The Socio-Monetary Incentives of Online Social Network Malware Campaigns
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The Socio-monetary Incentives of Online Social Network Malware Campaigns Ting-Kai Huang Bruno Ribeiro Google Carnegie Mellon University Mountain View, CA Pittsburgh, PA [email protected] [email protected] Harsha V. Madhyastha Michalis Faloutsos University of California Riverside University of New Mexico Riverside, CA Albuquerque, NM [email protected] [email protected] ABSTRACT 1. INTRODUCTION Online social networks (OSNs) offer a rich medium of mal- In 1949 von Neumann first suggested the possibility of cre- ware propagation. Unlike other forms of malware, OSN ating self-reproducing computer programs [42]. Thirty-five malware campaigns direct users to malicious websites that years later Cohen wrote one of the first computer malwares, hijack their accounts, posting malicious messages on their which he named a computer virus [7]. Since then, the con- behalf with the intent of luring their friends to the mali- nection between computer malware and biological viruses cious website, thus triggering word-of-mouth infections that has captivated the imagination of both researchers and the cascade through the network compromising thousands of ac- general public [10, 11, 12, 36], and the manner in which counts. But how are OSN users lured to click on the mali- malware interacts with people and computers has evolved. cious links? In this work, we monitor 3.5 million Facebook The inception of e-mail in the 60's created a new medium accounts and explore the role of pure monetary, social, and for malware developers [5, 15, 30]. combined socio-monetary psychological incentives in OSN Today, online social networks (OSNs) offer another new malware campaigns. Among other findings we see that the medium for malware propagation that, as shown in this and majority of the malware campaigns rely on pure social in- some of other of our recent studies [19, 33], is profoundly centives. However, we also observe that malware campaigns changing the face of malware. In OSN malware, OSN users using socio-monetary incentives infect more accounts and are lured into visiting malicious websites containing click- last longer than campaigns with pure monetary or social in- jacking attacks1 or into installing malicious in-OSN apps centives. The latter suggests the efficiency of an epidemic (e.g., Facebook apps). Once infected, the victim is imper- tactic surprisingly similar to the mechanism used by biolog- sonated in the social network, unknowingly exposing his or ical pathogens to cope with diverse gene pools. her friends to the same campaign through bogus direct mes- sages or broadcast posts, creating a word of mouth infection that cascades through the network [19, 33]. One of the key Categories and Subject Descriptors features of OSN malware (a.k.a. socware [19, 33]) is lever- H.1.2 [Information Systems]: User/Machine Systems| aging on the perceived \endorsement" of hijacked users from Human factors the in the eyes of that user's friends. OSN malware is more than just a nuisance, it enables identity theft and cyber- crime with several reported cases resulting in financial losses General Terms for the victims [20, 35]. Human Factors, Measurement But how are OSN users lured to click on these malicious links in the first place? We leverage on our prior work on de- tecting malware posts through a combination of keywords, Keywords anomalous user behavior, and topological anomalies [19, 33] OSN Malware; Social Incentives; Monetary Incentives; La- to study how OSN malware exploits psychological incen- bor Markets tives. Following Heyman and Ariely [17] classification of behavioral incentives in labor markets, we divide incentives into monetary, social, and socio-monetary (the latter is a Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed combination of monetary and social incentives). These so- for profit or commercial advantage and that copies bear this notice and the full cita- cial and monetary incentives are, for instance, a pure mon- tion on the first page. Copyrights for components of this work owned by others than etary posts that promises a \free iPad"; pure social posts ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or re- related to improving or checking your social status such as publish, to post on servers or to redistribute to lists, requires prior specific permission \Can you beat me in this game hlinki?" and \OMG check and/or a fee. Request permissions from [email protected]. COSN’14, October 1–2, 2014, Dublin, Ireland. 1 Copyright 2014 ACM 978-1-4503-3198-2/14/10 ...