Wednesday 27 December 2017

An Efficient and Fine-grained Big Data Access Control Scheme with Privacy-preserving Policy|M-Tech 2017 Projects

Cloud Technologies Hyderabad

An Efficient and Fine-grained Big Data Access Control Scheme with Privacy-preserving Policy


Implementation Video Of An Efficient and Fine-grained Big Data Access Control Scheme with Privacy-preserving Policy

IEEE 2017-2018 Java Projects


SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

An Internal Intrusion Detection and Protection System by Using Data Mining and Forensic Techniques|IEEE 2017 Projects

Cloud Technologies Hyderabad

An Internal Intrusion Detection and Protection System by Using Data Mining and Forensic Techniques


Implementation Video Of An Internal Intrusion Detection and Protection System by Using Data Mining and Forensic Techniques

IEEE 2017-2018 Java Projects


SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

Wednesday 6 December 2017

Provably Secure Key-Aggregate Cryptosystems with Broadcast Aggregate Keys for Online Data Sharing on the Cloud | IEEE-2017 Projects

Cloud Technologies Hyderabad

Provably Secure Key-Aggregate Cryptosystems with Broadcast Aggregate Keys for Online Data Sharing on the Cloud


Implementation Video Of Provably Secure Key-Aggregate Cryptosystems with Broadcast Aggregate Keys for Online Data Sharing on the Cloud

IEEE 2017-2018 Java Projects


SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

Thursday 30 November 2017

TAFC: Time and Attribute Factors Combined Access Control for Time-Sensitive Data in Public Cloud

Cloud Technologies Hyderabad

TAFC: Time and Attribute Factors Combined Access Control for Time-Sensitive Data in Public Cloud


Implementation Video Of TAFC: Time and Attribute Factors Combined Access Control for Time-Sensitive Data in Public Cloud

IEEE 2017-2018 Java Projects


SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

Thursday 23 November 2017

Collaborative Filtering-Based Recommendation of Online Social Voting IEEE-2017 Project

Cloud Technologies Hyderabad

Collaborative Filtering-Based Recommendation of Online Social Voting


Implementation Video Of Collaborative Filtering-Based Recommendation of Online Social Voting

IEEE 2017-2018 Java Projects


SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

Monday 20 November 2017

SeDaSC: Secure Data Sharing in Clouds-IEEE-2017 Projects

Cloud Technologies Hyderabad

SeDaSC: Secure Data Sharing in Clouds


Implementation Video Of SeDaSC: Secure Data Sharing in Clouds

IEEE 2017-2018 Java Projects


SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

Saturday 4 November 2017

Identity-based Remote Data Integrity Checking with Perfect Data Privacy Preserving for Cloud Storage IEEE 2017-2018 Projects

Cloud Technologies Hyderabad

Identity-based Remote Data Integrity Checking with Perfect Data Privacy Preserving for Cloud Storage


Implementation Video Of Identity-based Remote Data Integrity Checking with Perfect Data Privacy Preserving for Cloud Storage

IEEE 2017-2018 Java Projects


SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

Sunday 29 October 2017

Social Q&A: An Online Social Network Based Question and Answer System

Cloud Technologies Hyderabad

Social Q&A: An Online Social Network Based Question and Answer System


Implementation Video Of Social Q&A: An Online Social Network Based Question and Answer System

IEEE 2017-2018 Java Projects


SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

Thursday 5 October 2017

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

Cloud Technologies Hyderabad

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


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

IEEE 2017-2018 Java Projects


SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

Wednesday 4 October 2017

A Novel Efficient Remote Data Possession Checking Protocol in Cloud Storage | IEEE 2017 Project | M-Tech Project | B-Tech Project

