Christopher Bennett, AbdelRahman Abdou, and Paul C. van Oorschot (School of Computer Science, Carleton University, Canada)

Engines that scan Internet-connected devices allow for fast retrieval of useful information regarding said devices, and their running services. Examples of such engines include Censys and Shodan. We present a snapshot of our in-progress effort towards the characterization and systematic evaluation of such engines, herein focusing on results obtained from an empirical study that sheds light on several aspects. These include: the freshness of a result obtained from querying Censys and Shodan, the resources they consume from the scanned devices, and several interesting operational differences between engines observed from the network edge. Preliminary results confirm that the information retrieved from both engines can reflect updates within 24 hours, which aligns with implicit usage expectations in recent literature. The results also suggest that the consumed resources appear insignificant for common Internet applications, e.g., one full application-layer connection (banner grab) per port, per day. Results so far highlight the value of such engines to the research community

View More Papers

Reinforcement Learning-based Hierarchical Seed Scheduling for Greybox Fuzzing

Jinghan Wang (University of California, Riverside), Chengyu Song (University of California, Riverside), Heng Yin (University of California, Riverside)

Read More

A Devil of a Time: How Vulnerable is NTP...

Yarin Perry (The Hebrew University of Jerusalem), Neta Rozen-Schiff (The Hebrew University of Jerusalem), Michael Schapira (The Hebrew University of Jerusalem)

Read More

FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping

Xiaoyu Cao (Duke University), Minghong Fang (The Ohio State University), Jia Liu (The Ohio State University), Neil Zhenqiang Gong (Duke University)

Read More

(Short) Fooling Perception via Location: A Case of Region-of-Interest...

Kanglan Tang, Junjie Shen, and Qi Alfred Chen (UC Irvine)

Read More