Enabling Verifiable and Dynamic Ranked Search Over Outsourced Data

A secure and dynamic multi keyword ranked search scheme over encrypted cloud ...

2016 list

This document lists 2016 IEEE projects related to cloud computing and data mining/knowledge engineering. It includes 15 projects on secure and efficient cloud computing technologies such as keyword search, data sharing, auditing, and access control schemes. It also includes 8 projects on location-aware keyword queries, sentiment analysis, spatial keyword search, privacy-preserving location services, and approximate nearest neighbor queries over graph databases.

A secure and dynamic multi keyword ranked search scheme over encrypted cloud ...

We are the company providing Complete Solution for all Academic Final Year/Semester Student Projects. Our projects are suitable for B.E (CSE,IT,ECE,EEE), B.Tech (CSE,IT,ECE,EEE),M.Tech (CSE,IT,ECE,EEE) B.sc (IT & CSE), M.sc (IT & CSE), MCA, and many more..... We are specialized on Java,Dot Net ,PHP & Andirod technologies. Each Project listed comes with the following deliverable: 1. Project Abstract 2. Complete functional code 3. Complete Project report with diagrams 4. Database 5. Screen-shots 6. Video File SERVICE AT CLOUDTECHNOLOGIES IEEE, WEB, WINDOWS PROJECTS ON DOT NET, JAVA& ANDROID TECHNOLOGIES,EMBEDDED SYSTEMS,MAT LAB,VLSI DESIGN. ME, M-TECH PAPER PUBLISHING COLLEGE TRAINING Thanks&Regards cloudtechnologies # 304, Siri Towers,Behind Prime Hospitals Maitrivanam, Ameerpet. Contact:-8121953811,8522991105.040-65511811 cloudtechnologiesprojects@gmail.com http://cloudstechnologies.in/

A secure and dynamic multi keyword ranked search scheme over encrypted cloud ...

A secure and dynamic multi keyword ranked

jpstudcorner

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The document proposes a solution called privacy-preserving multi-keyword ranked search over encrypted cloud data (MRSE) that allows searching encrypted data stored in the cloud using multiple keywords. It establishes privacy requirements for such a system and uses an efficient "coordinate matching" similarity measure to determine relevance between search queries and documents. It first presents a basic MRSE scheme based on secure inner product computation, then improves upon it with two schemes that achieve different privacy levels while introducing low overhead on computation and communication as shown by experiments on real-world datasets.

Privacy preserving multi-keyword ranked search over encrypted cloud data

A secure and dynamic multi keyword ranked search scheme over encrypted cloud ...

Pvrtechnologies Nellore

This document proposes a secure multi-keyword ranked search scheme over encrypted cloud data that allows for dynamic operations like deletion and insertion of documents. It constructs a special tree-based index structure and uses a "Greedy Depth-first Search" algorithm to provide efficient search. The scheme utilizes a secure kNN algorithm to encrypt index and query vectors while still allowing accurate relevance scoring between encrypted vectors. It aims to achieve sub-linear search time and flexible handling of document updates.

A secure and dynamic multi keyword ranked search scheme over encrypted cloud ...

LeMeniz Infotech

A secure and dynamic multi keyword ranked search scheme over encrypted cloud data Do Your Projects With Technology Experts To Get this projects Call : 9566355386 / 99625 88976 Visit : www.lemenizinfotech.com / www.ieeemaster.com Mail : projects@lemenizinfotech.com Blog : http://ieeeprojectspondicherry.weebly.com Blog : http://www.ieeeprojectsinpondicherry.blogspot.in/ Youtube:https://www.youtube.com/watch?v=eesBNUnKvws

Privacy-Preserving Multi-keyword Top-k Similarity Search Over Encrypted Data

Combining efficiency, fidelity, and flexibility in resource information services

ieeepondy

This document proposes an LSH-based resource information service (LIS) that aims to achieve high efficiency, fidelity and flexibility for resource discovery in large-scale distributed systems like collaborative cloud computing. It presents three algorithms to transform resource descriptions into integers and uses min-wise independent permutations to build LSH functions. Simulation and experimental results on PlanetLab show the proposed service outperforms other approaches in terms of efficiency, fidelity and flexibility by significantly reducing overhead.

