Data Mining has wide applications in many areas such as banking, medicine, scientific research and among government agencies. Classification is one of the commonly used tasks in data mining applications.
DYNAMIC AND PUBLIC AUDITING WITH FAIR ARBITRATION FOR CLOUD DATANexgen Technology
TO GET THIS PROJECT COMPLETE SOURCE ON SUPPORT WITH EXECUTION PLEASE CALL BELOW CONTACT DETAILS
MOBILE: 9791938249, 0413-2211159, WEB: WWW.NEXGENPROJECT.COM,WWW.FINALYEAR-IEEEPROJECTS.COM, EMAIL:Praveen@nexgenproject.com
NEXGEN TECHNOLOGY provides total software solutions to its customers. Apsys works closely with the customers to identify their business processes for computerization and help them implement state-of-the-art solutions. By identifying and enhancing their processes through information technology solutions. NEXGEN TECHNOLOGY help it customers optimally use their resources.
Enabling efficient multi keyword ranked search over encrypted mobile cloud da...LeMeniz Infotech
Enabling efficient multi keyword ranked search over encrypted mobile cloud data through blind storage
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
DYNAMIC AND PUBLIC AUDITING WITH FAIR ARBITRATION FOR CLOUD DATANexgen Technology
TO GET THIS PROJECT COMPLETE SOURCE ON SUPPORT WITH EXECUTION PLEASE CALL BELOW CONTACT DETAILS
MOBILE: 9791938249, 0413-2211159, WEB: WWW.NEXGENPROJECT.COM,WWW.FINALYEAR-IEEEPROJECTS.COM, EMAIL:Praveen@nexgenproject.com
NEXGEN TECHNOLOGY provides total software solutions to its customers. Apsys works closely with the customers to identify their business processes for computerization and help them implement state-of-the-art solutions. By identifying and enhancing their processes through information technology solutions. NEXGEN TECHNOLOGY help it customers optimally use their resources.
Enabling efficient multi keyword ranked search over encrypted mobile cloud da...LeMeniz Infotech
Enabling efficient multi keyword ranked search over encrypted mobile cloud data through blind storage
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
Accurate and Efficient Secured Dynamic Multi-keyword Ranked SearchDakshineshwar Swain
A practically efficient and flexible searchable encrypted scheme which supports multi-keyword ranked search. To support multi-keyword search and result relevance ranking, we adopt Vector Space Model (VSM) to build the searchable index to achieve accurate search result.
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
DN18 | Ocean Protocol – Empowering a Decentralized Marketplace for The New AI...Dataconomy Media
Abstract of the Presentation:
Ocean Protocol is a non-profit foundation designing and implementing a decentralized data marketplace. Ocean Protocol aims to break down data silos through equitable, universal, and secure access.
The problem: Large companies have a data advantage in the ongoing AI revolution. With huge amounts data feeding AI models, there is an incentive to keep this data in-house and gain a competitive advantage. Given that more data often yields better AI, there are solutions which smaller companies and innovators can unlock if they had access to more data.
The solution: Ocean Protocol tackles this challenge with a decentralized marketplace for data and AI services. Data providers are incentivised to open their data, and data consumers will gain seamless access to a new world of data, be it big data from a large corporation, or an aggregate of small datasets.
This talk will demo the features available to Data Engineers, how you can partake in the decentralized data and AI ecosystem, and the roadmap until Ocean Protocol’s Ethereum main-net release.
About the Author:
Marcus Jones is the lead Data Scientist at Ocean Protocol, a Blockchain decentralized marketplace for data and models supporting the AI ecosystem. Marcus has been hacking in Python development and and Open Source projects for over 10 years, starting at the national research agency in Vienna, moving into international project management and consulting, and landing now in Berlin at Ocean Protocol. Marcus is focused on the intersection of Artificial Intelligence and the new decentralized Web 3.0 ecosystem, and how it can empower Data Engineers and Data Scientists.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
Decentralised AI through Distributed Ledger Technologies Gokul Alex
My seminar lecture session on Decentralised AI through Distributed Ledger Technologies in the second National Seminar on Machine Intelligence organised by University of Kerala, Department of Computer Science on 24th January 2020. I have covered the foundations of distributed ledger technologies, decentralisation roadmap, decentralised AI and decentralised data exchanges in this session.
