sajan-caissa

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

• Here, a secure multi-keyword ranked search scheme over encrypted cloud data is presented using JAVA as the frontend technology and backend as MySQL.• Specifically, the vector space model and the widely-used “term frequency (TF) × inverse document frequency(IDF)” model are combined in the index construction and query generation to provide multi-keyword ranked search.• We construct a special tree-based index structure and propose a “Greedy Depth-first Search” algorithm to provide efficient multi-keyword ranked search. • The secure kNN algorithm is utilized to encrypt the index and query vectors, and to ensure accurate relevance score calculation between encrypted index and query vectors. • To resist different attacks in different threat models, we construct two secure search schemes: the basic dynamic multi-keyword ranked search (BDMRS) scheme in the known ciphertext model, and the enhanced dynamic multi-keyword ranked search (EDMRS) scheme in the known background model.

compiler-

use of clang gcc and llvm in compiler optimization

FINE-GRAINED-MULTIKEYWORD-RANKED-SEARCH-OVER-ENCRYPTED-CLOUD-DATA

IMPLEMENTATION OF RESEARCH PAPER

hotel_recommender_system

A hotel recommender system in python using hybrid approach of content based and collaborative filtering of hotel reviews by a user. Text Mining done using NLTK library and chi-square feature selection using sklearn. User profile was generated using an ensemble classifier.

Hybrid-Movie-Recommender

using WARP cost function

Multi-keyword-Ranked-search

implementation of a research paper-gives a knowledge on jsp database connectivity

Secure-and-dynamic-Multi-Keyword-ranked-search-over-Encrypted-Cloud-Data

Topic-modelling-using-Latent-Dirichlet-Allocation

Gensim tool is used in building a LDA topic modelling

Virtual-Machine-VM-Consolidation-using-Roulette-wheel-selection-Strategy---Genetic-Algorithm

VM consolidation using genetic algorithm strategy implemented using cloudsim

vm-consolidation-using-particle-swarm-optimization

sajan-caissa/Virtual-Machine-VM-Consolidation-using-Roulette-wheel-selection-Strategy---Genetic-Algorithm

VM consolidation using genetic algorithm strategy implemented using cloudsim

sajan-caissa/vm-consolidation-using-particle-swarm-optimization

sajan-caissa/Secure-and-dynamic-Multi-Keyword-ranked-search-over-Encrypted-Cloud-Data

sajan-caissa/compiler-

use of clang gcc and llvm in compiler optimization

sajan-caissa/Hybrid-Movie-Recommender

using WARP cost function

sajan-caissa/Multi-keyword-Ranked-search

implementation of a research paper-gives a knowledge on jsp database connectivity

sajan-caissa/Topic-modelling-using-Latent-Dirichlet-Allocation

Gensim tool is used in building a LDA topic modelling

sajan-caissa/FINE-GRAINED-MULTIKEYWORD-RANKED-SEARCH-OVER-ENCRYPTED-CLOUD-DATA

IMPLEMENTATION OF RESEARCH PAPER

sajan-caissa/hotel_recommender_system

A hotel recommender system in python using hybrid approach of content based and collaborative filtering of hotel reviews by a user. Text Mining done using NLTK library and chi-square feature selection using sklearn. User profile was generated using an ensemble classifier.

sajan-caissa/-A-Secure-and-Dynamic-Multi-Keyword-Ranked-Search-Scheme-over-Encrypted-Cloud-Data

• Here, a secure multi-keyword ranked search scheme over encrypted cloud data is presented using JAVA as the frontend technology and backend as MySQL.• Specifically, the vector space model and the widely-used “term frequency (TF) × inverse document frequency(IDF)” model are combined in the index construction and query generation to provide multi-keyword ranked search.• We construct a special tree-based index structure and propose a “Greedy Depth-first Search” algorithm to provide efficient multi-keyword ranked search. • The secure kNN algorithm is utilized to encrypt the index and query vectors, and to ensure accurate relevance score calculation between encrypted index and query vectors. • To resist different attacks in different threat models, we construct two secure search schemes: the basic dynamic multi-keyword ranked search (BDMRS) scheme in the known ciphertext model, and the enhanced dynamic multi-keyword ranked search (EDMRS) scheme in the known background model.

sajan-caissa/aws-lambda-power-tuning

Step Functions state machine generator for AWS Lambda Power Tuning

sajan-caissa/Enabling-fine-grained-Multikryword-Search

Enabling Efficient Multi-Keyword Ranked Search Over Encrypted Mobile Cloud Data Through Blind Storage

sajan-caissa/FINE-GRAINED-MULTIKEYWORD-RANKED-SEARCH

sajan-caissa/hospital-admin

xml-dbms-wamp

sajan-caissa/mword

word 1.1a

sajan-caissa/permutation

sajan-caissa/VMPlacementSim

A simulator for Virtual Machine Placement Algorithms

sajan-caissa/xml-dbms