Cloud Technologies Hyderabad

A Novel Efficient Remote Data Possession Checking Protocol in Cloud Storage

Abstract As an important application in cloud computing, cloud storage offers user scalable, flexible and high quality data storage and computation services. A growing number of data owners choose to outsource data files to the cloud. Because cloud storage servers are not fully trustworthy, data owners need dependable means to check the possession for their files outsourced to remote cloud servers. To address this crucial problem, some remote data possession checking (RDPC) protocols have been presented. But many existing schemes have vulnerabilities in efficiency or data dynamics. In this paper, we provide a new efficient RDPC protocol based on holomorphic hash function. The new scheme is provably secure against forgery attack, replace attack and replay attack based on a typical security model. To support data dynamics, an operation record table (ORT) is introduced to track operations on file blocks. We further give a new optimized implementation for the ORT which makes the cost of accessing ORT nearly constant. Moreover, we make the comprehensive performance analysis which shows that our scheme has advantages in computation and communication costs. Information security, sometimes shortened to InfoSec, is the practice of preventing unauthorized access, use, disclosure, disruption, modification, inspection, recording or destruction of information. It is a general term that can be used regardless of the form the data may take (e.g. electronic, physical). Network security consists of the policies and practices adopted to prevent and monitor unauthorized access, misuse, modification, or denial of a computer network and network-accessible resources. Network security involves the authorization of access to data in a network, which is controlled by the network administrator. Users choose or are assigned an ID and password or other authenticating information that allows them access to information and programs within their authority. Network security covers a variety of computer networks, both public and private, that are used in everyday jobs; conducting transactions and communications among businesses, government agencies and individuals. Networks can be private, such as within a company, and others which might be open to public access. Network security is involved in organizations, enterprises, and other types of institutions. It does as its title explains: It secures the network, as well as protecting and overseeing operations being done. The most common and simple way of protecting a network resource is by assigning it a unique name and a corresponding password.
Existing System
Cloud service provider tries to provide a promising service for data storage, which saves the users costs of investment and resource. Nonetheless, cloud storage also brings various s security issues for the outsourced data. Although some security problems have been solved the important challenges of data tampering and data lost still exist in cloud storage. On the one hand, the accident disk error or hardware failure of the cloud storage server (CSS) may cause the unexpected corruption of outsourced files. On the other hand, the CSS is not fully trustworthy from the perspective of the data owner; it may actively delete or modify files for tremendous economic benefits. At the same time, CSS may hide the misbehaviors and data loss accidents from data owner to maintain a good reputation.
DISADVANTAGES • It is crucial for the data owner to utilize an efficient way to check the integrity for outsourced data. • In addition, they supplied two concrete schemes (S-PDP, E-PDP) based on RSA. Although these two protocols had good performance, it's a pity they didn't support dynamic operations. • Does not provide efficiency in remote data integrity checking. • More expensive. • The existing system provides less flexibility.
PROPOSED SYSTEM
It is essential for data owners to verify the integrity for the data stored on CSS before using it. For example, a big international trading company stores all the imports and exports record files on CSS. According to these files, the company can get the key information such as the logistics quantity, the trade volume etc. If any record file is discarded or tampered, the company will suffer from a big loss which may cause bad influence on its business and development. To avoid this kind of circumstances, it is mandatory to check the integrity for outsourced data files. Furthermore, since these files may refer to business secret, any information exposure is unacceptable. If the company competitor can execute the file integrity checking, by frequently checking the files they may obtain some useful information such as when the file changes, the growth rate of the file etc, by which they can guess the development of the company. Thus, to avoid this situation, we consider the private verification type in our scheme, that is, the data owner is the unique verifier. In fact, the current research direction of RDPC focuses on the public verification, in which anyone can perform the task of file integrity checking with the system public key. Although RDPC with public verification seems better than that with private verification, but it is unsuitable to the scenario mentioned above. Motivated by the above application scenarios, we present a novel efficient RDPC scheme by using homomorphic hash function , which has been used to construct RDPC schemes . Unfortunately, these schemes are either insecure or not efficient enough. To overcome these drawbacks, we refer to the idea of and introduce a private key for each tag generation in our RDPC scheme. Simultaneously, a new construction of ORT is presented for data dynamic which can improve the efficiency of the protocol greatly. Compared with the previous ones, our scheme has better performance in term of computation and communication. Our contributions are summarized as follows: We present a novel efficient dynamics. The basic scheme utilizes homomorphic hash function technique, in which the hash value of the sum for two blocks is equal to the product for two hash values of the corresponding blocks. We introduce a linear table called ORT to record data operations for supporting data dynamics such as block modification, block insertion and block deletion. To improve the efficiency for accessing ORT, we make use of doubly linked list and array to present an optimized implementation of ORT which reduces the cost to nearly constant level. We prove the presented scheme is secure against forgery attack, replay attack and replace attack based on a typical security model. At last we implement our scheme and make thorough comparison with previous schemes. Experiment results show that the new scheme has better performance and is practical for real applications.
Future Work:
In future work we are implementing de-duplication Technique for found duplicate file have in cloud. Because in the above System we are doing RDPC Technique to Data integrity. So it is degrade the system performance by doing for duplicate files. To improve system performance we will find duplicate file before upload in cloud, once if we found any duplicate file from cloud then this enhancing system does not allow to store in cloud. Advantages: 1. We can reduce the storage space. 2. We can save network round trips. For finding duplicate file we use SHA-256 algorithm for generating Hash Code for checking cloud with any file is matched. SYSTEM CONFIGURATION: Hardware requirements: Processer : Any Update Processer Ram : Min 1 GB Hard Disk : Min 100 GB Software requirements: Operating System : Windows family Technology : Java (1.7/1.8) Web Technologies : Html, Html-5, JavaScript, CSS. Web Server : Tomcat 7/8 Server side Lang : J2EE Database : My SQL5.5 UML : Star UML DFD : DFD Drawer Implemented by Development team : Cloud Technologies Website : http://www.cloudstechnologies.in Contact : 8121953811, 040-65511811

