Encrypted Keyword Search Mechanism Based on Bitmap Index for Personal Storage Services

2014 ◽  
Author(s):  
Yong Ho Hwang ◽  
Jae Woo Seo ◽  
Il Joo Kim
Keyword(s):  
Keyword Search ◽  
Bitmap Index ◽  
Search Mechanism

Dynamic Verifiable Encrypted Keyword Search Using Bitmap Index and Homomorphic MAC

2017 ◽  
Author(s):  
Rajkumar Ramasamy ◽  
S. Sree Vivek ◽  
Praveen George ◽  
Bharat S. Rawal Kshatriya
Keyword(s):  
Keyword Search ◽  
Bitmap Index ◽  
Homomorphic Mac

scholarly journals Se-PKSE: Secure Public-Key Searchable Encryption for Cloud-Assisted Lightweight Platforms

2021 ◽  
Author(s):  
Israt Jahan Mouri ◽  
Muhammad Ridowan ◽  
Muhammad Abdullah Adnan
Keyword(s):  
Keyword Search ◽  
Comprehensive Evaluation ◽  
Searchable Encryption ◽  
Public Key ◽  
Cloud Data ◽  
Interactive Search ◽  
Search Mechanism ◽  
Iot Devices ◽  
Index Tree ◽  
Data Usability

Abstract Since more and more data from lightweight platforms like IoT devices are being outsourced to the cloud, the need to ensure privacy while retaining data usability is important. Encrypting documents before uploading to the cloud, ensures privacy but reduces data usability. Searchable encryption, specially public-key searchable encryption (PKSE), allows secure keyword search in the cloud over encrypted documents uploaded from IoT devices. However, most existing PKSE schemes focus on returning all the files that match the queried keyword, which is not practical. To achieve a secure, practical, and efficient keyword search, we design a dynamic ranked PKSE framework over encrypted cloud data named \textit{Secure Public-Key Searchable Encryption} (Se-PKSE). We leverage a partially homomorphically encrypted index tree structure that provides sub-linear ranked search capability and allows dynamic insertion/deletion of documents without the owner storing any document details. An interactive search mechanism is introduced between the user and the cloud to eliminate trapdoors from the search request to ensure search keyword privacy and forward privacy. Finally, we implement a prototype of Se-PKSE and test it in the Amazon EC2 for practicality using the RFC dataset. The comprehensive evaluation demonstrates that Se-PKSE is efficient and secure for practical deployment.

On the search mechanism in problem solving

1960 ◽  
Author(s):  
W. S. Ray
Keyword(s):  
Problem Solving ◽  
Search Mechanism

Machine Learning of Motor Vehicle Accident Categories from Narrative Data

1996 ◽  
Vol 35 (04/05) ◽  
pp. 309-316 ◽  
Author(s):  
M. R. Lehto ◽  
G. S. Sorock
Keyword(s):  
Machine Learning ◽  
Bayesian Model ◽  
Keyword Search ◽  
Motor Vehicle ◽  
Motor Vehicle Accident ◽  
Computer Search ◽  
Vehicle Accident ◽  
Learning Technique ◽  
Expert Ratings ◽  
Keyword Searches

Abstract:Bayesian inferencing as a machine learning technique was evaluated for identifying pre-crash activity and crash type from accident narratives describing 3,686 motor vehicle crashes. It was hypothesized that a Bayesian model could learn from a computer search for 63 keywords related to accident categories. Learning was described in terms of the ability to accurately classify previously unclassifiable narratives not containing the original keywords. When narratives contained keywords, the results obtained using both the Bayesian model and keyword search corresponded closely to expert ratings (P(detection)≥0.9, and P(false positive)≤0.05). For narratives not containing keywords, when the threshold used by the Bayesian model was varied between p>0.5 and p>0.9, the overall probability of detecting a category assigned by the expert varied between 67% and 12%. False positives correspondingly varied between 32% and 3%. These latter results demonstrated that the Bayesian system learned from the results of the keyword searches.

Evaluation of Keyword Search System with Ranking

2015 ◽  
Vol 03 (03) ◽  
pp. 1462-1466
Author(s):  
P.Saranya, D r.S.Babu
Keyword(s):  
Keyword Search ◽  
Search System

Efficient XML Keyword Search Using H-Reduction Factor and Interactive Algorithm

2014 ◽  
Vol 9 (12) ◽  
pp. 2022 ◽  
Author(s):  
A. Mary Posonia ◽  
V. L. Jyothi
Keyword(s):  
Keyword Search ◽  
Reduction Factor ◽  
Xml Keyword Search ◽  
Interactive Algorithm
Sign in / Sign up

Export Citation Format

Share Document