Voltage Over-scaling-based Lightweight Authentication for IoT Security
ABSTARCT :
It is a challenging task to deploy lightweight security protocols in resource-constrained IoT applications. A hardware-oriented lightweight authentication protocol based on device signature generated during voltage over-scaling (VOS) was recently proposed to address this issue. VOS-based authentication employs the computation unit such as adders to generate the process variation dependent error which is combined with secret keys to create a two-factor authentication protocol. In this paper, machine learning (ML)-based modeling attacks to break such authentication is presented. We also propose a \underline{c}hallenge \underline{s}elf-\underline{o}bfuscation \underline{s}tructure (CSoS) which employs previous challenges combined with keys or random numbers to obfuscate the current challenge for the VOS-based authentication to resist ML attacks. Experimental results show that ANN, RNN and CMA-ES can clone the challenge-response behavior of VOS-based authentication with up to 99.65% prediction accuracy, while the prediction accuracy is less than 51.2% after deploying our proposed ML resilient technique. In addition, our proposed CSoS also shows good obfuscation ability for strong PUFs. Experimental results show that the modeling accuracies are below 54% when $10^6$ challenge-response pairs (CRPs) are collected to model the CSoS-based Arbiter PUF with ML attacks such as LR, SVM, ANN, RNN and CMA-ES.
EXISTING SYSTEM :
? In some of the above studies such as the focus of the authors is on approach to solve energy management problem, However, the transfer of a massive amount of data on the existing communication infrastructure is challenging.
? We have presented a comprehensive study of existing memristor based hardware authentication techniques and their weaknesses for extending the state-of-the-art for memory component dependent authentication techniques.
? Existing time offset based data level detection techniques can only detect spoofing if there is a discontinuous change in time, caused by a step change in the GPS reference.
? Our approach is a data-level detection mechanism, no change to the receiver architecture is required to integrate our countermeasure as an add-on to existing systems.
DISADVANTAGE :
? In the device authentication, the response bit is ‘0’ or ‘1’, which is a binary classification problem.
? It is appropriate for medium-scale complex optimization problems.
? It combines the reliability and globality of ES with the adaptiveness of covariance matrices, and can solve complex multiple peak optimization problems.
? To address this problem, we develop a simple, fast, and tamper-proof hardware dependent signal authentication and spoofing detection mechanism for civilian navigation signals.
? This problem can be addressed by using differential measurement techniques where the resistance of the memristor is compared with other fixed resistors with different resistances.
PROPOSED SYSTEM :
• In this paper the grey wolf optimizer (GWO), artificial bee colony (ABC) optimization algorithm-based Time of Use (ToU) pricing model is proposed to define the rates for shoulder-peak and on-peak hours.
• In this paper, a novel real-time electricity scheduling for smart demand side management system using the IoT is proposed that employs: scalability, adaptability, Interoperability and connectivity between appliances over cloud platforms.
• The proposed system offered analytics and business intelligence (BI), which allowed the researchers to gain insights on the data collected by visualizing dashboards and reports.
• The researchers proposed the IoT platform for collecting the data, monitoring, managing and controlling microgrid.
ADVANTAGE :
? The key to constructing a good SVM is to maximize the margin while minimizing classification errors, and the whole process is regulated by the regularization coefficient.
? CSoS is not only efficient for VOLtA but also can be deployed for strong PUFs and exhibits good obfuscation ability.
? The attackers need to select effective training set in massive data and build an efficient model. Therefore, it is impossible for attackers to clone the CSoS-based authentication by brute-force attacks.
? VOS is a common power reduction technology and can be used for approximate computing.
? The common logic gates include NOT gate, AND gate, OR gate, and XOR gate, where the XOR gate is linearly inseparable, and hence it is often used to encrypt information in cryptography.
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