Monday 2 October 2017

Robust and Auditable Access Control With Multiple Attribute Authorities for Public Cloud Storage

Cloud Technologies Hyderabad

Robust and Auditable Access Control With Multiple Attribute Authorities for Public Cloud Storage


Implementation Video Of Robust and Auditable Access Control With Multiple Attribute Authorities for Public Cloud Storage

IEEE 2017-2018 Java Projects


SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

Tuesday 19 September 2017

NetSpam a Network-based Spam Detection Framework for Reviews in Online Social Media

Cloud Technologies Hyderabad

NetSpam a Network-based Spam Detection Framework for Reviews in Online Social Media


Implementation Video Of NetSpam a Network-based Spam Detection Framework for Reviews in Online Social Media

IEEE 2017-2018 Java Projects


SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

Wednesday 13 September 2017

M-Tech Projects NetSpam: a Network-based Spam Detection Framework for Reviews in Online Social Media

Cloud Technologies Hyderabad

NetSpam: a Network-based Spam Detection Framework for Reviews in Online Social Media


Abstract:

Abstract—Nowadays, a big part of people rely on available content in social media in their decisions (e.g. reviews and feedback on a topic or product). The possibility that anybody can leave a review provide a golden opportunity for spammers to write spam reviews about products and services for different interests. Identifying these spammers and the spam content is a hot topic of research and although a considerable number of studies have been done recently toward this end, but so far the methodologies put forth still barely detect spam reviews, and none of them show the importance of each extracted feature type. In this study, we propose a novel framework, named NetSpam, which utilizes spam features for modeling review datasets as heterogeneous information networks to map spam detection procedure into a classification problem in such networks. Using the importance of spam features help us to obtain better results in terms of different metrics experimented on real-world review datasets from Yelp and Amazon websites. The results show that NetSpam outperforms the existing methods and among four categories of features; including review-behavioral, user-behavioral, reviewlinguistic, user-linguistic, the first type of features performs better than the other categories.


Existing System

In Existing work, the work only depend on the detect the spam reviews and spammers. None of them show the importance of each extracted feature type. On the other hand, a considerable amount of literature has been published on the techniques used to identify spam and spammers as well as different type of analysis on this topic. These techniques can be classified into different categories; some using linguistic patterns in text which are mostly based on bigram, and unigram, others are based on behavioral patterns that rely on features extracted from patterns in users’ behavior which are mostly metadata based.


Disadvantages: • These work not enough to classify the spam network. • Lack of work to detect spam features.

