Aggregate Searchable Encryption With Result Privacy

2020 ◽  
Vol 14 (2) ◽  
pp. 62-82
Author(s):  
Dhruti P. Sharma ◽  
Devesh C. Jinwala
Keyword(s):  
Count Data ◽  
Data Extraction ◽  
Searchable Encryption ◽  
Primary Concern ◽  
Conjunctive Query ◽  
Search Query ◽  
Encrypted Data ◽  
Storage Server ◽  
Partial Data ◽  
Aggregate Query

With searchable encryption (SE), the user is allowed to extract partial data from stored ciphertexts from the storage server, based on a chosen query of keywords. A majority of the existing SE schemes support SQL search query, i.e. 'Select * where (list of keywords).' However, applications for encrypted data analysis often need to count data matched with a query, instead of data extraction. For such applications, the execution of SQL aggregate query, i.e. 'Count * where (list of keywords)' at server is essential. Additionally, in case of semi-honest server, privacy of aggregate result is of primary concern. In this article, the authors propose an aggregate searchable encryption with result privacy (ASE-RP) that includes ASearch() algorithm. The proposed ASearch() performs aggregate operation (i.e. Count *) on the implicitly searched ciphertexts (for the conjunctive query) and outputs an encrypted result. The server, due to encrypted form of aggregate result, would not be able to get actual count unless having a decryption key and hence ASearch() offers result privacy.

Aggregate Searchable Encryption With Result Privacy

2021 ◽  
pp. 922-945
Author(s):  
Dhruti P. Sharma ◽  
Devesh C. Jinwala
Keyword(s):  
Data Analysis ◽  
Count Data ◽  
Data Extraction ◽  
Searchable Encryption ◽  
Primary Concern ◽  
Conjunctive Query ◽  
Encrypted Data ◽  
Storage Server ◽  
Partial Data ◽  
Aggregate Query

With searchable encryption (SE), the user is allowed to extract partial data from stored ciphertexts from the storage server, based on a chosen query of keywords. A majority of the existing SE schemes support SQL search query, i.e. 'Select * where (list of keywords).' However, applications for encrypted data analysis often need to count data matched with a query, instead of data extraction. For such applications, the execution of SQL aggregate query, i.e. 'Count * where (list of keywords)' at server is essential. Additionally, in case of semi-honest server, privacy of aggregate result is of primary concern. In this article, the authors propose an aggregate searchable encryption with result privacy (ASE-RP) that includes ASearch() algorithm. The proposed ASearch() performs aggregate operation (i.e. Count *) on the implicitly searched ciphertexts (for the conjunctive query) and outputs an encrypted result. The server, due to encrypted form of aggregate result, would not be able to get actual count unless having a decryption key and hence ASearch() offers result privacy.

scholarly journals Multiuser Searchable Encryption with Token Freshness Verification

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Dhruti Sharma ◽  
Devesh C. Jinwala
Keyword(s):  
Empirical Analysis ◽  
Security Analysis ◽  
Searchable Encryption ◽  
Functional Encryption ◽  
Search Query ◽  
Search Activity ◽  
Replay Attack ◽  
Encrypted Data ◽  
Practical Applications

A Multiuser Searchable Encryption (MUSE) can be defined with the notion of Functional Encryption (FE) where a user constructs a search token from a search key issued by an Enterprise Trusted Authority (ETA). In such scheme, a user possessing search key constructs search token at any time and consequently requests the server to search over encrypted data. Thus, an FE based MUSE scheme is not suitable for the applications where a log of search activities is maintained at the enterprise site to identify dishonest search query from any user. In addition, none of the existing searchable schemes provides security against token replay attack to avoid reuse of the same token. In this paper, therefore we propose an FE based scheme, Multiuser Searchable Encryption with Token Freshness Verification (MUSE-TFV). In MUSE-TFV, a user prepares one-time usable search token in cooperation with ETA and thus every search activity is logged at the enterprise site. Additionally, by verifying the freshness of a token, the server prevents reuse of the token. With formal security analysis, we prove the security of MUSE-TFV against chosen keyword attack and token replay attack. With theoretical and empirical analysis, we justify the effectiveness of MUSE-TFV in practical applications.

