Article
A LOCATION-AWARE FRAMEWORK FOR DETECTING SUSPICIOUS FILE MIGRATION IN CLOUD
Cloud storage has become widely popular due to its flexibility and convenience, but users often have no control over the actual location of their data, which raises concerns about security and trust. To address this issue, the proposed system, LAST-HDFS, integrates Location-Aware Storage Technique with Hadoop Distributed File System. It ensures that sensitive data is stored only within user-defined legal boundaries. The system continuously monitors file migration and replication across cloud nodes to detect suspicious or illegal transfers. File movements are modeled using weighted graph algorithms to group data with similar privacy requirements in the same region. Each cloud node uses a socket monitor to track real-time communication and data transfer activities. Based on this real-time information, the system calculates the probability of illegal file movement. Experimental results in a large-scale cloud environment with 50 nodes and 10,000 migration events show that the proposed system achieves 96.3% detection accuracy with 2.1% false positive rate, demonstrating effectiveness in improving cloud data security and trust
Full Text Attachment
