Pinned Repositories
mirna-pipeline
bloom-filters
Testing GUAVA bloom filter
FlexSC
A Flexible Efficient Secure Computation Backend
GeoLite2CityDB_Summary
Python3 -- large file parsing + API handling example
Integer-to-Word-converter_Python-3
Simple python3 code to convert any non-negative integer number to word.
interview
Interview questions
learning_Javascript
Learning React and Node.js
SecCQ
In this project, we address three potential challenges for secure sharing and count query execution on the genomic data: data privacy, query privacy, and output privacy.
SecSPQ
It provides an opportunity for the researchers to execute a similar patient query (SPQ) on encrypted biomedical data preserving data, query, and output privacy.
SecSS
In this project, we propose a method to securely perform substring search and set-maximal search on SNPs datasets using a generalized suffix tree.
Safiur-Mahdi's Repositories
Safiur-Mahdi/bloom-filters
Testing GUAVA bloom filter
Safiur-Mahdi/FlexSC
A Flexible Efficient Secure Computation Backend
Safiur-Mahdi/GeoLite2CityDB_Summary
Python3 -- large file parsing + API handling example
Safiur-Mahdi/Integer-to-Word-converter_Python-3
Simple python3 code to convert any non-negative integer number to word.
Safiur-Mahdi/interview
Interview questions
Safiur-Mahdi/learning_Javascript
Learning React and Node.js
Safiur-Mahdi/SecCQ
In this project, we address three potential challenges for secure sharing and count query execution on the genomic data: data privacy, query privacy, and output privacy.
Safiur-Mahdi/SecSPQ
It provides an opportunity for the researchers to execute a similar patient query (SPQ) on encrypted biomedical data preserving data, query, and output privacy.
Safiur-Mahdi/SecSS
In this project, we propose a method to securely perform substring search and set-maximal search on SNPs datasets using a generalized suffix tree.
Safiur-Mahdi/Resume
The project conatains resume formats for both academic and industry purposes
Safiur-Mahdi/SecCI
Secure Cohort Identification for Clinical Trial using Heterogeneous Healthcare Data