Proposed System

We propose NetSpam framework that is a novel network based approach which models review networks as heterogeneous information networks. The general concept of our proposed framework is to model a given review dataset as a Heterogeneous Information Network (HIN) and to map the problem of spam detection into a HIN classification problem. In particular, we model review dataset as a HIN in which reviews are connected through different node types (such as features and users). A weighting concept is then employed to calculate each feature’s importance (or weight). These weights are utilized to calculate the final labels for reviews using both unsupervised and supervised approaches. Advantages • Importance of spam features help us to obtain better results in terms of different metrics experimented on real-world review datasets • Initiating the work to detect spam features.
SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

Wednesday 6 September 2017

IEEE-2017 Project | Attribute-Based Storage Supporting Secure Deduplication of Encrypted Data in Cloud Video

Cloud Technologies Hyderabad

Attribute-Based Storage Supporting Secure Deduplication of Encrypted Data in Cloud


Implementation Video in Java From Cloud Technologies

IEEE 2017 Java Projects


SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

Tuesday 29 August 2017

B-Tech IEEE Projects | A Secure and Dynamic Multi keyword Ranked Search Scheme over Encrypted Cloud Data

Cloud Technologies Hyderabad

A Secure and Dynamic Multi keyword Ranked Search Scheme over Encrypted Cloud Data


Implementation Video Of A Secure and Dynamic Multi keyword Ranked Search Scheme over Encrypted Cloud Data

IEEE 2016-2017 Java Projects


SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

M-Tech Projects | Smart Crawler A Two - stage Crawler for Efficiently Harvesting Deep Web Interfaces

Cloud Technologies Hyderabad

Smart Crawler A Two - stage Crawler for Efficiently Harvesting Deep Web Interfaces


Implementation Video in Java From Cloud Technologies

IEEE 2016 2017 Java Projects


SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

M-Tech Cloud Computing Project | DiploCloud: Efficient and Scalable Managementof RDF Data in the Cloud

Cloud Technologies Hyderabad

DiploCloud: Efficient and Scalable Managementof RDF Data in the Cloud


Implementation Video in Java From Cloud Technologies

IEEE 2016 2017 Java Projects


SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

M-Tech IEEE 2016 Project | Privacy-Preserving Location Sharing Servicesfor Social Networks

Cloud Technologies Hyderabad

Privacy-Preserving Location Sharing Servicesfor Social Networks


Implementation Video in Java From Cloud Technologies

IEEE 2016-2017 Java Projects


SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

Sunday 27 August 2017

M-IEEE 2017 Projects | SociRank: Identifying and Ranking Prevalent News Topics Using Social Media Factors

Cloud Technologies Hyderabad

SociRank: Identifying and Ranking Prevalent News Topics Using Social Media Factors


Implementation Video in Java From Cloud Technologies

IEEE 2017 Java Projects


SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

B-Tech Main Projects | SociRank: Identifying and Ranking Prevalent News Topics Using Social Media Factors

Cloud Technologies Hyderabad

SociRank: Identifying and Ranking Prevalent News Topics Using Social Media Factors


Abstract:

Mass media sources, specifically the news media, have traditionally informed us of daily events. In modern times, social media services such as Twitter provide an enormous amount of user-generated data, which have great potential to contain informative news-related content. For these resources to be useful, we must find a way to filter noise and only capture the content that, based on its similarity to the news media, is considered valuable. However, even after noise is removed, information overload may still exist in the remaining data—hence, it is convenient to prioritize it for consumption. To achieve prioritization, information must be ranked in order of estimated importance considering three factors. First, the temporal prevalence of a particular topic in the news media is a factor of importance, and can be considered the media focus (MF) of a topic. Second, the temporal prevalence of the topic in social media indicates its user attention (UA). Last, the interaction between the social media users who mention this topic indicates the strength of the community discussing it, and can be regarded as the user interaction (UI) toward the topic. We propose an unsupervised framework—SociRank—which identifies news topics prevalent in both social media and the news media, and then ranks them by relevance using their degrees of MF, UA, and UI. Our experiments show that SociRank improves the quality and variety of automatically identified news topics.

Existing System

Historically, knowledge that apprises the general public of daily events has been provided by mass media sources, specifically the news media. The news media presents professionally verified occurrences or events, while social media presents the interests of the audience in these areas, and may thus provide insight into their popularity. Unfortunately, filter noise and only capture the content that, based on its news media, and social media is very difficult. However, even after noise is removed, information overload may still exist in the remaining data—hence, it is difficult to prioritize.


Disadvantages: 1. Hard to find a way to filter news from noisy. 2. High computational demand to prioritize.

