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A Novel Attack on Complex APUFs Using the Evolutionary Deep Convolutional Neural Network

Intelligent Automation & Soft Computing 2023年第9期37卷 3059-3081页

作者： Ali Ahmadi Shahrakht parisa hajirahimi Omid Rostami Diego Martín Department of Industrial Engineering Sharif University of TechnologyTehran14588-89694Iran Department of Business Administration Boston UniversityBostonMA02215USA Department of Industrial Engineering University of HoustonHoustonTX77204USA ETSI de Telecomunicación Universidad Politécnica de MadridMadrid28040Spain

As the internet of things(IoT)continues to expand rapidly,the significance of its security concerns has grown in recent *** address these concerns,physical unclonable functions(PUFs)have emerged as valuable tools for enhancing IoT *** leverage the inherent randomness found in the embedded hardware of IoT ***,it has been shown that some PUFs can be modeled by attackers using machine-learning-based *** this paper,a new deep learning(DL)-based modeling attack is introduced to break the resistance of complex *** training DL models is a problem that falls under the category of NP-hard problems,there has been a significant increase in the use of meta-heuristics(MH)to optimize DL ***,it is widely recognized that finding the right balance between exploration and exploitation when dealing with complex problems can pose a significant *** address these chal-lenges,a novel migration-based multi-parent genetic algorithm(MBMPGA)is developed to train the deep convolutional neural network(DCNN)in order to achieve a higher rate of accuracy and convergence speed while decreas-ing the run-time of the *** the proposed MBMPGA,a non-linear migration model of the biogeography-based optimization(BBO)is utilized to enhance the exploitation ability of GA.A new multi-parent crossover is then introduced to enhance the exploration ability of *** behavior of the proposed MBMPGA is examined on two real-world optimization *** benchmark problems,MBMPGA outperforms other MH algorithms in convergence *** proposed model are also compared with previous attacking models on several simulated challenge-response pairs(CRPs).The simulation results on the XAPUF datasets show that the introduced attack in this paper obtains more than 99%modeling accuracy even on *** addition,the proposed MBMPGA-DCNN outperforms the state-of-the-art modeling attacks in a reduced timeframe and with a smaller number of requi

关键词： IoT security PUFs modeling attacks evolutionary deep learning migration-based multi-parent genetic algorithm

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Exact identities for sessile drops

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Applied Mathematics and Mechanics(English Edition) 2015年第3期36卷 293-302页

作者： M.hajirahimi F.MOKHTARI A.H.FATOLLAHI Physics Group South Tehran BranchIslamic Azad University Department of Physics Alzahra University

By direct integration of the are presented for the axisymmetric sessile geometrical parameters, including the apex Young-Laplace relation, a set of identities drops on fiat and curved substrates. The curvature, the apex height, and the contact radius, are related by the identities. The validity of the identities is checked by various numerical solutions for drops on flat and curved substrates.

关键词： drop hydrostatics surface tension identity

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Performance evaluation of series and parallel strategies for financial time series forecasting

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Financial Innovation 2017年第1期3卷 357-380页

作者： Mehdi Khashei Zahra hajirahimi Department of industrial and system engineering Isfahan University of TechnologyIsfahanIran

Background:Improving financial time series forecasting is one of the most challenging and vital issues facing numerous financial analysts and decision *** its direct impact on related decisions,various attempts have been made to achieve more accurate and reliable forecasting results,of which the combining of individual models remains a widely applied *** general,individual models are combined under two main strategies:series and *** it has been proven that these strategies can improve overall forecasting accuracy,the literature on time series forecasting remains vague on the choice of an appropriate strategy to generate a more accurate hybrid ***:Therefore,this study’s key aim is to evaluate the performance of series and parallel strategies to determine a more accurate ***:Accordingly,the predictive capabilities of five hybrid models are constructed on the basis of series and parallel strategies compared with each other and with their base models to forecast stock *** do so,autoregressive integrated moving average(ARIMA)and multilayer perceptrons(MLPs)are used to construct two series hybrid models,ARIMA-MLP and MLP-ARIMA,and three parallel hybrid models,simple average,linear regression,and genetic algorithm ***:The empirical forecasting results for two benchmark datasets,that is,the closing of the Shenzhen Integrated Index(SZII)and that of Standard and Poor’s 500(S&P 500),indicate that although all hybrid models perform better than at least one of their individual components,the series combination strategy produces more accurate hybrid models for financial time series forecasting.

关键词： Series and parallel combination strategies Multilayer perceptrons Autoregressive integrated moving average Financial time series forecasting Stock markets

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