H
Haider Adnan Khan
Researcher at Georgia Institute of Technology
Publications - 14
Citations - 302
Haider Adnan Khan is an academic researcher from Georgia Institute of Technology. The author has contributed to research in topics: Feature extraction & Intelligent word recognition. The author has an hindex of 8, co-authored 14 publications receiving 210 citations. Previous affiliations of Haider Adnan Khan include United International University.
Papers
More filters
Proceedings ArticleDOI
Handwritten Bangla numeral recognition using Local Binary Pattern
Tasnuva Hassan,Haider Adnan Khan +1 more
TL;DR: The proposed OCR system was evaluated on the off-line handwritten Bangla numeral database CMATERdb 3.1, and achieved an excellent accuracy of 96:7% character recognition rate.
Proceedings Article
One&Done: A Single-Decryption EM-Based Attack on OpenSSL’s Constant-Time Blinded {RSA}
Monjur Alam,Haider Adnan Khan,Moumita Dey,Nishith Sinha,Robert Callan,Alenka Zajic,Milos Prvulovic +6 more
TL;DR: The first side channel attack approach that, without relying on the cache organization and/or timing, retrieves the secret exponent from a single decryption on arbitrary ciphertext in a modern (current version of OpenSSL) fixed-window constant-time implementation of RSA is presented.
Proceedings ArticleDOI
Handwritten Bangla digit recognition using Sparse Representation Classifier
TL;DR: This work applied Sparse Representation Classifier on the image zone density, an image domain statistical feature extracted from the character image, to classify the Bangla numerals and demonstrates an excellent accuracy of 94% on the off-line handwritten Bangla numeral database CMATERdb 3.1.
Journal ArticleDOI
Malware Detection in Embedded Systems Using Neural Network Model for Electromagnetic Side-Channel Signals
TL;DR: A novel malware detection system for critical embedded and cyber-physical systems (CPS) that exploits electromagnetic (EM) side-channel signals from the device to detect malicious activity and can detect DDoS and ransomware with 100% accuracy.
Journal ArticleDOI
IDEA: Intrusion Detection through Electromagnetic-Signal Analysis for Critical Embedded and Cyber-Physical Systems
Haider Adnan Khan,Nader Sehatbakhsh,Luong N. Nguyen,Robert Callan,Arie Yeredor,Milos Prvulovic,Alenka Zajic +6 more
TL;DR: A novel framework called IDEA that exploits electromagnetic (EM) side-channel signals to detect malicious activity on embedded and cyber-physical systems (CPS) and can detect different attacks with excellent accuracy from distances up to 3 m.