scholarly journals EFFICIENT AND EXPRESSIVE KEYWORD SEARCH OVER ENCRYPTED DATA IN CLOUD

2020 ◽  
pp. 145-147
Author(s):  
Zeeshan Sharief
Keyword(s):  
Keyword Search ◽  
Bilinear Pairings ◽  
Searchable Encryption ◽  
Encrypted Data ◽  
Access Structures ◽  
Attribute Based Encryption ◽  
Cloud Server ◽  
Encryption Schemes ◽  
Boolean Formulas ◽  
Significant Performance

Searchable encryption allows a cloud server to conduct keyword search over encrypted data on behalf of the data users without learning the underlying plaintexts. However, most existing searchable encryption schemes only support single or conjunctive keyword search, while a few other schemes that can perform expressive keyword search are computationally inefficient since they are built from bilinear pairings over the composite-order groups. In this paper, we propose an expressive public-key searchable encryption scheme in the prime-order groups, which allows keyword search policies i.e., predicates, access structures to be expressed in conjunctive, disjunctive or any monotonic Boolean formulas and achieves significant performance improvement over existing schemes. We formally define its security and prove that it is selectively secure in the standard model. Also, we implement the proposed scheme using a rapid prototyping tool called Charm and conduct several experiments to evaluate it performance. The results demonstrate that our scheme is much more efficient than the ones built over the composite-order groups. INDEX TERMS - Searchable encryption, cloud computing, expressiveness, attribute-based encryption

Characterization and Clinical Management of Clozapine-Induced Fever

2007 ◽  
Vol 41 (10) ◽  
pp. 1700-1704 ◽  
Author(s):  
Carolina Molina Lowe ◽  
Rebekah R Arthur Grube ◽  
Ann C Scates
Keyword(s):  
English Language ◽  
Treatment Initiation ◽  
Data Extraction ◽  
Drug Discontinuation ◽  
Primary Concern ◽  
High Grade Fever ◽  
Data Synthesis ◽  
Clozapine Therapy ◽  
Study Selection ◽  
Management Recommendations

Objective: To characterize clozapine-induced fever and suggest clinically relevant management recommendations. Data Sources: Literature was accessed through MEDLINE (1966–June 2007) using the terms clozapine, fever, and adverse effects. In addition, reference citations from publications identified were reviewed. Study Selection and Data Extraction: All English-language articles about human studies ot fever associated with the use of clozapine were evaluated. Data Synthesis: Mild to high-grade fever frequently accompanies clozapine therapy. Fever usually occurs within 10–15 days after treatment initiation and has been reported to last between 2 and 4 days. The mechanism and clinical implications of clozapine-induced fever are unclear. The primary concern for clinicians, with regard to these fevers, is the possibility of 2 serious conditions: agranulocytosis with infection or neuroleptic malignant syndrome (NMS). However, the presence of fever during clozapine therapy does not appear to predict agranulocytosis, NMS, or an increased rate of drug discontinuation at 1 year. Conclusions: Available data suggest that clozapine-induced fevers are benign: once infectious and other medical causes for fever are ruled out, clozapine therapy can be continued.

scholarly journals WEB SCALE INFORMATION EXTRACTION USING WRAPPER INDUCTION APPROACH

2014 ◽  
pp. 18-24
Author(s):  
RINA ZAMBAD ◽  
JAYANT GADGE
Keyword(s):  
Information Extraction ◽  
Data Extraction ◽  
Extraction Methods ◽  
Experimental Results ◽  
Search Query ◽  
Wrapper Induction

Information extraction from unstructured, ungrammatical data such as classified listings is difficult because traditional structural and grammatical extraction methods do not apply. The proposed architecture extracts unstructured and un-grammatical data using wrapper induction and show the result in structured format. The source of data will be collected from various post website. The obtained post data pages are processed by page parsing, cleansing and data extraction to obtain new reference sets. Reference sets are used for mapping the user search query, which improvised the scale of search on unstructured and ungrammatical post data. We validate our approach with experimental results.

Sign in / Sign up

Export Citation Format

Share Document