Graphs or Networks are becoming more mainstream after Google and Facebook have shown how Graphs can be leveraged to create business value. Heterogenous information networks is a concept that I found interesting to represent nodes and relationships of different kinds. The researchers that are doing a lot of research in this area are Jiawei Han and Yizhou Sun and googling them will bring up one of their books.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
With the growth of cloud technologies, computing
resources and cloud storage have become the most
demanding online services. There are several companies
desiring to outsource their data storage and resources as
well. While storing private and sensitive data on a third
party data center, it is necessary to consider security and
privacy which become major issues. In this paper, a novel
Double Encryption with Single Decryption (DESD) crypto
technique is proposed to secure the data in cloud storage.
The proposed technique comprises of encryption and
decryption phases where in the encryption phase the data is
randomly partitioned into multiple fragments. Double
encryption is done on each fragment by prime numbers, as
well as Invertible Non-linear Function (INF). These
multiple encrypted data are stored at the multiple cloud
storages with the help of cloud service provider (CSP).
After all verification process the data user collects the key
from the data owner and decrypts the gathered data from
the cloud with the knowledge of inverse INF. The proposed
crypto technique provides more security and privacy to
cloud data and any illegitimate users cannot retrieve the
original data. The performance of the proposed DESD
technique is compared with AES and Triple DES
techniques and the experimental results are plotted which
shows the proposed technique is efficient and faster.
Data Anonymization for Privacy Preservation in Big Datarahulmonikasharma
Cloud computing provides capable ascendable IT edifice to provision numerous processing of a various big data applications in sectors such as healthcare and business. Mainly electronic health records data sets and in such applications generally contain privacy-sensitive data. The most popular technique for data privacy preservation is anonymizing the data through generalization. Proposal is to examine the issue against proximity privacy breaches for big data anonymization and try to recognize a scalable solution to this issue. Scalable clustering approach with two phase consisting of clustering algorithm and K-Anonymity scheme with Generalisation and suppression is intended to work on this problem. Design of the algorithms is done with MapReduce to increase high scalability by carrying out dataparallel execution in cloud. Wide-ranging researches on actual data sets substantiate that the method deliberately advances the competence of defensive proximity privacy breaks, the scalability and the efficiency of anonymization over existing methods. Anonymizing data sets through generalization to gratify some of the privacy attributes like k- Anonymity is a popularly-used type of privacy preserving methods. Currently, the gauge of data in numerous cloud surges extremely in agreement with the Big Data, making it a dare for frequently used tools to actually get, manage, and process large-scale data for a particular accepted time scale. Hence, it is a trial for prevailing anonymization approaches to attain privacy conservation for big data private information due to scalabilty issues.
Block chain is probably one of the technologies that has the potential to disrupt several business models. We are looking at Graph Analytics of temporal Graphs can help us see how a block chain ledger, network and an account changes over time.
Applying Blockchain Technology for Digital TransformationGokul Alex
My virtual webinar session on applying Blockchain Technology for Digital Transformation of Contemporary Business Models in the UL Talks Series organised by ULTS, the IT Subsidiary of ULCCS. This presentation is a journey through the basic concepts of Blockchain Technology and a compilation of interesting business cases around Blockchain Technology.
1croreprojects is the best hybrid cloud system for all area and also developing realtime projects, phd projects are fully developed in our institute. We have been effectively in providing solutions for different challenges across a wide range of market and customers propagate across the globe.
3rd International Conference on Big Data and Blockchain (BDAB 2022)ijcisjournal
3rd International Conference on Big Data and Blockchain (BDAB 2022) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Big Data and Blockchain. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Big Data and Blockchain.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
User-Centric Evaluation of a K-Furthest Neighbor Collaborative Filtering Reco...Alan Said
Collaborative filtering recommender systems often use nearest neighbor methods to identify candidate items. In this paper we present an inverted neighborhood model, k-Furthest Neighbors, to identify less ordinary neighborhoods for the purpose of creating more diverse recommendations. The approach is evaluated two-fold, once in a traditional information retrieval evaluation setting where the model is trained and validated on a split train/test set, and once through an online user study (N=132) to identify users’ erceived quality of the recommender. A standard k-nearest neighbor recommender is used as a baseline in both evaluation settings. our evaluation shows that even though the proposed furthest neighbor model is outperformed in the traditional evaluation setting, the perceived usefulness of the algorithm shows no significant difference in the results of the user study.
