创新数据系统研究会议(CIDR)于2002年由Michael Stonebraker、Jim Gray和David DeWitt发起,目的是为数据库社区提供一个展示创新数据系统体系结构的场所以及一个著名的出版机会。CIDR是对主流数据库会议(如SIGMOD和VLDB)的补充,强调系统架构的观点。CIDR汇集了来自学术界和产业界的研究人员和实践者,讨论该领域最新的创新和有远见的想法。CIDR主要鼓励关于创新和风险数据管理系统体系结构思想、系统构建经验和洞察力、丰富的实验研究、具有挑战性的立场声明的论文。CIDR特别重视创新、基于经验的洞察力和远见。 官网地址:http://dblp.uni-trier.de/db/conf/cidr/

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The lack of security measures among the Internet of Things (IoT) devices and their persistent online connection gives adversaries a prime opportunity to target them or even abuse them as intermediary targets in larger attacks such as distributed denial-of-service (DDoS) campaigns. In this paper, we analyze IoT malware and focus on the endpoints reachable on the public Internet, that play an essential part in the IoT malware ecosystem. Namely, we analyze endpoints acting as dropzones and their targets to gain insights into the underlying dynamics in this ecosystem, such as the affinity between the dropzones and their target IP addresses, and the different patterns among endpoints. Towards this goal, we reverse-engineer 2,423 IoT malware samples and extract strings from them to obtain IP addresses. We further gather information about these endpoints from public Internet-wide scanners, such as Shodan and Censys. For the masked IP addresses, we examine the Classless Inter-Domain Routing (CIDR) networks accumulating to more than 100 million (78.2% of total active public IPv4 addresses) endpoints. Our investigation from four different perspectives provides profound insights into the role of endpoints in IoT malware attacks, which deepens our understanding of IoT malware ecosystems and can assist future defenses.

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