Proposed System

We propose an unsupervised system SociRank which effectively identifies news topics that are prevalent in both social media and the news media, and then ranks them by relevance using their degrees of MF, UA, and UI. Even though this paper focuses on news topics. News media sources are considered reliable because they are published by professional journalists, who are held accountable for their content. On the other hand, the Internet, being a free and open forum for information exchange, has recently seen a fascinating phenomenon known as social media. In social media, regular, non-journalist users are able to publish unverified content and express their interest in certain events. Consolidated, filtered, and ranked news topics from both professional news providers and individuals have several benefits. The most evident use is the potential to improve the quality and coverage of news recommender systems or Web feeds, adding user popularity feedback.


Advantages: 1. We can find a way to filter noise and only capture the news. 2. We can filter the news based on topic. 3. Main use potential to improve the quality and coverage of news recommender systems.
SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

IEEE 2017-2018 Java Projects | M-Tech IEEE 2017-2018 Projects | B-Tech Main Projects

Cloud Technologies Hyderabad

IEEE 2017-2018 Java Projects | M-Tech IEEE 2017-2018 Projects | B-Tech Main Projects


IEEE-JAVA-2017-2018 Data Mining Projects


Point-of-interest Recommendation for Location Promotion in Location-based Social Networks


Personal Web Revisitation by Context and Content Keywords with Relevance Feedback


SociRank: Identifying and Ranking Prevalent News Topics Using Social Media Factors


IEEE-JAVA-2017-2018 Cloud Computing Projects Using Amazon Web Services


Identity-Based Data Outsourcing With Comprehensive Auditing in Clouds


RAAC: Robust and Auditable Access Control With Multiple Attribute Authorities for Public Cloud Storage


Attribute-Based Storage Supporting Secure Deduplication of Encrypted Data in Cloud


A Novel Efficient Remote Data Possession Checking Protocol in Cloud Storage


Fast Phrase Search for Encrypted Cloud Storage


Identity-based Remote Data Integrity Checking with Perfect Data Privacy Preserving for Cloud Storage


Practical Privacy-Preserving Content-Based Retrieval in Cloud Image Repositories


Provably Secure Key-Aggregate Cryptosystems with Broadcast Aggregate Keys for Online Data Sharing on the Cloud


Secure k-NN Query on Encrypted Cloud Data with Multiple Keys


TAFC: Time and Attribute Factors Combined Access Control for Time-Sensitive Data in Public Cloud


Saturday 26 August 2017

Paper Publishing In UGC Approved Journals For M-Tech Students

Cloud Technologies Hyderabad

Paper Publishing In UGC Approved Journals For M-Tech Students

We Providing papers for publication in all areas of engineering, science and technology.

We Impact Factor 4 & Above

With Following Support

1-Modified Paper
2-Acceptance Letter
3-Soft Copy of Paper
4-Online Paper
5-Soft Copy of Certificates
6-Hard Copy of Certificates

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

Friday 25 August 2017

CSE Main Projects | Point-of-interest Recommendation for Location Promotion in Location-based Social Networks

Cloud Technologies Hyderabad

Point-of-interest Recommendation for Location Promotion in Location-based Social Networks


Implementation Video in Java From Cloud Technologies

IEEE 2017 Java Projects


SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

M-Tech IEEE Project| Personal Web Revisitation by Context and Content Keywords with Relevance Feedback

Cloud Technologies Hyderabad

Personal Web Revisitation by Context and Content Keywords with Relevance Feedback


Implementation Video in Java From Cloud Technologies


SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

Wednesday 23 August 2017

B-Tech main Projects | Attribute-Based Storage Supporting Secure Deduplication of Encrypted Data in Cloud


Attribute-Based Storage Supporting Secure Deduplication of Encrypted Data in Cloud


Abstract

Attribute-based encryption (ABE) has been widely used in cloud computing where a data provider outsources his/her encrypted data to a cloud service provider, and can share the data with users possessing specific credentials (or attributes). However, the standard ABE system does not support secure de-duplication, which is crucial for eliminating duplicate copies of identical data in order to save storage space and network bandwidth. In this paper, we present an attribute-based storage system with secure de-duplication in a hybrid cloud setting, where a private cloud is responsible for duplicate detection and a public cloud manages the storage. Compared with the prior data de-duplication systems, our system has two advantages. Firstly, it can be used to confidentially share data with users by specifying access policies rather than sharing decryption keys. Secondly, it achieves the standard notion of semantic security for data confidentiality while existing systems only achieve it by defining a weaker security notion. In addition, we put forth a methodology to modify a ciphertext over one access policy into ciphertexts of the same plaintext but under other access policies without revealing the underlying plaintext.