Extended Performance Appraise of Image Retrieval Using the Feature Vector as ...Waqas Tariq
The extension to the content based image retrieval (CBIR) technique based on row mean of transformed columns of image is presented here. As compared to earlier contemplation three image transforms, now the performance appraise of proposed CBIR technique is done using seven different image transforms like Discrete Cosine Transform (DCT), Discrete Sine Transform (DST), Hartley Transform, Haar Transform, Kekre Transform, Walsh Transform and Slant Transform. The generic image database with 1000 images spread across 11 categories is used to test the performance of proposed CBIR techniques. For each transform 55 queries (5 per category) were fired on the image database. Every technique is tested on both the color and grey version of image database. To compare the performance of image retrieval technique across transforms average precision and recall are computed of all queries. The results have shown the performance improvement (higher precision and recall values) with proposed methods compared to all pixel data of image at reduced computations resulting in faster retrieval in both gray as well as color versions of image database. Even the variation of considering DC component of transformed columns as part of feature vector and excluding it are also tested and it is found that presence of DC component in feature vector improvises the results in image retrieval. The ranking of transforms for performance in proposed gray CBIR techniques with DC component consideration can be given as DST, Haar, Hartley, DCT, Walsh, Slant and Kekre. In color variants of proposed techniques with DC component, the performance ranking of image transforms starting from best can be listed as DCT, Haar, Walsh, Slant, DST, Hartley and Kekre transform.
Accurate and Efficient Secured Dynamic Multi-keyword Ranked SearchDakshineshwar Swain
A practically efficient and flexible searchable encrypted scheme which supports multi-keyword ranked search. To support multi-keyword search and result relevance ranking, we adopt Vector Space Model (VSM) to build the searchable index to achieve accurate search result.
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
DN18 | Ocean Protocol – Empowering a Decentralized Marketplace for The New AI...Dataconomy Media
Abstract of the Presentation:
Ocean Protocol is a non-profit foundation designing and implementing a decentralized data marketplace. Ocean Protocol aims to break down data silos through equitable, universal, and secure access.
The problem: Large companies have a data advantage in the ongoing AI revolution. With huge amounts data feeding AI models, there is an incentive to keep this data in-house and gain a competitive advantage. Given that more data often yields better AI, there are solutions which smaller companies and innovators can unlock if they had access to more data.
The solution: Ocean Protocol tackles this challenge with a decentralized marketplace for data and AI services. Data providers are incentivised to open their data, and data consumers will gain seamless access to a new world of data, be it big data from a large corporation, or an aggregate of small datasets.
This talk will demo the features available to Data Engineers, how you can partake in the decentralized data and AI ecosystem, and the roadmap until Ocean Protocol’s Ethereum main-net release.
About the Author:
Marcus Jones is the lead Data Scientist at Ocean Protocol, a Blockchain decentralized marketplace for data and models supporting the AI ecosystem. Marcus has been hacking in Python development and and Open Source projects for over 10 years, starting at the national research agency in Vienna, moving into international project management and consulting, and landing now in Berlin at Ocean Protocol. Marcus is focused on the intersection of Artificial Intelligence and the new decentralized Web 3.0 ecosystem, and how it can empower Data Engineers and Data Scientists.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
Decentralised AI through Distributed Ledger Technologies Gokul Alex
My seminar lecture session on Decentralised AI through Distributed Ledger Technologies in the second National Seminar on Machine Intelligence organised by University of Kerala, Department of Computer Science on 24th January 2020. I have covered the foundations of distributed ledger technologies, decentralisation roadmap, decentralised AI and decentralised data exchanges in this session.
Graphs or Networks are becoming more mainstream after Google and Facebook have shown how Graphs can be leveraged to create business value. Heterogenous information networks is a concept that I found interesting to represent nodes and relationships of different kinds. The researchers that are doing a lot of research in this area are Jiawei Han and Yizhou Sun and googling them will bring up one of their books.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
With the growth of cloud technologies, computing
resources and cloud storage have become the most
demanding online services. There are several companies
desiring to outsource their data storage and resources as
well. While storing private and sensitive data on a third
party data center, it is necessary to consider security and
privacy which become major issues. In this paper, a novel
Double Encryption with Single Decryption (DESD) crypto
technique is proposed to secure the data in cloud storage.
