System Call Processing Using Lightweight NLP for IoT Behavioral Malware Detection-Reference-Cited by-同舟云学术

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System Call Processing Using Lightweight NLP for IoT Behavioral Malware Detection

Published:2023 Issue: Volume: Page:103-115
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
language:
Short-container-title:

Author:

Carter John^ORCID,Mancoridis Spiros^ORCID,Nkomo Malvin^ORCID,Weber Steven^ORCID,Dandekar Kapil R.^ORCID

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-99-0272-9_7

Reference23 articles.

1. Ali, A.I., Partal, S.Z., Kepke, S., Partal, H.P.: ZigBee and LoRa based wireless sensors for smart environment and IoT applications. In: 2019 1st Global Power, Energy and Communication Conference (GPECOM), pp. 19–23 (2019). https://doi.org/10.1109/GPECOM.2019.8778505

2. An, N., Duff, A., Noorani, M., Weber, S., Mancoridis, S.: Malware anomaly detection on virtual assistants, pp. 124–131, October 2018. https://doi.org/10.1109/MALWARE.2018.8659366

3. Antonakakis, M., et al.: Understanding the mirai botnet. In: 26th USENIX security symposium (USENIX Security 17), pp. 1093–1110 (2017)

4. Aslan, A., Samet, R.: A comprehensive review on malware detection approaches. IEEE Access 8, 6249–6271 (2020). https://doi.org/10.1109/ACCESS.2019.2963724

5. Bilge, L., Dumitraş, T.: Before we knew it: an empirical study of zero-day attacks in the real world. In: Proceedings of the 2012 ACM Conference on Computer and Communications Security. CCS 2012, New York, NY, USA, pp. 833–844. Association for Computing Machinery (2012). https://doi.org/10.1145/2382196.2382284

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1. Using NLP for Functional Size Measurement of IoT Devices;2023 Eleventh International Conference on Intelligent Computing and Information Systems (ICICIS);2023-11-21

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