Supporting dynamic update scheme for assured deletion based-multicopy association tree
Cloud storage services provide storage resources for resource-constrained users, which reduces their local overhead and computing cost. As an extension of cloud computing, fog computing introduces a fog layer between the cloud and users to deploy computing, storage, and other types of equipment, allowing users to operate outsourced data conveniently. Although cloud storage brings many conveniences to users, assured data deletion is still one of the crucial security challenges. This paper proposes an efficient and secure cloud data deletion scheme (SDUS-AD) that supports dynamic data updates in multi-copy scenarios. In this scheme, a new dynamic structure called Multi-Copy Association Tree is designed to realize the dynamic update of outsourced data efficiently and safely. A cloud-fog-user layer structure is used to meet the needs of resource-constrained users to update data and ensure the confidentiality of data privacy. Detailed performance analysis and simulation experiments show that SDUS-AD is efficient, safe, and feasible.
Code (0)
등록된 구현이 없습니다.
Tasks
Cloud ComputingSimilar Papers 제목 키워드 기반
In-Place Updates of a Graph Index for Streaming Approximate Nearest Neighbor Search
Indices for approximate nearest neighbor search (ANNS) are a basic component for information retrieval and widely used in database, search, recommendation and RAG systems. In these scenarios, documents or other objects a…
Information RetrievalRAGSublinear Update Time Randomized Algorithms for Dynamic Graph Regression
A well-known problem in data science and machine learning is {\em linear regression}, which is recently extended to dynamic graphs. Existing exact algorithms for updating the solution of dynamic graph regression require …
Graph RegressionregressionProximity Graph Maintenance for Fast Online Nearest Neighbor Search
Approximate Nearest Neighbor (ANN) search is a fundamental technique for (e.g.,) the deployment of recommender systems. Recent studies bring proximity graph-based methods into practitioners' attention -- proximity graph-…
QuantizationRecommendation SystemsGraph-based Nearest Neighbors with Dynamic Updates via Random Walks
Approximate nearest neighbor search (ANN) is a common way to retrieve relevant search results, especially now in the context of large language models and retrieval augmented generation. One of the most widely used algori…
Descent-to-Delete: Gradient-Based Methods for Machine Unlearning
We study the data deletion problem for convex models. By leveraging techniques from convex optimization and reservoir sampling, we give the first data deletion algorithms that are able to handle an arbitrarily long seque…
Machine Unlearning