Accurate and Efficient Secured Dynamic Multi-keyword Ranked Search

Dakshineshwar Swain

The document presents a project on developing an "accurate and efficient dynamic multi-keyword ranked search scheme". It aims to address issues with searching encrypted data outsourced to the cloud. The proposed system uses a tree-based index structure and "Greedy Depth-first Search" algorithm to improve search efficiency. It also utilizes TF-IDF scores to rank documents by relevance to search terms. The project aims to provide a searchable encryption scheme that supports accurate, efficient multi-keyword searches and dynamic operations on document collections.

MongoDB .local London 2019: Best Practices for Working with IoT and Time-seri...

MongoDB

Time series data is increasingly at the heart of modern applications - think IoT, stock trading, clickstreams, social media, and more. With the move from batch to real time systems, the efficient capture and analysis of time series data can enable organizations to better detect and respond to events ahead of their competitors or to improve operational efficiency to reduce cost and risk. Working with time series data is often different from regular application data, and there are best practices you should observe. This talk covers: Common components of an IoT solution • The challenges involved with managing time-series data in IoT applications • Different schema designs, and how these affect memory and disk utilization – two critical factors in application performance. • How to query, analyze and present IoT time-series data using MongoDB Compass and MongoDB Charts • At the end of the session, you will have a better understanding of key best practices in managing IoT time-series data with MongoDB.

A SECURE AND DYNAMIC MULTI-KEYWORD RANKED SEARCH SCHEME OVER ENCRYPTED CLOUD...

Nexgen Technology

bulk ieee projects in pondicherry,ieee projects in pondicherry,final year ieee projects in pondicherry Nexgen Technology Address: Nexgen Technology No :66,4th cross,Venkata nagar, Near SBI ATM, Puducherry. Email Id: praveen@nexgenproject.com. www.nexgenproject.com Mobile: 9751442511,9791938249 Telephone: 0413-2211159. NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km

Privacy preserving multi-keyword ranked search over encrypted cloud data

Enabling secure and efficient ranked keyword

IMPULSE_TECHNOLOGY

This document proposes a system for enabling secure and efficient ranked keyword search over outsourced cloud data. It summarizes that existing searchable encryption techniques only support basic Boolean search and do not consider relevance ranking. The proposed system explores using relevance scores from information retrieval to build a searchable index and develops a one-to-many order-preserving mapping technique to protect sensitive score information, allowing efficient server-side ranking without compromising keyword privacy. The system provides ranked search results while maintaining strong security guarantees.

Webinar elastic stack {on telecom} english webinar part (1)

Yassine, LASRI

Telecoms network consists of hundreds of network elements that generate call detail records or event data for each phone call, text message, internet activity, or even a simple walk from one location to another. The number of records per day varies between millions and billions. In many cases, the network elements are from different vendors. The typical interface to access these records is file-based. Communication services providers want to analyze these records to run campaigns, improve user experience, improve network or call center, or to detect fraud. They need a system that unifies source data, runs near real-time analytics, and scales with increasing network traffic. Join our upcoming webinar to discover how we power telecom analytics using the Elastic Stack, an open source, scalable & distributed, reliably and securely take data from any source, in any format, then search, analyze, and visualize it in real time. Elastic Stack is a group of open source products from Elastic designed to help users take data from any type of source and in any format and search, analyze, and visualize that data in real time. The product group was formerly known as ELK Stack, in which the letters in the name stood for the products in the group: Elasticsearch, Logstash and Kibana. A fourth product, Beats, was subsequently added to the stack, rendering the potential acronym unpronounceable. Elastic Stack can be deployed on premises or made available as Software as a Service (SaaS).

