We address the problem of finding query facets which are multiple groups of words or phrases that explain and summarize the content covered by a query. We assume that the important aspects of a query are usually presented and repeated in the query’s top retrieved documents in the style of lists, and query facets can be mined out by aggregating these significant lists. We propose a systematic solution, which we refer to as QDMiner, to automatically mine query facets by extracting and grouping frequent lists from free text, HTML tags, and repeat regions within top search results. Experimental results show that a large number of lists do exist and useful query facets can be mined by QDMiner. We further analyze the problem of list duplication, and find better query facets can be mined by modeling fine-grained similarities between lists and penalizing the duplicated lists.

Exisiting Systems

There is only one authority responsible for attribute management and key distribution. This only-one-authority scenario can bring a single-point bottleneck on both security and performance. Once the authority is compromised, an adversary can easily obtain the only-one-authority’s master key, then he/she can generate private keys of any attribute subsetto decrypt the specific encrypted data. Crash or offline of a specific authority will make that private keys of all attributes in attribute subset maintained by this authority cannot be generated and distributed, which will still influence the whole system’s effective operation.

Advantages:

This only-one-authority scenario can bring a single-point bottleneck on both security and performance.

These CP-ABE schemes are still far from being widely used for access control in public cloud storage.

Disadvantages:

Crash or offline of a specific authority will make that private keys of all attributes in attribute subset maintained by this authority cannot be generated and distributed, which will still influence the whole system’s effective operation.

the access structure is not flexible enough to satisfy complex environments. Subsequently,much effort has been made to deal with the disadvantages in the early schemes.

MODULE DESCRIPTION:

In this project, A Robust and Verifiable Threshold Multi-Authority

Access Control System in Public Cloud Storage have three modules .

User module
MultiauthorityAccess control
Public cloud storage.

User Module:

In this module, Users are having authentication and security to access the detail which is presented in the system. Before accessing or searching the details user should have the account in that otherwise they should register first.

Multi-authority Access control:

We conduct a threshold multi-authority CP-ABE access control scheme for

public cloud storage, named TMACS, in which multiple authorities jointly manage a uniform attribute set

To the best of our knowledge, we are the first to design a multiauthority access control architecture to deal with the problem.

To satisfy this hybrid scenario, we conduct a hybrid multi-authority access control scheme, by combining the traditional multi-authority scheme with our proposed TMACS.

Public Cloud Storage:

Cloud storage is an important service of cloud computing which provides services for data owners to outsource data to store in cloud via Internet.

The cloud server is always online and managed by the cloud provider. Usually, the cloud server and its provider is assumed “honest-but-curious”.

The cloud server does nothing but provide a platform for owners storing and sharing their encrypted data.The cloud server doesn’t conduct data access control for owners.

System Configuration:

HARDWARE REQUIREMENTS:

Hardware – Pentium

Speed – 1.1 GHz

RAM – 1GB

Hard Disk – 20 GB

Key Board – Standard Windows Keyboard

Mouse – Two or Three Button Mouse

Monitor – SVGA

Automatically Mining Facets for Queries from Their Search Results