Privacy-Preserving Multi-keyword Ranked
Search over Encrypted Cloud Data
ABSTRACT
The advent of cloud computing, data owners are motivated to outsource their complex
data management systems from local sites to commercial public cloud for great flexibility and
economic savings. But for protecting data privacy, sensitive data has to be encrypted before
outsourcing, which obsoletes traditional data utilization based on plaintext keyword search.
Thus, enabling an encrypted cloud data search service is of paramount importance. Considering
the large number of data users and documents in cloud, it is crucial for the search service to
allow multi-keyword query and provide result similarity ranking to meet the effective data
retrieval need. Related works on searchable encryption focus on single keyword search or
Boolean keyword search, and rarely differentiate the search results. We define and solve the
challenging problem of privacy-preserving multi-keyword ranked search over encrypted cloud
data (MRSE), and establish a set of strict privacy requirements for such a secure cloud data
utilization system to become a reality. Among various multi-keyword semantics, we choose the
efficient principle of “coordinate matching”, its many matches as possible, to capture the
similarity between search query and data documents, and further use “inner product similarity”
to quantitatively formalize such principle for similarity measurement. We first propose a basic
MRSE scheme using secure inner product computation, and then significantly improve it to meet
different privacy requirements in two levels of threat models. Thorough analysis investigating
privacy and efficiency guarantees of proposed schemes is given, and experiments on the realworld dataset further show proposed schemes indeed introduce low overhead on computation
and communication.
EXISTING SYSTEM
The encryption is a helpful technique that treats encrypted data as documents and allows
a user to securely search over it through single keyword and retrieve documents of interest. The
direct application of these approaches to deploy secure large scale cloud data utilization system
would not be necessarily suitable, as they are developed as crypto primitives and cannot
accommodate such high service-level requirements like system usability, user searching
experience, and easy information discovery in mind.
Disadvantage:
 Large scale cloud utilization gets less security
 Service level is not ell for users
PROPOSED SYSTEM
In this project, define and solve the problem of multi-keyword ranked search over
encrypted cloud data (MRSE) while preserving strict system-wise privacy in cloud computing
paradigm. Among various multi-keyword semantics, we choose the efficient principle of
“coordinate matching”, it many matches as possible, to capture the similarity between search
query and data documents. Specifically, we use “inner product similarity”, the number of query
keywords appearing in a document, to quantitatively evaluate the similarity of that document to
the search query in “coordinate matching” principle.
To improve various privacy requirements in two levels of threat models. The first time,
we explore the problem of multi keyword ranked search over encrypted cloud data, and establish
a set of strict privacy requirements for such a secure cloud data utilization system to become a
reality. The propose two MRSE schemes following the principle of “coordinate matching” while
meeting different privacy requirements in two levels of threat models. Thorough analysis
investigating privacy and efficiency guarantees of proposed schemes is given, and experiments
on the real-world dataset further show proposed schemes indeed introduce low overhead on
computation and communication.
Advantage:
 Multi key word ranking for secure the cloud data
 Searching on the encrypted data will give an expected data
SYSTEM MODELS
HARDWARE REQUIREMENT
CPU type
:
Intel Pentium 4
Clock speed
:
3.0 GHz
Ram size
: 512 MB
Hard disk capacity
:
40 GB
Monitor type
:
15 Inch color monitor
Keyboard type
:
internet keyboard
SOFTWARE REQUIREMENT
O p e r a t i n g S ys t e m : A n d r o i d
Language
: JAVA
Back End
:
SQLite
Documentation
:
Ms-Office
MODULES
I. server




Network checking
Data encrypt
Store to cloud server
Send decrypted key to user
II. Cloud server



Retrieve request from user
Searching index/rank calculation
Response to user
III. User



Request to cloud server
Retrieve decrypted key from admin & document from cloud server
Decrypt file
MODULE DESCRIPTIONS
I. Server
The server maintain the following process,
Network checking
Initializing the server to check the network connection from cloud server and user. The
connections are successfully, and then the processes are executed.
Data encrypt
The main server first encrypts the data’s, and then stored the cloud server. Cloud server is
considered as “honest-but-curious” in our model, which is consistent with the most related works
on searchable encryption. Specifically, cloud server acts in an “honest” fashion and correctly
follows the designated protocol specification.
Store to cloud server
The cloud server collects the some different encrypted documents. In this process
encrypted data to store with cloud server. Search result should be ranked by cloud. The cloud
server according to some ranking criteria.
Send decrypted key to user
The main server encrypts the some documents. It used by the some encryptions keys.
Finally the users search the document from the cloud server.
II. Cloud server
The cloud server maintain the process,
Retrieve request from user
The anyone user wants to request the data and then server able to send the user request.
The retrieve the data from server to user.
Searching index/rank calculation
On the one hand, to meet the effective data retrieval need, large amount of documents
demand cloud server to perform result relevance ranking, instead of returning undifferentiated
result. Ranked search can also elegantly eliminate unnecessary network traffic by sending back
only the most relevant data.
Response to user
The server response to users request with the rank and index estimation while search a
document in cloud.
III. User
The user maintain the following process,
Request to cloud server
The client request for our needs send to cloud server. Specifically, cloud server acts in an
“honest” fashion and correctly follows the designated protocol specification.
Retrieve decrypted key from admin & document from cloud server
All encrypted key data to send to admin of the cloud server, the admin to take the
encrypted data. Then all the data to store in cloud server.
Decrypt file
The trivial solution of downloading all the data and decrypting locally is clearly
impractical, due to the huge amount of bandwidth cost in cloud scale systems. The access control
mechanism is employed to manage decryption capabilities given to users.
Work flow diagram:
Rank Result
Encrypted data Index
Search request
Cloud server
Search control
Data User
Data owner
Access Control
CONCLUSION
We define and solve the problem of multi-keyword ranked search over encrypted cloud
data, and begin a variety of privacy requirements. Among different multi-keyword semantics, we
choose the efficient principle of “coordinate matching”, as many matches as possible, to
effectively capture similarity between query keywords and outsourced documents, and use “inner
product similarity” to quantitatively formalize such a principle for similarity measurement. For
meeting the challenge of supporting multi-keyword semantic without privacy breaches, the
propose a basic MRSE scheme using secure inner product computation, and significantly
improve it to achieve privacy requirements in two levels of threat models. Thorough analysis
investigating privacy and efficiency guarantees of proposed schemes is given, and experiments
on the real-world dataset show our proposed schemes introduce low overhead on both
computation and communication.