Long Short-Term Memory-Based Anomaly Detection for IoT Systems with  Blockchain-Enhanced Security and Trust Mechanisms

Sruthi Vaddelli,V.Mary Anita Rajam

Long Short-Term Memory-Based Anomaly Detection for IoT Systems with Blockchain-Enhanced Security and Trust Mechanisms

Authors

Sruthi Vaddelli,V.Mary Anita Rajam

Keywords:

Abstract

The proliferation of IoT systems has introduced significant security vulnerabilities, necessitating robust intrusion detection mechanisms.

References

Smith, J., & Doe, A. (2023). Anomaly Detection Using CNN in IoT. IEEE Transactions on IoT, 20(4), 123-135.

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Published

2023-12-20

How to Cite

Sruthi Vaddelli,V.Mary Anita Rajam. (2023). Long Short-Term Memory-Based Anomaly Detection for IoT Systems with Blockchain-Enhanced Security and Trust Mechanisms. Journal of Computational Analysis and Applications (JoCAAA), 31(4), 2745–2755. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/5190