BLACK, MALE, AND HIGH-ACHIEVING: AN EXAMINATION OF A RISK FACTOR AND CULTURAL RESOURCES FOR BLACK MALE ACADEMIC ACHIEVEMENT

Black boys are confronted with unique educational circumstances. They are often misdiagnosed and misplaced into special education programs (Bush-Daniels, 2008; Patton, 1998; Terman et al., 1996). Additionally, they are less likely to be enrolled in gifted and talented programs, even if their former achievements reflect their aptitude to succeed (Black Alliance for Educational Options, n.d.; Moore & Flowers, 2012). Given these statistics, a considerable emphasis has been placed on the causes and the consequences of low/under achievement for this population. As a result, the experiences of Black males who are achieving have been greatly neglected. Moreover, little is known about the factors that facilitate academic achievement among high-achieving Black boys. In an effort to bring the heterogenic nature of schooling experiences for Black boys to light, the present study examined the influence risk and protective factors had on the academic experiences of high-achieving Black boys. Grounded in the risk and resilience framework and the Integrative Model for the Study of Minority Youth Development, this study explored whether the high-achieving Black high school boys in this sample (n =88) reported experiencing discrimination (i.e. academic-based) and how this academic-based discrimination related to their 1) academic performance (i.e. GPA), 2) perceptions of math ability, and 3) race-based academic self-concept. In addition to exploring how academic-based discrimination was linked to academic achievement, this study examined how cultural resources such as racial socialization messages and racial identity related to academic achievement. Specifically, cultural socialization, preparation for bias, egalitarianism, private regard and public regard were evaluated alongside the three academic outcomes under study. Finally, the study explored whether aspects of racial socialization or racial identity buffered the effects of discrimination on any of the outcomes. Interestingly, the race/ethnicity of the student mattered for how students perceived their math ability. The risk factor academic-based discrimination was linked to academic performance. Cultural resources cultural socialization, preparation for bias, and private regard were linked to various academic outcomes of interest. There was only one significant moderating effect: a high private regard buffered the relationship between academic-based discrimination and race-based academic self-concept. Limitations and implications of this study are discussed.

Active Data Collection Techniques to Understand Online Scammers and Cybercriminals

Nigerian scam, also known as advance fee fraud or 419 scam, is a prevalent form of online fraudulent activity that causes financial loss to individuals and businesses. Nigerian scam has evolved from simple non-targeted email messages to more sophisticated scams targeted at users of classifieds, dating and other websites. Even though such scams are observed and reported by users frequently, the community’s understanding of Nigerian scams is limited since the scammers operate “underground”. To better understand the underground Nigerian scam ecosystem and seek effective methods to deter Nigerian scam and cybercrime in general, we conduct a series of active and passive measurement studies. Relying upon the analysis and insight gained from the measurement studies, we make four contributions: (1) we analyze the taxonomy of Nigerian scam and derive long-term trends in scams; (2) we provide an insight on Nigerian scam and cybercrime ecosystems and their underground operation; (3) we propose a payment intervention as a potential deterrent to cybercrime operation in general and evaluate its effectiveness; and (4) we offer active and passive measurement tools and techniques that enable in-depth analysis of cybercrime ecosystems and deterrence on them. We first created and analyze a repository of more than two hundred thousand user-reported scam emails, stretching from 2006 to 2014, from four major scam reporting websites. We select ten most commonly observed scam categories and tag 2,000 scam emails randomly selected from our repository. Based upon the manually tagged dataset, we train a machine learning classifier and cluster all scam emails in the repository. From the clustering result, we find a strong and sustained upward trend for targeted scams and downward trend for non-targeted scams. We then focus on two types of targeted scams: sales scams and rental scams targeted users on Craigslist. We built an automated scam data collection system and gathered large-scale sales scam emails. Using the system we posted honeypot ads on Craigslist and conversed automatically with the scammers. Through the email conversation, the system obtained additional confirmation of likely scam activities and collected additional information such as IP addresses and shipping addresses. Our analysis revealed that around 10 groups were responsible for nearly half of the over 13,000 total scam attempts we received. These groups used IP addresses and shipping addresses in both Nigeria and the U.S. We also crawled rental ads on Craigslist, identified rental scam ads amongst the large number of benign ads and conversed with the potential scammers. Through in-depth analysis of the rental scams, we found seven major scam campaigns employing various operations and monetization methods. We also found that unlike sales scammers, most rental scammers were in the U.S. The large-scale scam data and in-depth analysis provide useful insights on how to design effective deterrence techniques against cybercrime in general. We study underground DDoS-for-hire services, also known as booters, and measure the effectiveness of undermining a payment system of DDoS Services. Our analysis shows that the payment intervention can have the desired effect of limiting cybercriminals’ ability and increasing the risk of accepting payments.