Peng Wang (Indiana University Bloomington), Zilong Lin (Indiana University Bloomington), Xiaojing Liao (Indiana University Bloomington), XiaoFeng Wang (Indiana University Bloomington)

A new type of underground illicit drug promotion, illicit drug business listings on local search services (e.g., local knowledge panel, map search, voice search), is increasingly being utilized by miscreants to advertise and sell controlled substances on the Internet. Miscreants exploit the problematic upstream local data brokers featuring loose control on data quality to post listings that promote illicit drug business. Such a promotion, in turn, pollutes the major downstream search providers’ knowledge bases and further reaches a large audience through web, map, and voice searches. To the best of our knowledge, little has been done so far to understand this new illicit promotion in terms of its scope, impact, and techniques, not to mention any effort to identify such illicit drug business listings on a large scale. In this paper, we report the first measurement study of the illicit drug business listings on local search services. Our findings have brought to light the vulnerable and less regulated local business listing ecosystem and the pervasiveness of such illicit activities, as well as the impact on local search audience.

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Forensic Analysis of Configuration-based Attacks

Muhammad Adil Inam (University of Illinois at Urbana-Champaign), Wajih Ul Hassan (University of Illinois at Urbana-Champaign), Ali Ahad (University of Virginia), Adam Bates (University of Illinois at Urbana-Champaign), Rashid Tahir (University of Prince Mugrin), Tianyin Xu (University of Illinois at Urbana-Champaign), Fareed Zaffar (LUMS)

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Chhoyhopper: A Moving Target Defense with IPv6

A S M Rizvi (University of Southern California/Information Sciences Institute) and John Heidemann (University of Southern California/Information Sciences Institute)

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DRIVETRUTH: Automated Autonomous Driving Dataset Generation for Security Applications

Raymond Muller (Purdue University), Yanmao Man (University of Arizona), Z. Berkay Celik (Purdue University), Ming Li (University of Arizona) and Ryan Gerdes (Virginia Tech)

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WIP: Interrupt Attack on TEE-protected Robotic Vehicles

Mulong Luo (Cornell University) and G. Edward Suh (Cornell University)

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