The proposed technique comprises of encryption and
decryption phases where in the encryption phase the data is
randomly partitioned into multiple fragments. Double
encryption is done on each fragment by prime numbers, as
well as Invertible Non-linear Function (INF). These
multiple encrypted data are stored at the multiple cloud
storages with the help of cloud service provider (CSP).
After all verification process the data user collects the key
from the data owner and decrypts the gathered data from
the cloud with the knowledge of inverse INF. The proposed
crypto technique provides more security and privacy to
cloud data and any illegitimate users cannot retrieve the
original data. The performance of the proposed DESD
technique is compared with AES and Triple DES
techniques and the experimental results are plotted which
shows the proposed technique is efficient and faster.
Data Anonymization for Privacy Preservation in Big Datarahulmonikasharma
Cloud computing provides capable ascendable IT edifice to provision numerous processing of a various big data applications in sectors such as healthcare and business. Mainly electronic health records data sets and in such applications generally contain privacy-sensitive data. The most popular technique for data privacy preservation is anonymizing the data through generalization. Proposal is to examine the issue against proximity privacy breaches for big data anonymization and try to recognize a scalable solution to this issue. Scalable clustering approach with two phase consisting of clustering algorithm and K-Anonymity scheme with Generalisation and suppression is intended to work on this problem. Design of the algorithms is done with MapReduce to increase high scalability by carrying out dataparallel execution in cloud. Wide-ranging researches on actual data sets substantiate that the method deliberately advances the competence of defensive proximity privacy breaks, the scalability and the efficiency of anonymization over existing methods. Anonymizing data sets through generalization to gratify some of the privacy attributes like k- Anonymity is a popularly-used type of privacy preserving methods. Currently, the gauge of data in numerous cloud surges extremely in agreement with the Big Data, making it a dare for frequently used tools to actually get, manage, and process large-scale data for a particular accepted time scale. Hence, it is a trial for prevailing anonymization approaches to attain privacy conservation for big data private information due to scalabilty issues.
Block chain is probably one of the technologies that has the potential to disrupt several business models. We are looking at Graph Analytics of temporal Graphs can help us see how a block chain ledger, network and an account changes over time.
Applying Blockchain Technology for Digital TransformationGokul Alex
My virtual webinar session on applying Blockchain Technology for Digital Transformation of Contemporary Business Models in the UL Talks Series organised by ULTS, the IT Subsidiary of ULCCS. This presentation is a journey through the basic concepts of Blockchain Technology and a compilation of interesting business cases around Blockchain Technology.
1croreprojects is the best hybrid cloud system for all area and also developing realtime projects, phd projects are fully developed in our institute. We have been effectively in providing solutions for different challenges across a wide range of market and customers propagate across the globe.
3rd International Conference on Big Data and Blockchain (BDAB 2022)ijcisjournal
3rd International Conference on Big Data and Blockchain (BDAB 2022) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Big Data and Blockchain. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Big Data and Blockchain.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
User-Centric Evaluation of a K-Furthest Neighbor Collaborative Filtering Reco...Alan Said
Collaborative filtering recommender systems often use nearest neighbor methods to identify candidate items. In this paper we present an inverted neighborhood model, k-Furthest Neighbors, to identify less ordinary neighborhoods for the purpose of creating more diverse recommendations. The approach is evaluated two-fold, once in a traditional information retrieval evaluation setting where the model is trained and validated on a split train/test set, and once through an online user study (N=132) to identify users’ erceived quality of the recommender. A standard k-nearest neighbor recommender is used as a baseline in both evaluation settings. our evaluation shows that even though the proposed furthest neighbor model is outperformed in the traditional evaluation setting, the perceived usefulness of the algorithm shows no significant difference in the results of the user study.