Existing System

In existing system a data provider Bob intends to upload a file M to the cloud, and share M (file data) with users having certain credentials. In order to do so, Bob encrypts M under an access policy A over a set of attributes, and uploads the corresponding ciphertext to the cloud, such that only users whose sets of attributes satisfying the access policy can decrypt the ciphertext. Later, another data provider Alice, uploads a ciphertext for the same underlying file M but ascribed to a different access policy A0. Since the file is uploaded in an encrypted form, the cloud is not able to discern that the plaintext corresponding to Alice’s ciphertext is the same as that corresponding to Bob’s, and will store M twice. Obviously, such duplicated storage wastes storage space and communication bandwidth.

Proposed System

In this paper, we present an attribute-based storage system which employs ciphertext-policy attribute-based encryption (CP-ABE) and supports secure deduplication. In the proposed attributed-based system, the same file could be encrypted to different ciphertexts associated with different access policies, storing only one ciphertext of the file means that users whose attributes satisfy the access policy of a discarded ciphertext (but not that of the stored ciphertext) will be denied to access the data that they are entitled to. To overcome this problem, we equip the private cloud with another capability named ciphertext regeneration. For a ciphertext c of a plaintext M with access policy A, the private cloud will be provided with a trapdoor key which is generated along with the ciphertext c by a data provider. The private cloud can use the trapdoor key to convert the ciphertext c with access policy A to a new ciphertext C with another access policy A0 without knowing the underlying message M. Thus, if two data providers happen to upload two ciphertexts corresponding to the same file but under different access policies A and A0, the private cloud can regenerate a ciphertext for the same underlying file with an access policy A UA0 using the corresponding trapdoor key and then store the new ciphertext instead of the old one in the public cloud.

Modules:


Data Provider:
A data provider wants to outsource his/her data to the cloud and share it with users possessing certain credentials.
Attribute Authority (AA):
In this system Attribute Authority can generate first Public Key PK and Master Key MK as well The authority executes the algorithm which inputs a set of attributes S(S ⊆ A˜) and creates a Secret Key SK and these keys can be send to authorized User‘s.
Cloud:
The cloud consists of a public cloud which is in charge of data storage and a private cloud which performs certain computation such as tag checking.
User:
At the user side, each user can download an item, and decrypt the ciphertext with the attribute-based private key generated by the AA if this user’s attribute set satisfies the access structure. Each user checks the correctness of the decrypted message using the label, and accepts the message if it is consistent with the label.

SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

IEEE 2017 B-Tech Main & M-Tech Project | Point-of-interest Recommendation for Location Promotion in Location-based Social Networks


Point-of-interest Recommendation for Location Promotion in Location-based Social Networks


Abstract

With the wide application of location-based social networks (LBSNs), point-of-interest (POI) recommendation has become one of the major services in LBSNs. The behaviors of users in LBSNs are mainly checking in POIs, and these checking in behaviors are influenced by user’s behavior habits and his/her friends. In social networks, social influence is often used to help businesses to attract more users. Each target user has a different influence on different POI in social networks. This paper selects the list of POIs with the greatest influence for recommending users. Our goals are to satisfy the target user’s service need, and simultaneously to promote businesses’ locations (POIs). This paper defines a POI recommendation problem for location promotion. Additionally, we use sub modular properties to solve the optimization problem. At last, this paper conducted a comprehensive performance evaluation for our method using two real LBSN datasets. Experimental results show that our proposed method achieves significantly superior POI recommendations comparing with other state-of-the-art recommendation approaches in terms of location promotion.


Existing System

Recently, many researchers have been engaged in location-aware services. In LBSNs, users can post comments on locations or activities, upload photos, and share check-in locations in which users are interested with friends. These locations are called points-of-interest (POIs). Currently, POI recommendation has become one of main location-aware services in LBSNs. POI recommendation approaches mostly involve recommending users with some locations in which users may be interested based on users’ characters, preferences, and behavioral habits. Through the detailed analysis above, we observe traditional POI recommendations rarely focus on the effect of social relationships for businesses location promotion through the POI recommendation process.


