Identifying Adversary Impact Using End User Verifiable Key with Permutation Framework

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Abstract

In the Internet of Things (IoT), security is a crucial aspect that ensures secure communication, transactions, and authentication for different applications. In IoT security, maintaining the user interface and platform security is a critical issue that needs to be addressed due to leaky security distribution. During communication, synchronisation and security are important problems. The security problems are caused by the adversary impact and vulnerable attacks, leading to service failure. Therefore, the Permutated Security Framework (PSF) is designed to manage security in the IoT by providing secure communication, transactions, and authentication for different applications. The PSF uses time intervals to manage transaction security. These intervals are secured using end-verifiable keys generated using the conventional Rivest–Shamir–Adleman (RSA) technique in IoT-based communication-related applications. In this approach, the key validity is first provided for the interval, and in the latter, the access permitted time modifies its validity. The security of transactions is managed by dividing time into smaller intervals and providing different levels of security for each interval. By using time intervals, the framework is adaptable and adjustable to changes in the system, such as user density and service allocation rate, adapting parallel transactions per support vector classifications’ recommendations. The proposed framework aims to synchronise interval security, service allocation, and user flexibility to mitigate adversary impact, service failures, and service delays while improving the access rate and transactions. This allows for more flexibility and better management of transaction security. The proposed framework reduces adversary impact (10.98%), service failure (11.82%), and service delay (10.19%) and improves the access rate by 7.73% for different transactions.

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APA

Anjum, M., Shahab, S., Yu, Y., & Guye, H. F. (2023). Identifying Adversary Impact Using End User Verifiable Key with Permutation Framework. Electronics (Switzerland), 12(5). https://doi.org/10.3390/electronics12051136

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