Back to Search
Journal ArticleOpen Access

SafetyMed: A Novel IoMT Intrusion Detection System Using CNN-LSTM Hybridization

Author Affiliations
Daffodil International University, Jahangirnagar University, Queensland University of Technology, Imam Mohammad ibn Saud Islamic University, ...
Published InElectronics
Year2023
Citations93

Abstract

The Internet of Medical Things (IoMT) has become an attractive playground to cybercriminals because of its market worth and rapid growth. These devices have limited computational capabilities, which ensure minimum power absorption. Moreover, the manufacturers use simplified architecture to offer a competitive price in the market. As a result, IoMTs cannot employ advanced security algorithms to defend against cyber-attacks. IoMT has become easy prey for cybercriminals due to its access to valuable data and the rapidly expanding market, as well as being comparatively easier to exploit.As a result, the intrusion rate in IoMT is experiencing a surge. This paper proposes a novel Intrusion Detection System (IDS), namely SafetyMed, combining Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks to…
View at Publisher

BORR does not host full-text PDFs. The button above takes you to the original publisher.