Disadvantages: • No Concept for on the location promotion in LBSNs. • Helps only for business people not for users.

Proposed System

In view of POIs, POIs (e.g.restaurants, hotel, markets) have to explore checking-in records to attract more users to visit; more users (e.g., friends of users that checked in these POIs) will be influenced to check in these locations. In this paper, we regard the influence on the business as a maximization location promotion problem. The essential goals of recommendation system are to satisfy users’ service demands and merchants’ advertising needs. this paper proposes POI recommendation method for promoting POIs. Our proposed method is not only a tool for businesses to use to promote their products and attract more customers to visit their stores, but also recommends users with some POI’s satisfying users preferences.


Advantages: • We propose a novel point-of-interest recommendation problem, and its goal is to promote the businesses’ locations ( POIs ). • We define the user’s IS under special POI categories in an entire social network, and model user mobility to describe the geographical influence between user. Few Points:

In this paper, focus on POI recommendation to social user based on his friends and friends of friends instead of unknown recommendation. Main Application collects check in data with geo properties. Like user from his location move to POI , PGu,v(l) tradeoff between geographical influence. And Target user to another user relation, PTu,v(l) semantic influence b/w u and v. POI recommendation approaches mostly involve recommending users with some locations in which users may be interested based on users’ characters, preferences. Like Facebook no suggest you some business locations according to your interests.


SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811

Tuesday 22 August 2017

M-Tech IEEE 2017 Project | Personal Web Revisitation by Context and Content Keywords with Relevance Feedback


Personal Web Revisitation by Context and Content Keywords with Relevance Feedback


Abstract

Getting back to previously viewed web pages is a common yet uneasy task for users due to the large volume of personally accessed information on the web. This paper leverages human’s natural recall process of using episodic and semantic memory cues to facilitate recall, and presents a personal web revisitation technique called WebPagePrev through context and content keywords. Underlying techniques for context and content memories’ acquisition, storage, decay, an utilization for page re-finding are discussed. A relevance feedback mechanism is also involved to tailor to individual’s memory strength and revisitation habits. Our dynamic management of context and content memories including decay and reinforcement strategy can mimic users’ retrieval and recall mechanism. Among time, location, and activity context factors in WebPagePrev, activity is the best recall cue, and context + content based re-finding delivers the best performance, compared to context based re-finding and content based re-finding.

Existing System

In the literature, a number of techniques and tools like bookmarks, history tools, search engines, etc systems have been developed to support personal web revisitation. In existing search engine, and fetched relevant previously viewed results from its cache. The newly available results were then merged with the previously viewed results to create a list that supported intuitive re-finding and contained new information. For Ex: History Tools. History tools of web browsers maintain user’s accessed URLs chronologically according to visit time (e.g., today, yesterday, last week, etc.), and accessed page titles and contents. Search Engines. How search engines are used for re-finding previously found search results. It explored the differences between queries that had substantial/minimal changes between the previous query and the revisit query.


Disadvantages: • No search for web revisitation. • Depends on only time and date.

Proposed System

Inspired by the psychological findings, this paper explores how to leverage our natural recall process of using episodic and semantic memory cues to facilitate personal web revisitation. We present a personal web revisitation technique, called WebPagePrev, that allows users to get back to their previously focused pages through access context and page content keywords. Underlying techniques for context and content memories’ acquisition, storage, and utilization for web page recall are discussed. Preparation for web revisitation. When a user accesses a web page, which is of potential to be revisited later by the user (i.e., page access time is over a threshold), the context acquisition and management module captures the current access context (i.e., time, location, activities inferred from the currently running computer programs) into a probabilistic context tree.
Advantages: • New technology for personal web revisitation. • Depend on both context and content keywords.


SYSTEM REQUIREMENTS HARDWARE REQUIREMENTS:
Hardware : Pentium Speed : 1.1 GHz RAM : 1GB Hard Disk : 20 GB
SOFTWARE REQUIREMENTS:
Operating System : Windows Family Technology : Java and J2EE Web Technologies : Html, JavaScript, CSS Web Server : Apache Tomcat 7.0/8.0 Database : My SQL 5.5 or Higher UML's : StarUml Java Version : JDK 1.7 or 1.8
Implemented by
Development team :

Cloud Technologies

www.cloudstechnologies.in


Contact : 8121953811, 040-65511811