Novel Deception Techniques for Malware Detection on Industrial Control Systems

• Takanori, Machida

• Dai, Yamamoto

• Yuki, Unno

• Hisashi, Kojima

抄録

To maintain the availability of industrial control systems (ICS), it is important to robustly detect malware infection that spreads within the ICS network. In ICS, a host often communicates with the determined hosts; for instance, a supervisory control host observes and controls the same devices routinely via the network. Therefore, a communication request to the unused internet protocol (IP) address space, i.e., darknet, in the ICS network is likely to be caused by malware in the compromised host in the network. That is, darknet monitoring may enable us to detect malware that tries to spread indiscriminately within the network. On the other hand, clever malware, such as malware determining target hosts of infection with reference to host lists in the networks, infects the confined hosts in the networks, and consequently evades detection by security sensors or honeypots. In this paper, we propose novel deception techniques that lure such malware to our sensor, by embedding the sensor information continuously in the lists of hosts in the ICS networks. In addition, the feasibility of the proposed deception techniques is shown through our simplified implementation by using actual malware samples: WannaCry and Conficker.------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.29(2021) (online)DOI　http://dx.doi.org/10.2197/ipsjjip.29.559------------------------------

To maintain the availability of industrial control systems (ICS), it is important to robustly detect malware infection that spreads within the ICS network. In ICS, a host often communicates with the determined hosts; for instance, a supervisory control host observes and controls the same devices routinely via the network. Therefore, a communication request to the unused internet protocol (IP) address space, i.e., darknet, in the ICS network is likely to be caused by malware in the compromised host in the network. That is, darknet monitoring may enable us to detect malware that tries to spread indiscriminately within the network. On the other hand, clever malware, such as malware determining target hosts of infection with reference to host lists in the networks, infects the confined hosts in the networks, and consequently evades detection by security sensors or honeypots. In this paper, we propose novel deception techniques that lure such malware to our sensor, by embedding the sensor information continuously in the lists of hosts in the ICS networks. In addition, the feasibility of the proposed deception techniques is shown through our simplified implementation by using actual malware samples: WannaCry and Conficker.------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.29(2021) (online)DOI　http://dx.doi.org/10.2197/ipsjjip.29.559------------------------------

収録刊行物

• 情報処理学会論文誌

  情報処理学会論文誌 62 (9), 2021-09-15

キーワード

• [特集：Society 5.0を実現するコンピュータセキュリティ技術] industrial control system (ICS), malware detection, darknet monitoring, honeypot, server message block (SMB), address resolution protocol (ARP)

詳細情報

• CRID: 1050289455246384384
• NII論文ID: 170000185563
• NII書誌ID: AN00116647
• ISSN: 18827764
• Web Site: http://id.nii.ac.jp/1001/00212752/
• 本文言語コード: en
• 資料種別: journal article
• データソース種別:
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  • CiNii Articles