$15.00. Clickjacking and other attack mechanisms are described in http://dx.doi.org/10.1145/2660460.2660478. Huang et al. [19] if a friend has deleted you! Click hherei, it works!", or of reports statistics of the observed incentives at the campaign shared curiosity\This is shocking hlinki!"; and finally (socio- level. Section 7 shows that simulations of epidemics on real monetary) a combination of social and monetary incentives OSN topologies using mixed incentives can indeed outper- (e.g., a friend's challenge with the promise of a free iPad if form pure incentives, even if mixed incentives are not as you win). effective than pure incentives in infecting to the subpopula- tion of individuals susceptible to the pure incentive. Finally, Contributions Section 8 discusses our results and future work. One of the main contributions of this work is to study the im- pact of distinct socio-monetary incentives in the size and du- 2. PRELIMINARIES 2 ration of malware campaigns , covering the posts of nearly Facebook is the largest online social network ever created 3.5 million Facebook users collected over ten months be- in the Internet's short history. With over 1.11 billion active tween July 2011 and April 2012. With the help of My- users as of March 2013 [9], Facebook is a prime source of PageKeeper malware post detection heuristics [19, 33] and online social network data. Through the analysis of posts of 226 Mechanical Turk [3] volunteers we classify thousands of over 3.5 million Facebook users collected over ten months, unique Facebook posts. We note, however, that our monitor- we observe a new generation of computer malware that re- ing is restricted to both users that installed MyPageKeeper lies heavily on two factors to spread through word of mouth: and the posts of their friends that are visible to these users. (a) incentive mechanisms provided by the post and (b) peo- But while we are limited to users of one online social network ple's cognitive capacity to distinguish between a legitimate (Facebook) that volunteer to have their accounts protected request from a friend and a bogus request from an infected by MyPageKeeper, the data collected from this viewpoint (of friend. Other security factors are also known to play a role 3.5 million users) is of great interest. Aside from truly ran- in security threats [4, 18, 25, 45], such as users' belief that dom monitoring without user consent, data collection from they are less at risk than others, the fact that privacy and volunteers is prone to unknown biases. security are abstract concepts, and that it is hard for non- We observe that 67% of the malware campaigns in our experts to judge risk. We leave the analysis of the analysis of dataset use pure social incentives. Interestingly, and de- these other security factors as future work, so we can instead spite Heyman and Ariely's observations that subjects ex- focus our analysis on the role of socio-monetary incentives. posed to socio-monetary incentives act like subjects exposed A representative example of the kind of incentive used to monetary incentives [17], we observe that combined socio- on Facebook malware campaigns3 is the campaign whose monetary incentives are more effective { in fact, stochasti- posts include the text \OMG check if a friend has deleted cally dominant with respect to number of infected users and you! Click hherei, it works!". This campaign simultaneously campaign durations { than campaigns using pure social or exploits the reader's incentive to know his or her social status pure monetary incentives. For instance, malware campaigns in the group and the credibility (and social capital [37]) of with socio-monetary incentives last on average 136% longer the impersonated victim. The latter is remarkably different than pure monetary and pure social campaigns. from messages seen in e-mail spam, an effect broadly felt on the use of keywords. For instance, \viagra" and \pills" are Relation to Biological Pathogens popular keywords in e-mail spam, but out of the hundreds A simple explanation for the effectiveness of combined socio- of thousands of malicious posts we collected on Facebook, monetary incentives is a type of percolation effect observed not a single one contains these keywords [33]. in plant pathogen epidemics over mixed crops [28, 46]. Through Once the post appears legitimate to the victim, a com- simulations we show that even if the susceptibility to com- bination of the incentives in the post and the victim's sus- bined incentives is less than that of any one specialized ceptibility to the incentive drive the victim's decision as to incentive, combining incentives provide a tremendous ad- whether or not to click on the malicious link. The data vantage to percolate over the network. On Facebook the shows that social incentives often target the victim's social mix is the likely propensity of distinct users to be more capital { increasing one's social capital is known as one of attracted to either monetary or social incentives. While the reasons why people join online social networks [37] { or there are other plausible explanations to why campaigns the victim's social insecurities about his or her social status with socio-monetary incentives infect more users and last in their social group.