Zhengyi Li (Indiana University Bloomington), Xiaojing Liao (Indiana University Bloomington)

An appraisal system is a feedback mechanism that has gained popularity in underground marketplaces. This system allows appraisers, who receive free samples from vendors, to provide assessments (i.e., appraisal reviews) for products in underground marketplaces. In this paper, we present the first measurement study on the appraisal system within underground marketplaces. Specifically, from 17M communication traces from eight marketplaces spanning from Feb 2006 to Mar 2023, we discover 56,229 appraisal reviews posted by 18,701 unique appraisers. We look into the appraisal review ecosystem, revealing five commonly used requirements and merits in the appraiser selection process. These findings indicate that the appraisal system is a well-established and structured process within the underground marketplace ecosystem. Furthermore, we reveal the presence of high-quality and unique cyber threat intelligence (CTI) in appraisal reviews. For example, we identify the geolocations of followers for a social booster and programming languages used for malware. Leveraging our extraction model, which integrates 41 distinct types of CTI, we capture 23,978 artifacts associated with 16,668 (50.2%) appraisal reviews. In contrast, artifacts are found in only 8.9% of listings and 2.7% of non-appraisal reviews. Our study provides valuable insights into this under-explored source of CTI, complementing existing research on threat intelligence gathering.

View More Papers

Securing Lidar Communication through Watermark-based Tampering Detection (Long)

Michele Marazzi, Stefano Longari, Michele Carminati, Stefano Zanero (Politecnico di Milano)

Read More

WIP: Modeling and Detecting Falsified Vehicle Trajectories Under Data...

Jun Ying, Yiheng Feng (Purdue University), Qi Alfred Chen (University of California, Irvine), Z. Morley Mao (University of Michigan and Google)

Read More

EMMasker: EM Obfuscation Against Website Fingerprinting

Mohammed Aldeen, Sisheng Liang, Zhenkai Zhang, Linke Guo (Clemson University), Zheng Song (University of Michigan – Dearborn), and Long Cheng (Clemson University)

Read More

EM Eye: Characterizing Electromagnetic Side-channel Eavesdropping on Embedded Cameras

Yan Long (University of Michigan), Qinhong Jiang (Zhejiang University), Chen Yan (Zhejiang University), Tobias Alam (University of Michigan), Xiaoyu Ji (Zhejiang University), Wenyuan Xu (Zhejiang University), Kevin Fu (Northeastern University)

Read More