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Scanning the Scanners: Sensing the Internet from a Massively Distributed Network Telescope

Published: 21 October 2019 Publication History

Abstract

Scanning of hosts on the Internet to identify vulnerable devices and services is a key component in many of today's cyberattacks. Tracking this scanning activity, in turn, provides an excellent signal to assess the current state-of-affairs for many vulnerabilities and their exploitation. So far, studies tracking scanning activity have relied on unsolicited traffic captured in darknets, focusing on random scans of the address space. In this work, we track scanning activity through the lens of unsolicited traffic captured at the firewalls of some 89,000 hosts of a major Content Distribution Network (CDN). Our vantage point has two distinguishing features compared to darknets: (i) it is distributed across some 1,300 networks, and (ii) its servers are live, offering services and thus emitting traffic. While all servers receive a baseline level of probing from Internet-wide scans, i.e., scans targeting random subsets of or the entire IPv4 space, we show that some 30% of all logged scan traffic is the result of localized scans. We find that localized scanning campaigns often target narrow regions in the address space, and that their characteristics in terms of target selection strategy and scanned services differ vastly from the more widely known Internet-wide scans. Our observations imply that conventional darknets can only partially illuminate scanning activity, and may severely underestimate widespread attempts to scan and exploit individual services in specific prefixes or networks. Our methods can be adapted for individual network operators to assess if they are subjected to targeted scanning activity.

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      cover image ACM Conferences
      IMC '19: Proceedings of the Internet Measurement Conference
      October 2019
      497 pages
      ISBN:9781450369480
      DOI:10.1145/3355369
      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 for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Publication History

      Published: 21 October 2019

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      Author Tags

      1. Internet scanning
      2. Internet security
      3. network telescope
      4. unsolicited traffic

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      IMC '19
      IMC '19: ACM Internet Measurement Conference
      October 21 - 23, 2019
      Amsterdam, Netherlands

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      IMC '19 Paper Acceptance Rate 39 of 197 submissions, 20%;
      Overall Acceptance Rate 277 of 1,083 submissions, 26%

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      Cited By

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      • (2024)I Know Who You Scanned Last Summer: Mapping the Landscape of Internet-Wide Scanners2024 IFIP Networking Conference (IFIP Networking)10.23919/IFIPNetworking62109.2024.10619808(222-230)Online publication date: 3-Jun-2024
      • (2024)Have you SYN me? Characterizing Ten Years of Internet ScanningProceedings of the 2024 ACM on Internet Measurement Conference10.1145/3646547.3688409(149-164)Online publication date: 4-Nov-2024
      • (2024)Flow Interaction Graph Analysis: Unknown Encrypted Malicious Traffic DetectionIEEE/ACM Transactions on Networking10.1109/TNET.2024.337085132:4(2972-2987)Online publication date: Aug-2024
      • (2024)A Survey on Enterprise Network Security: Asset Behavioral Monitoring and Distributed Attack DetectionIEEE Access10.1109/ACCESS.2024.341906812(89363-89383)Online publication date: 2024
      • (2024)HoDiNTComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2024.110570250:COnline publication date: 1-Aug-2024
      • (2024)Optimization of Network Mapping for Screening and Intrusion Sensing DevicesCryptology and Network Security with Machine Learning10.1007/978-981-97-0641-9_1(1-19)Online publication date: 23-Apr-2024
      • (2024)Exploring the Discovery Process of Fresh IPv6 Prefixes: An Analysis of Scanning Behavior in Darknet and HoneynetPassive and Active Measurement10.1007/978-3-031-56249-5_4(95-111)Online publication date: 20-Mar-2024
      • (2023)Glowing in the darkProceedings of the 32nd USENIX Conference on Security Symposium10.5555/3620237.3620585(6221-6237)Online publication date: 9-Aug-2023
      • (2023)DSCOPEProceedings of the 32nd USENIX Conference on Security Symposium10.5555/3620237.3620572(5989-6006)Online publication date: 9-Aug-2023
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