Embedding Security Awareness in IoT Systems: A Framework for Providing Change Impact Insights
The Internet of Things (IoT) is rapidly advancing toward increased autonomy; however, the inherent dynamism, environmental uncertainty, device heterogeneity, and diverse data modalities pose serious challenges to its reliability and security. This paper proposes a novel framework for embedding secur...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-07-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/14/7871 |
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| author | Masrufa Bayesh Sharmin Jahan |
| author_facet | Masrufa Bayesh Sharmin Jahan |
| author_sort | Masrufa Bayesh |
| collection | DOAJ |
| description | The Internet of Things (IoT) is rapidly advancing toward increased autonomy; however, the inherent dynamism, environmental uncertainty, device heterogeneity, and diverse data modalities pose serious challenges to its reliability and security. This paper proposes a novel framework for embedding security awareness into IoT systems—where security awareness refers to the system’s ability to detect uncertain changes and understand their impact on its security posture. While machine learning and deep learning (ML/DL) models integrated with explainable AI (XAI) methods offer capabilities for threat detection, they often lack contextual interpretation linked to system security. To bridge this gap, our framework maps XAI-generated explanations to a system’s structured security profile, enabling the identification of components affected by detected anomalies or threats. Additionally, we introduce a procedural method to compute an Importance Factor (IF) for each component, reflecting its operational criticality. This framework generates actionable insights by highlighting contextual changes, impacted components, and their respective IFs. We validate the framework using a smart irrigation IoT testbed, demonstrating its capability to enhance security awareness by tracking evolving conditions and providing real-time insights into potential Distributed Denial of Service (DDoS) attacks. |
| format | Article |
| id | doaj-art-082ca7c368c345c4bbd36d4a5eed1520 |
| institution | DOAJ |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-082ca7c368c345c4bbd36d4a5eed15202025-08-20T03:13:42ZengMDPI AGApplied Sciences2076-34172025-07-011514787110.3390/app15147871Embedding Security Awareness in IoT Systems: A Framework for Providing Change Impact InsightsMasrufa Bayesh0Sharmin Jahan1Department of Computer Science, Oklahoma State University, Stillwater, OK 74078, USADepartment of Computer Science, Oklahoma State University, Stillwater, OK 74078, USAThe Internet of Things (IoT) is rapidly advancing toward increased autonomy; however, the inherent dynamism, environmental uncertainty, device heterogeneity, and diverse data modalities pose serious challenges to its reliability and security. This paper proposes a novel framework for embedding security awareness into IoT systems—where security awareness refers to the system’s ability to detect uncertain changes and understand their impact on its security posture. While machine learning and deep learning (ML/DL) models integrated with explainable AI (XAI) methods offer capabilities for threat detection, they often lack contextual interpretation linked to system security. To bridge this gap, our framework maps XAI-generated explanations to a system’s structured security profile, enabling the identification of components affected by detected anomalies or threats. Additionally, we introduce a procedural method to compute an Importance Factor (IF) for each component, reflecting its operational criticality. This framework generates actionable insights by highlighting contextual changes, impacted components, and their respective IFs. We validate the framework using a smart irrigation IoT testbed, demonstrating its capability to enhance security awareness by tracking evolving conditions and providing real-time insights into potential Distributed Denial of Service (DDoS) attacks.https://www.mdpi.com/2076-3417/15/14/7871IoTchange impactImportance Factorsecurity awareness |
| spellingShingle | Masrufa Bayesh Sharmin Jahan Embedding Security Awareness in IoT Systems: A Framework for Providing Change Impact Insights Applied Sciences IoT change impact Importance Factor security awareness |
| title | Embedding Security Awareness in IoT Systems: A Framework for Providing Change Impact Insights |
| title_full | Embedding Security Awareness in IoT Systems: A Framework for Providing Change Impact Insights |
| title_fullStr | Embedding Security Awareness in IoT Systems: A Framework for Providing Change Impact Insights |
| title_full_unstemmed | Embedding Security Awareness in IoT Systems: A Framework for Providing Change Impact Insights |
| title_short | Embedding Security Awareness in IoT Systems: A Framework for Providing Change Impact Insights |
| title_sort | embedding security awareness in iot systems a framework for providing change impact insights |
| topic | IoT change impact Importance Factor security awareness |
| url | https://www.mdpi.com/2076-3417/15/14/7871 |
| work_keys_str_mv | AT masrufabayesh embeddingsecurityawarenessiniotsystemsaframeworkforprovidingchangeimpactinsights AT sharminjahan embeddingsecurityawarenessiniotsystemsaframeworkforprovidingchangeimpactinsights |