Extended Performance Appraise of Image Retrieval Using the Feature Vector as ...Waqas Tariq
The extension to the content based image retrieval (CBIR) technique based on row mean of transformed columns of image is presented here. As compared to earlier contemplation three image transforms, now the performance appraise of proposed CBIR technique is done using seven different image transforms like Discrete Cosine Transform (DCT), Discrete Sine Transform (DST), Hartley Transform, Haar Transform, Kekre Transform, Walsh Transform and Slant Transform. The generic image database with 1000 images spread across 11 categories is used to test the performance of proposed CBIR techniques. For each transform 55 queries (5 per category) were fired on the image database. Every technique is tested on both the color and grey version of image database. To compare the performance of image retrieval technique across transforms average precision and recall are computed of all queries. The results have shown the performance improvement (higher precision and recall values) with proposed methods compared to all pixel data of image at reduced computations resulting in faster retrieval in both gray as well as color versions of image database. Even the variation of considering DC component of transformed columns as part of feature vector and excluding it are also tested and it is found that presence of DC component in feature vector improvises the results in image retrieval. The ranking of transforms for performance in proposed gray CBIR techniques with DC component consideration can be given as DST, Haar, Hartley, DCT, Walsh, Slant and Kekre. In color variants of proposed techniques with DC component, the performance ranking of image transforms starting from best can be listed as DCT, Haar, Walsh, Slant, DST, Hartley and Kekre transform.
A Parallel Architecture for Multiple-Face Detection Technique Using AdaBoost ...Hadi Santoso
Face detection is a very important biometric application in the field of image
analysis and computer vision. The basic face detection method is AdaBoost
algorithm with a cascading Haar-like feature classifiers based on the
framework proposed by Viola and Jones. Real-time multiple-face detection,
for instance on CCTVs with high resolution, is a computation-intensive
procedure. If the procedure is performed sequentially, an optimal real-time
performance will not be achieved. In this paper we propose an architectural
design for a parallel and multiple-face detection technique based on Viola
and Jones' framework. To do this systematically, we look at the problem
from 4 points of view, namely: data processing taxonomy, parallel memory
architecture, the model of parallel programming, as well as the design of
parallel program. We also build a prototype of the proposed parallel
technique and conduct a series of experiments to investigate the gained
acceleration.
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/sept-2014-member-meeting-scottkrig
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Scott Krig, author of the book "Computer Vision Metrics: Survey, Taxonomy, and Analysis," delivers the presentation "Introduction to Feature Descriptors in Vision: From Haar to SIFT" at the September 2014 Embedded Vision Alliance Member Meeting.
Approximate nearest neighbor methods and vector models – NYC ML meetupErik Bernhardsson
Nearest neighbors refers to something that is conceptually very simple. For a set of points in some space (possibly many dimensions), we want to find the closest k neighbors quickly.
This presentation covers a library called Annoy built my me that that helps you do (approximate) nearest neighbor queries in high dimensional spaces. We're going through vector models, how to measure similarity, and why nearest neighbor queries are useful.
Project report on ONLINE REAL ESTATE BUSINESSDivyesh Shah
A project report on 'online real estate' will help you to understand the modeling diagrams for this project and all type of information related to this project
The Field of Human Resource Management is developing very fast and every department of Human activity is realizing it’s important in the smooth functioning of the organization. Innovative techniques are developed to improve the culture at workplace so that the employees are motivated to give in their best to the organization as also to attain job satisfaction. Hence, it important implements the latest human resource practices in the organization.
The Latest Techniques in the field of Human Resource Development are Employees for Lease, Moon Lighting by Employees, Dual Career Group, Work Life Balance (flexi time & flexi work), Training & Development, Management Participation in Employees’ organization, Employee’s Proxy, Human Resources Accounting, Organizational Politics, Exit Policy & Practice, etc.
This project is about WORK LIFE BALANCE. A latest technique in the field of a human resource. To see how the organization is adopting the new trends in the HR field.
Enabling fine grained multi-keyword search supporting classified sub-dictiona...Shakas Technologies
Using cloud computing, individuals can store their data on remote servers and allow data access to public users through the cloud servers. As the outsourced data are likely to contain sensitive privacy information, they are typically encrypted before uploaded to the cloud.
Enabling fine grained multi-keyword search supporting classified sub-dictiona...Shakas Technologies
Using cloud computing, individuals can store their data on remote servers and allow data access to public users through the cloud servers. As the outsourced data are likely to contain sensitive privacy information, they are typically encrypted before uploaded to the cloud.
We provide a generic framework that, with the help of a preprocessing phase that is independent of the inputs of the users, allows an arbitrary number of users to securely outsource a computation to two non-colluding external servers.
