user device. The content management system can recover effected content items associated with the user device by replacing the effected versions of the content items with versions of the content items that existed immediately before the malicious software started making changes to the user device.