Privacy preserving multi-keyword ranked search over encrypted cloud data

Privacy preserving multi-keyword ranked search over encrypted cloud data

This document proposes a system called privacy-preserving multi-keyword ranked search over encrypted cloud data (MRSE). Existing searchable encryption systems only support single-keyword or boolean keyword search without result ranking. The proposed MRSE system allows a user to search for multiple keywords and returns documents ranked by relevance. It establishes privacy requirements and uses an efficient "coordinate matching" semantic to quantify document similarity based on keyword matches. The system architecture includes modules for data owners to encrypt and upload files, for users to search and download encrypted files, and for ranking search results.

Webinar: Rearchitecting Storage for the Next Wave of Splunk Data Growth

Storage Switzerland

Privacy preserving multi-keyword ranked search over encrypted cloud data

Alex G. Lee, Ph.D. Esq. CLP

Sensordaten analysieren mit Docker, CrateDB und Grafana

Claus Matzinger

Predictive analytics, Internet of Things, Industrie 4.0: Begriffe, die in aller Munde sind. Wie aber sehen echte Installationen aus? Wie können containerbasierte Microservices den Deploymentprozess vereinfachen und gleichzeitig die Produktivität erhöhen? Claus Matzinger von Crate.io wird in diesem Vortrag all diese Fragen beantworten und mittels Raspberry Pis, Grafana und Rust einige Best Practices aus der "echten Welt" vorstellen.

Fuzzy Keyword Search Over Encrypted Data in Cloud Computing

IJERA Editor

As Cloud Computing becomes prevalent, more and more sensitive information are being centralized into the cloud. For the protection of data privacy, sensitive data usually have to be encrypted before outsourcing, which makes effective data utilization a very challenging task. Although traditional searchable encryption schemes allow a user to securely search over encrypted data through keywords and selectively retrieve files of interest, these techniques support only exact keyword search. This significant drawback makes existing techniques unsuitable in cloud computing as it is greatly affect system usability, rendering user searching experiences very frustrating and system efficiency very low. In this paper, for the first time we formalize and solve the problem of effective fuzzy keyword search over encrypted cloud while maintaining keyword privacy. In our solution, we exploit edit distance to quantify keyword similarity and develop new advanced technique on constructing fuzzy keyword sets which greatly reduces the storage and representation overheads. In this way, we show that our proposed solution is secure and privacy preserving, while realizing the goal of fuzzy keyword search.

Press release

John Lathouwers

Xanadu Based Big Data CBIR System:Automated Astronomical Objects Classificati...

NEW SECURE CONCURRECY MANEGMENT APPROACH FOR DISTRIBUTED AND CONCURRENT ACCES...

ijiert bestjournal

Handover the critical data to the cloud provider sh ould have the guarantee of security and availabilit y for data at rest,in motion,and in use. Many alternatives sys tems exist for storage services,but the data confi dentiality in the database as a service paradigm are still immature. We propose a novel architecture that integrates clo ud database services paradigm with data confidentiality and exe cuting concurrent operations on encrypted data. Thi s is the method supporting geographically distributed client s to connect directly and access to an encrypted cl oud database,and to execute concurrent and independent operation s by using modifying the database structure. The proposed architecture has also the more advanta ge of removing intermediate proxies that limit the flexibility,availability,and expandability properties that are inbuilt in cloud-based systems. The efficacy of th e proposed architecture is evaluated by theoretical analyses a nd extensive experimental results with the help of prototype implementation related to the TPC-C standard benchm ark for various categories of clients and network l atencies. We propose a multi-keyword ranked search method for the encrypted cloud data databases,which simultan eously fulfill the needs of privacy requirements. The prop osed scheme could return not only the exact matchin g files,but also the files including the terms latent semantica lly associated to the query keyword.

M.E Computer Science Cloud Computing Projects

Vijay Karan

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