Secure two party differentially private data release for vertically partition...Shakas Technologies
Privacy-preserving data publishing addresses the problem of disclosing sensitive data when mining for useful information. Among the existing privacy models, _-differential privacy provides one of the strongest privacy guarantees.
Secure and distributed data discovery and dissemination in wireless sensor ne...Shakas Technologies
A data discovery and dissemination protocol for wireless sensor networks (WSNs) is responsible for updating configuration parameters of, and distributing management commands to, the sensor nodes. All existing data discovery and dissemination protocols suffer from two drawbacks.
Data is a technique for eliminating duplicate copies of data, and has been widely used in cloud storage to reduce storage space and upload bandwidth. However, there is only one copy for each file stored in cloud even if such a file is owned by a huge number of users. As a result, system improves storage utilization while reducing reliability
We provide a generic framework that, with the help of a preprocessing phase that is independent of the inputs of the users, allows an arbitrary number of users to securely outsource a computation to two non-colluding external servers.
We propose a mediated certificateless encryption scheme without pairing operations for securely sharing sensitive information in public clouds. Mediated certificateless public key encryption (mCL-PKE) solves the key escrow problem in identity based encryption and certificate revocation problem in public key cryptography.
We propose a new design for large-scale multimedia content protection systems. Our design leverages cloud infrastructures to provide cost efficiency, rapid deployment, scalability, and elasticity to accommodate varying workloads
Key updating for leakage resiliency with application to aes modes of operationShakas Technologies
Side-channel analysis (SCA) exploits the information leaked through unintentional outputs (e.g., power consumption) to reveal the secret key of cryptographic modules. The real threat of SCA lies in the ability to mount attacks over small parts of the key and to aggregate information over different encryptions.
Key updating for leakage resiliency with application to aes modes of operationShakas Technologies
Side-channel analysis (SCA) exploits the information leaked through unintentional outputs (e.g., power consumption) to reveal the secret key of cryptographic modules. The real threat of SCA lies in the ability to mount attacks over small parts of the key and to aggregate information over different encryptions.
Similar to K nearest neighbor classification over semantically secure encrypted (20)
A Personal Privacy Data Protection Scheme for Encryption and Revocation of Hi...Shakas Technologies
A Personal Privacy Data Protection Scheme for Encryption and Revocation of High-Dimensional Attri
Shakas Technologies ( Galaxy of Knowledge)
#11/A 2nd East Main Road,
Gandhi Nagar,
Vellore - 632006.
Mobile : +91-9500218218 / 8220150373| land line- 0416- 3552723
Shakas Training & Development | Shakas Sales & Services | Shakas Educational Trust|IEEE projects | Research & Development | Journal Publication |
Email : info@shakastech.com | shakastech@gmail.com |
website: www.shakastech.com
Facebook: https://www.facebook.com/pages/Shakas-Technologies
Detecting Mental Disorders in social Media through Emotional patterns-The cas...Shakas Technologies
Detecting Mental Disorders in social Media through Emotional patterns-The case of Anorexia and depression
Shakas Technologies ( Galaxy of Knowledge)
#11/A 2nd East Main Road,
Gandhi Nagar,
Vellore - 632006.
Mobile : +91-9500218218 / 8220150373| land line- 0416- 3552723
Shakas Training & Development | Shakas Sales & Services | Shakas Educational Trust|IEEE projects | Research & Development | Journal Publication |
Email : info@shakastech.com | shakastech@gmail.com |
website: www.shakastech.com
Facebook: https://www.facebook.com/pages/Shakas-Technologies
CO2 EMISSION RATING BY VEHICLES USING DATA SCIENCE
Shakas Technologies ( Galaxy of Knowledge)
#11/A 2nd East Main Road,
Gandhi Nagar,
Vellore - 632006.
Mobile : +91-9500218218 / 8220150373| land line- 0416- 3552723
Shakas Training & Development | Shakas Sales & Services | Shakas Educational Trust|IEEE projects | Research & Development | Journal Publication |
Email : info@shakastech.com | shakastech@gmail.com |
website: www.shakastech.com
Facebook: https://www.facebook.com/pages/Shakas-Technologies
Identifying Hot Topic Trends in Streaming Text Data Using News Sequential Evo...Shakas Technologies
Identifying Hot Topic Trends in Streaming Text Data Using News Sequential Evolution Model Based on Distributed Representations.
