Eagle Scouts: Merit beyond the Badge

Previous studies have shown that participation in Scouting produces better citizens.6 And, there is no shortage of examples or anecdotal accounts that would affirm these findings. Surprisingly, however, there is very little scientific evidence to confirm the prosocial benefits associated with Scouting or earning the rank of Eagle Scout. Thus, the central question of this study is to determine if participation in Scouting and ultimately becoming an Eagle Scout is associated with prosocial behavior and positive youth development that carries over into young adulthood and beyond

Feature Engineering Using File Layout for Malware Detection

Malware detection on binary executables provides a high availability to even binaries which are not disassembled or decompiled. However, a binary-level approach could cause ambiguity problems. In this paper, we propose a new feature engineering technique that use minimal knowledge about the internal layout on a binary. The proposed feature avoids the ambiguity problems by integrating the information about the layout with structural entropy. The experimental results show that our feature improves accuracy and F1-score by 3.3% and 0.07, respectively, on a CNN based malware detector with realistic benign and malicious samples.Comment: 2pages, no figures, This manuscript was presented in the poster session of The Annual Computer Security Applications Conference (ACSAC) 202

SVM Based Indoor/Mixed/Outdoor Classification for Digital Photo Annotation in a Ubiquitous Computing Environment

This paper extends our previous framework for digital photo annotation by adding noble approach of indoor/mixed/outdoor image classification. We propose the best feature vectors for a support vector machine based indoor/mixed/ outdoor image classification. While previous research classifies photographs into indoor and outdoor, this study extends into three types, including indoor, mixed, and outdoor classes. This three-class method improves the performance of outdoor classification. This classification scheme showed 5--10% higher performance than previous research. This method is one of the components for digital image annotation. A digital camera or an annotation server connected to a ubiquitous computing network can automatically annotate captured photos using the proposed method