Research Associate
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Muhamamd Abdul Moiz Zia holds a Bachelor’s degree in Computer Science from the University of Central Punjab, Lahore. He is pursuing a Master’s in Applied Computer Science at the University of Winnipeg. His interests are database forensics, digital forensics, and security and privacy.
Identification of PDF Creator Tools Using Machine Learning: A Digital Forensics Approach
– Developed a machine learning framework to identify PDF creator tools, enhancing digital forensics by analyzing binary data beyond traditional metadata.
– Utilized techniques like byte histograms and entropy measurements to detect origin of PDF documents more accurately than metadata analysis alone.
File Type Detection in Digital Forensics with Byte Frequency, Entropy, and Header Info
– Developed a comprehensive machine learning framework for content-based file type identification, integrating byte histograms, entropy, and header information to create a robust feature set for accurate classification
– Utilized diverse data features to analyze and authenticate file types beyond traditional identification methods. This approach included extracting detailed byte histograms to capture file structure, measuring entropy to assess data complexity, and using header information for additional metadata insights.
Survey on string matching approaches in Digital Forensics
– Analyzed and compared key string matching algorithms utilized in digital forensics, focusing on their implementation within popular forensic tools. Evaluated the performance of each algorithm in terms of speed, accuracy, and efficiency under various forensic conditions.
I am pursuing a Master's in Computer Science, focusing on Advanced Data Structures and Algorithms, Security and Privacy, Machine Learning, and Cloud Computing. These courses have equipped me with a deep understanding of efficient algorithm design, cybersecurity principles, machine learning models, and cloud architecture. I have applied clustering techniques to datasets, enhanced security in Redis databases for digital forensics, and developed content-based file type identification systems using machine learning.
This education has provided a robust foundation in advanced computing concepts, practical skills in emerging technologies, and a comprehensive understanding of security and privacy, preparing me for a career in the dynamic field of computer science.