Shakas Technologies ( Galaxy of Knowledge)
#11/A 2nd East Main Road,
Gandhi Nagar,
Vellore - 632006.
Mobile : +91-9500218218 / 8220150373| land line- 0416- 3552723
Shakas Training & Development | Shakas Sales & Services | Shakas Educational Trust|IEEE projects | Research & Development | Journal Publication |
Email : info@shakastech.com | shakastech@gmail.com |
website: www.shakastech.com
Facebook: https://www.facebook.com/pages/Shakas-Technologies
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Epistemic Interaction - tuning interfaces to provide information for AI support
K nearest neighbor classification over semantically secure encrypted
1. 1.
#13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, vellore – 6.
Off: 0416-2247353 / 6066663 Mo: +91 9500218218 /8870603602,
Project Titles: http://shakastech.weebly.com/2015-2016-titles
Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com
K-NEAREST NEIGHBOR CLASSIFICATION OVER SEMANTICALLY SECURE
ENCRYPTED RELATIONAL DATA
ABSTRACT:
Data Mining has wide applications in many areas such as banking, medicine, scientific
research and among government agencies. Classification is one of the commonly used tasks in
data mining applications. For the past decade, due to the rise of various privacy issues, many
theoretical and practical solutions to the classification problem have been proposed under
different security models. However, with the recent popularity of cloud computing, users now
have the opportunity to outsource their data, in encrypted form, as well as the data mining tasks
to the cloud. Since the data on the cloud is in encrypted form, existing privacy-preserving
classification techniques are not applicable. In this paper, we focus on solving the classification
problem over encrypted data. In particular, we propose a secure k-NN classifier over encrypted
data in the cloud. The proposed protocol protects the confidentiality of data, privacy of user’s
input query, and hides the data access patterns. To the best of our knowledge, our work is the
first to develop a secure k-NN classifier over encrypted data under the semi-honest model. Also,
we empirically analyze the efficiency of our proposed protocol using a real world dataset under
different parameter settings
2. 1.
#13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, vellore – 6.
Off: 0416-2247353 / 6066663 Mo: +91 9500218218 /8870603602,
Project Titles: http://shakastech.weebly.com/2015-2016-titles
Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com
EXISTING SYSTEM:
Existing work on Privacy-Preserving Data Mining (either perturbation or secure multi-
party computation based approach) cannot solve the DMED problem. Perturbed data do not
possess semantic security, so data perturbation techniques cannot be used to encrypt highly
sensitive data. Also the perturbed data do not produce very accurate data mining results. Secure
multi-party computation (SMC) based approach assumes data are distributed and not encrypted
at each participating party.
PROPOSED SYSTEM:
We focus on solving the classification problem over encrypted data. In particular, we
propose a secure k-NN classifier over encrypted data in the cloud. The proposed protocol
protects the confidentiality of data, privacy of user’s input query, and hides the data access
patterns. To the best of our knowledge, our work is the first to develop a secure k-NN classifier
over encrypted data under the semi-honest model. Also, we empirically analyze the efficiency of
our proposed protocol using a real-world dataset under different parameter settings. We proposed
novel methods to effectively solve the DMED problem assuming that the encrypted data are
outsourced to a cloud. Specifically, we focus on the classification problem since it is one of the
most common data mining tasks. Because each classification technique has their own advantage,
to be concrete, this paper concentrates on executing the knearest neighbor classification method
over encrypted data in the cloud computing environment.
3. 1.
#13/ 19, 1st Floor, Municipal Colony, Kangayanellore Road, Gandhi Nagar, vellore – 6.
Off: 0416-2247353 / 6066663 Mo: +91 9500218218 /8870603602,
Project Titles: http://shakastech.weebly.com/2015-2016-titles
Website: www.shakastech.com, Email - id: shakastech@gmail.com, info@shakastech.com
HARDWARE REQUIREMENTS:
• System : Pentium IV 2.4 GHz.
• Hard Disk : 40 GB.
• Floppy Drive : 1.44 Mb.
• Monitor : 15 VGA Colour.
• Mouse : Logitech.
• RAM : 256 Mb.
SOFTWARE REQUIREMENTS:
• Operating system : - Windows XP.
• Front End : - JSP
• Back End : - SQL Server