Dr. Ebrima N. Ceesay
Ebrima N. Ceesay, MS, Ph.D. is Associate at Booz Allen Hamilton
where he
is consulting on information security, forensics, data
mining, and machine learning.
Ebrima coauthored
Using Type Qualifiers to Analyze Untrusted Integers
and Detecting Security Flaws in C Programs,
A Taxonomy for Comparing Attack-Graph
Approaches,
Waveform Development, and
An Artificial Neural Networks Approach in Detecting Phishing
Attacks.
Some of the projects he has worked on include:
- Authorship Identification Forensics: He studied unsupervised learning techniques to identify authorship of Phishing emails based on email structures and linguistic patterns found in Phishing emails.
- Kernel Feature Extraction: He studied kernel methods; Kernel Principal Component Analysis (KPCA); Kernel Linear Discriminant Analysis (KLDA); and Kernel Maximum Margin Discriminant Analysis (KKMDA) to perform online feature extraction on a Phishing repository.
- Diversity Algorithm for Worrisome Software and Networks (DAWSON): He studied how to break the vulnerability specification for the executing component code or protocol that an attacker is exploiting without breaking the functionality of the executing component or protocol. A high level abstraction of defense-in-depth.