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Internet of Things Attacks Detection and Classification Using Tiered Hidden Markov Model

Published: 19 February 2019 Publication History

Abstract

Internet of Things (IoT) attacks have rapidly risen in frequency in recent years as IoT devices become more commonplace in industry, businesses, and homes. Since these devices have very basic functionality and are not designed with security in mind, they are easy targets for attacks that can steal data or gain access to the network the devices are connected to. Here we propose a tiered system of Hidden Markov Models (HMMs) for identifying these attacks and classifying them by type of attack. This system has a tree-based structure, with the main HMM being applied to the raw network data to identify attacks. This main HMM branches off into separate HMMs for each type of attack to classify the attacks according to how important the consequences of the attack are and how likely each attack is to happen.

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Cited By

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  • (2024)DAG: A Lightweight and Real-Time Edge Defense Model for IoT DDoS AttacksFrontiers of Networking Technologies10.1007/978-981-97-3890-8_5(61-73)Online publication date: 10-Jul-2024
  • (2020)HMM Based on Baum-Welch Algorithm for Predicting Critical Data Packets in IoT Network2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT49239.2020.9225343(1-6)Online publication date: Jul-2020

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cover image ACM Other conferences
ICSCA '19: Proceedings of the 2019 8th International Conference on Software and Computer Applications
February 2019
611 pages
ISBN:9781450365734
DOI:10.1145/3316615
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 the author(s) 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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  • University of New Brunswick: University of New Brunswick

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Association for Computing Machinery

New York, NY, United States

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Published: 19 February 2019

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Author Tags

  1. Hidden Markov Model
  2. Internet of Things (IoT)
  3. IoT attacks

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Cited By

View all
  • (2024)DAG: A Lightweight and Real-Time Edge Defense Model for IoT DDoS AttacksFrontiers of Networking Technologies10.1007/978-981-97-3890-8_5(61-73)Online publication date: 10-Jul-2024
  • (2020)HMM Based on Baum-Welch Algorithm for Predicting Critical Data Packets in IoT Network2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT49239.2020.9225343(1-6)Online publication date: Jul-2020

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