During testing utmost all appropriate and suitable strategy needs to be established for consistent fault coverage, improved controllability and observability. The scan chains used in BIST allows some fine control over data propagations that is used as a backdoor to break the security over cryptographic cores. To alleviate these scan-based side-channel attacks, implementing a more inclusive security strategy is required to confuse the attacker and to ensure the key management process which is always a difficult task to task in cryptographic research. In this work for testing AES core Design-for-Testability (DfT) is considered with some random response compaction, bit masking during the scan process. In the proposed scan architecture, scan-based attack does not allow finding out actual computations which are related to the cipher transformations and key sequence. And observing the data through the scan structure is secured. The experimental results validate the potential metrics of the proposed scan model in terms of robustness to the scan attack and penalty gap that exists due to the inclusion of scan designs in AES core. Also investigate the selection of appropriate location points to implement the bit level modification to avoid attack for retrieving a key.
Authentication is a suitable form of restricting the network from different types of attacks, especially in case of fifth-generation telecommunication networks, especially in healthcare applications. The handover and authentication mechanism are one such type that enables mitigation of attacks in health-related services. In this paper, we model an evolutionary model that uses a fuzzy evolutionary model in maintaining the handover and key management to improve the performance of authentication in nanocore technology-based 5G networks. The model is designed in such a way that it minimizes the delays and complexity while authenticating the networks in 5G networks. The attacks are mitigated using an evolutionary model when it is trained with the relevant attack datasets, and the model is validated to mitigate the attacks. The simulation is conducted to test the efficacy of the model, and the results of simulation show that the proposed method is effective in improving the handling and authentication and mitigation against various types of attacks in mobile health applications.
Objective: Preservation of patient’s medical information in health care industries under Medical Sensor Networks (MSN).
Methods: This paper proposes a novel key management technique known as k- secure with FBKM, which generates a robust key to allow communication between sensors present in the Body Sensor Units (BSU) and Body Central Unit (BCU). This proposed work strengthens the FBKM technique which is placed between BCU and the point accessible to medical experts at a remote place in the overall health care monitoring environment.
Results: The FBKM technique has proved its success in authentication and security by improving genuine acceptance rate, false rejection rate, and declining false acceptance rate.
Conclusion: The k- secure with FBKM scheme enhances the performance of the existing FBKM scheme in Medical Sensor Networks.