False data injection attacks in healthcare

Mohiuddin Ahmed; Abu S.S.M. Barkat Ullah

doi:10.1007/978-981-13-0292-3_12

False data injection attacks in healthcare

Mohiuddin Ahmed, Abu S.S.M. Barkat Ullah

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

10 Citations (Scopus)

Abstract

False data injection attacks (FDIA) are widely studied mainly in the area of smart grid, power systems and wireless sensor networks. In this paper, an overview of the FDIA is proposed including the definition and detection techniques proposed so far. The main focus of this paper is to create awareness about the impact of the FDIA in domains other than smart grid such as healthcare. The impact of FDIA in healthcare is overlooked for last couple of years around the globe. However, the recent information security incidents rise in the healthcare sector reaffirms the requirements of preventive measures for FDIA in healthcare. In this paper, we also focus on the emerging attacks on the healthcare domain to understand the importance of FDIA prevention techniques.

Original language	English
Title of host publication	Data Mining - 15th Australasian Conference, AusDM 2017, Revised Selected Papers
Editors	David Stirling, Yee Ling Boo, Lianhua Chi, Kok-Leong Ong, Lin Liu, Graham Williams
Place of Publication	Singapore
Publisher	Springer
Pages	192-197
Number of pages	6
ISBN (Electronic)	9789811302923
ISBN (Print)	9789811302916
DOIs	https://doi.org/10.1007/978-981-13-0292-3_12
Publication status	Published - 14 Apr 2018
Externally published	Yes
Event	15th Australasian Conference on Data Mining, AusDM 2017 - Melbourne, Australia Duration: 19 Aug 2017 → 20 Aug 2017

Publication series

Name	Communications in Computer and Information Science
Volume	845
ISSN (Print)	1865-0929

Conference

Conference	15th Australasian Conference on Data Mining, AusDM 2017
Country/Territory	Australia
City	Melbourne
Period	19/08/17 → 20/08/17

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-981-13-0292-3_12

https://link.springer.com/book/10.1007/978-981-13-0292-3#about

Cite this

Ahmed, M., & Barkat Ullah, A. S. S. M. (2018). False data injection attacks in healthcare. In D. Stirling, Y. L. Boo, L. Chi, K-L. Ong, L. Liu, & G. Williams (Eds.), Data Mining - 15th Australasian Conference, AusDM 2017, Revised Selected Papers (pp. 192-197). (Communications in Computer and Information Science; Vol. 845). Springer. https://doi.org/10.1007/978-981-13-0292-3_12

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abstract = "False data injection attacks (FDIA) are widely studied mainly in the area of smart grid, power systems and wireless sensor networks. In this paper, an overview of the FDIA is proposed including the definition and detection techniques proposed so far. The main focus of this paper is to create awareness about the impact of the FDIA in domains other than smart grid such as healthcare. The impact of FDIA in healthcare is overlooked for last couple of years around the globe. However, the recent information security incidents rise in the healthcare sector reaffirms the requirements of preventive measures for FDIA in healthcare. In this paper, we also focus on the emerging attacks on the healthcare domain to understand the importance of FDIA prevention techniques.",

keywords = "FDIA, Healthcare, Smart grid",

author = "Mohiuddin Ahmed and {Barkat Ullah}, {Abu S.S.M.}",

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Ahmed, M & Barkat Ullah, ASSM 2018, False data injection attacks in healthcare. in D Stirling, YL Boo, L Chi, K-L Ong, L Liu & G Williams (eds), Data Mining - 15th Australasian Conference, AusDM 2017, Revised Selected Papers. Communications in Computer and Information Science, vol. 845, Springer, Singapore, pp. 192-197, 15th Australasian Conference on Data Mining, AusDM 2017, Melbourne, Australia, 19/08/17. https://doi.org/10.1007/978-981-13-0292-3_12

False data injection attacks in healthcare. / Ahmed, Mohiuddin; Barkat Ullah, Abu S.S.M.
Data Mining - 15th Australasian Conference, AusDM 2017, Revised Selected Papers. ed. / David Stirling; Yee Ling Boo; Lianhua Chi; Kok-Leong Ong; Lin Liu; Graham Williams. Singapore: Springer, 2018. p. 192-197 (Communications in Computer and Information Science; Vol. 845).

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

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False data injection attacks in healthcare

Abstract

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Conference

UN SDGs

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