A Hybrid Mechanism for Advance IoT Malware Detection

Aijaz Khan, Gaurav Choudhary, Shishir Kumar Shandilya, Durgesh M. Sharma*, Ashish K. Sharma

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

IoT malware analysis is a challenging task for researchers worldwide because of its difficulty. IoT devices lack homogeneous processor architecture and security design, making malware analysis challenging. Therefore, IoT malware detection is a prime focus of research. Various researches have been underway for adequate solutions, adapted in all frames and under a single umbrella. This paper looked at advanced IoT malware detection requirements and proposed a hybrid model to solve the existing problem. We have also provided a background overview of IoT malware, concerning two famous malware samples Mirai and Darlloz, and future research challenges. Furthermore, we have collected, compared, and analyzed the key research in IoT security specifically for malware analysis and attempted to provide critical decision points during the development of security architecture.
Original languageEnglish
Title of host publicationProceedings of the International Conference on IoT, Intelligent Computing and Security
Volume982
PublisherSpringer
Publication date2023
Pages247-259
ISBN (Electronic)978-981-19-8136-4
DOIs
Publication statusPublished - 2023
EventInternational Conference on, Intelligent computing and Security 2021: A Paradigm Shift - Greater Noida, India
Duration: 17 Dec 202118 Dec 2021

Conference

ConferenceInternational Conference on, Intelligent computing and Security 2021
Country/TerritoryIndia
CityGreater Noida
Period17/12/202118/12/2021

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