In Partial Fulfillment of the Requirements for the Degree of Master of Science
will defend his thesis
Automatic Feature Extraction for Phishing Email Detection
Each year, billions are lost in damages from phishing emails, and human researchers put countless hours researching new discovery techniques and finding the flaws in the old ones. The number of articles publishing these findings are increasing very rapidly, too rapidly for humans to amass and remember in a reasonable amount of time. This thesis adapts FeatureSmith's Android malware detection to phishing emails, to automatically extract all the features in each scholarly article, patent, and/or thesis. Because of the nature of phishing email, which requires intelligent application of multiple features for accurate classification, the weighting and ranking utilized by FeatureSmith for Android to find the best features, was not as effective for phishing email. As a result the final, most helpful, features must then be manually extracted to use in phishing email detection. Sometimes the extraction process involves going to the source article, which can reveal tables, or other sources, of other overlooked features that can also be implemented.
Date: Friday, July 20, 2018
Time: 4:00 PM
Place: PGH 550
Advisor: Dr. Rakesh Verma
Faculty, students, and the general public are invited.