Scripting the crime commission process in the illicit online prescription drug trade

This paper considers the processes in the illicit online prescription drug trade, namely search-redirection attacks and the operation of unlicensed pharmacies using crime script analysis. Empirical data have been used to describe the salient elements of the online criminal infrastructures and associated monetization paths enabling criminal profitability. This analysis reveals the existence of structural chokepoints: components of online criminal operations being limited in number, and critical for the operations’ profitability. Consequently, interventions targeting such components can reduce the opportunities and incentives to engage in online crime through an increase in criminal operational costs, and in the risk of apprehension.This work was supported by the Department of Homeland Security (DHS) Science and Technology Directorate, Cyber Security Division (DHSS&T/CSD) Broad Agency Announcement 11.02; the Government of Australia; and SPAWAR Systems Center Pacific [contract number N66001-13-C-0131]. The opinions, findings, and conclusions or recommendations expressed are those of the authors and do not reflect those of the aforementioned agencies.This is the final version of the article. It first appeared from Oxford University Press via http://dx.doi.org/10.1093/cybsec/tyv00

A Nearly Four-Year Longitudinal Study of Search-Engine Poisoning

We investigate the evolution of search-engine poisoning using data on over 5 million search results collected over nearly 4 years. We build on prior work investigating search-redirection attacks, where criminals compromise high-ranking websites and direct search traf-fic to the websites of paying customers, such as unlicensed phar-macies who lack access to traditional search-based advertisements. We overcome several obstacles to longitudinal studies by amalga-mating different resources and adapting our measurement infras-tructure to changes brought by adaptations by both legitimate op-erators and attackers. Our goal is to empirically characterize how strategies for carrying out and combating search poisoning have evolved over a relatively long time period. We investigate how the composition of search results themselves has changed. For in-stance, we find that search-redirection attacks have steadily grown to take over a larger share of results (rising from around 30 % in late 2010 to a peak of nearly 60 % in late 2012), despite efforts by search engines and browsers to combat their effectiveness. We also study the efforts of hosts to remedy search-redirection attacks. We find that the median time to clean up source infections has fallen from around 30 days in 2010 to around 15 days by late 2013, yet the number of distinct infections has increased considerably over the same period. Finally, we show that the concentration of traffic to the most successful brokers has persisted over time. Further, these brokers have been mostly hosted on a few autonomous systems, which indicates a possible intervention strategy. Categories and Subject Descriptors K.4.1 [Public Policy Issues]: Abuse and crime involving comput-er

Detecting cyberbullying and cyberaggression in social media

Cyberbullying and cyberaggression are increasingly worrisome phenomena affecting people across all demographics. More than half of young social media users worldwide have been exposed to such prolonged and/or coordinated digital harassment. Victims can experience a wide range of emotions, with negative consequences such as embarrassment, depression, isolation from other community members, which embed the risk to lead to even more critical consequences, such as suicide attempts. In this work, we take the first concrete steps to understand the characteristics of abusive behavior in Twitter, one of today’s largest social media platforms. We analyze 1.2 million users and 2.1 million tweets, comparing users participating in discussions around seemingly normal topics like the NBA, to those more likely to be hate-related, such as the Gamergate controversy, or the gender pay inequality at the BBC station. We also explore specific manifestations of abusive behavior, i.e., cyberbullying and cyberaggression, in one of the hate-related communities (Gamergate). We present a robust methodology to distinguish bullies and aggressors from normal Twitter users by considering text, user, and network-based attributes. Using various state-of-the-art machine-learning algorithms, we classify these accounts with over 90% accuracy and AUC. Finally, we discuss the current status of Twitter user accounts marked as abusive by our methodology and study the performance of potential mechanisms that can be used by Twitter to suspend users in the future

Kek, Cucks, and God Emperor Trump: A Measurement Study of 4chan's Politically Incorrect Forum and its Effects on the Web

The discussion-board site 4chan has been part of the Internet's dark underbelly since its inception, and recent political events have put it increasingly in the spotlight. In particular, /pol/, the “Politically Incorrect'” board, has been a central figure in the outlandish 2016 US election season, as it has often been linked to the alt-right movement and its rhetoric of hate and racism. However, 4chan remains relatively unstudied by the scientific community: little is known about its user base, the content it generates, and how it affects other parts of the Web. In this paper, we start addressing this gap by analyzing /pol/ along several axes, using a dataset of over 8M posts we collected over two and a half months. First, we perform a general characterization, showing that /pol/ users are well distributed around the world and that 4chan's unique features encourage fresh discussions. We also analyze content, finding, for instance, that YouTube links and hate speech are predominant on /pol/. Overall, our analysis not only provides the first measurement study of /pol/, but also insight into online harassment and hate speech trends in social media

Avoidable mortality across Canada from 1975 to 1999

BACKGROUND: The concept of 'avoidable' mortality (AM) has been proposed as a performance measure of health care systems. In this study we examined mortality in five geographic regions of Canada from 1975 to 1999 for previously defined avoidable disease groups that are amenable to medical care and public health. These trends were compared to mortality from other causes. METHODS: National and regional age-standardized mortality rates for ages less than 65 years were estimated for avoidable and other causes of death for consecutive periods (1975–1979, 1980–1985, 1985–1989, 1990–1994, and 1995–1999). The proportion of all-cause mortality attributable to avoidable causes was also determined. RESULTS: From 1975–1979 to 1995–1999, the AM decrease (46.9%) was more pronounced compared to mortality from other causes (24.9%). There were persistent regional AM differences, with consistently lower AM in Ontario and British Columbia compared to the Atlantic, Quebec, and Prairies regions. This trend was not apparent when mortality from other causes was examined. Injuries, ischaemic heart disease, and lung cancer strongly influenced the overall AM trends. CONCLUSION: The regional differences in mortality for ages less than 65 years was attributable to causes of death amenable to medical care and public health, especially from causes responsive to public health

Secure Network Management Using a Key Distribution Center

Abstract. The proliferation and growth of modern computer networks have made network management infrastructures an integral part of the administration process. Nevertheless, most of these do not have the notion of security assimilated by design. Thus, existing network equipment cannot be managed securely without additional hardware or software security modules. This paper discusses a simple, yet robust, solution for securing an existing management infrastructure based on the SNMP protocol.