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Optimal monitoring and attack detection of networks modeled by Bayesian attack graphs

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Cybersecurity 2024年第1期7卷 1-15页

作者： Armita Kazeminajafabadi mahdi Imani Department of Electrical and Computer Engineering Northeastern UniversityBostonMAUSA

Early attack detection is essential to ensure the security of complex networks,especially those in critical *** is particularly crucial in networks with multi-stage attacks,where multiple nodes are connected to external sources,through which attacks could enter and quickly spread to other network *** attack graphs(BAGs)are powerful models for security risk assessment and mitigation in complex networks,which provide the probabilistic model of attackers’behavior and attack progression in the *** attack detection techniques developed for BAGs rely on the assumption that network compromises will be detected through routine monitoring,which is unrealistic given the ever-growing complexity of *** paper derives the optimal minimum mean square error(MMSE)attack detection and monitoring policy for the most general form of *** exploiting the structure of BAGs and their partial and imperfect monitoring capacity,the proposed detection policy achieves the MMSE optimality possible only for linear-Gaussian state space models using Kalman *** adaptive resource monitoring policy is also introduced for monitoring nodes if the expected predictive error exceeds a user-defined *** and efficient matrix-form computations of the proposed policies are provided,and their high performance is demonstrated in terms of the accuracy of attack detection and the most efficient use of available resources using synthetic Bayesian attack graphs with different topologies.

关键词： Multi-stage attacks Bayesian attack graph Attack detection Optimal monitoring

Improving mobile mass monitoring in the IoT environment based on Fog computing using an improved forest optimization algorithm

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Journal of Control and Decision 2024年第1期11卷 36-49页

作者： Tahere Motedayen mahdi Yaghoobi Maryam Kheirabadi Department of Computer Engineering Neyshabur BranchIslamic Azad UniversityNeyshaburIran

In the IoT-based users monitor tasks in the network environment by participating in the data collection process by smart *** monitor their data in the form of fog computing(mobile mass monitoring).Service providers are required to pay user rewards without increasing platform *** of the NP-Hard methods to maximise the coverage rate and reduce the platform costs(reward)is the Cooperative Based Method for Smart Sensing Tasks(CMST).This article uses chaos theory and fuzzy parameter setting in the forest optimisation *** proposed method is implemented with *** average findings show that the network coverage rate is 31%and the monitoring cost is 11%optimised compared to the CMST scheme and the mapping of the mobile mass monitoring problem to meta-heuristic *** using the improved forest optimisation algorithm can reduce the costs of the mobile crowd monitoring platform and has a better coverage rate.

关键词： Internet of Things mobile mass monitoring forest optimization algorithm chaos theory fuzzy system

Data-driven Distributionally Adjustable Robust Chance-constrained DG Capacity Assessment

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 115-127页

作者： Masoume Mahmoodi Seyyed mahdi Noori Rahim Abadi Ahmad Attarha Paul Scott Lachlan Blackhall the College of Engineering and Computer Science The Australian National UniversityCanberraAustralia

Moving away from fossil fuels towards renewable sources requires system operators to determine the capacity of distribution systems to safely accommodate green and distributed generation(DG).However,the DG capacity of a distribution system is often underestimated due to either overly conservative electrical demand and DG output uncertainty modelling or neglecting the recourse capability of the available *** improve the accuracy of DG capacity assessment,this paper proposes a distributionally adjustable robust chance-constrained approach that utilises uncertainty information to reduce the conservativeness of conventional robust *** proposed approach also enables fast-acting devices such as inverters to adjust to the real-time realisation of uncertainty using the adjustable robust counterpart *** achieve a tractable formulation,we first define uncertain chance constraints through distributionally robust conditional value-at-risk(CVaR),which is then reformulated into convex quadratic *** subsequently solve the resulting large-scale,yet convex,model in a distributed fashion using the alternating direction method of multipliers(ADMM).Through numerical simulations,we demonstrate that the proposed approach outperforms the adjustable robust and conventional distributionally robust approaches by up to 15%and 40%,respectively,in terms of total installed DG capacity.

关键词： Distributed generation(DG)capacity assessment distributionally robust optimisation chance-constrained optimisation distribution system

Kink-band Kinematic Analysis and its Implications for Late-stage Deformation in the Internal Parts of the Zagros Collision(Sanandaj–Sirjan Zone) in West Iran

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Acta Geologica Sinica(English Edition) 2024年第04期 921-935页

作者： Maryam HEYDARI mahdi BEHYARI Department of Geology Faculty of Sciences Urmia University

In the internal parts of the Zagros collision zone, several deformation phases have been superimposed. The early deformation phase caused the development of a penetrative foliation. The late-stage deformation phase was preferentially accommodated within shear zones and caused the generation of shear bands, implying a non-coaxial component of deformation, the end of this stage deformation was marked by the development of kink-bands. In the vicinity of Zagros suture zone, the kink angle increased from 40° to 60°, and the kink-bands was converted to chevron folds. In this region, the external(α) and internal(β) angular ratio is α/β ≠ 1 and kink angle increased, and deformation occurred with 10% to 30% volume loss. Farther from the suture zone in the east, α/β = 1; and total volume was constant or increased by 5% to 10%. Kink-bands kinematic analysis in the study area revealed this structures were sensitive to deformation conditions and components such that, with decreasing distance to the Zagros suture zone, shearing and rotation increased, a high kinematic vorticity dominated, and volume loss occurred during deformation.

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Advanced Machine Learning Methods for Prediction of Blast-Induced Flyrock Using Hybrid SVR Methods

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1595-1617页

作者： Ji Zhou Yijun Lu Qiong Tian Haichuan Liu mahdi Hasanipanah Jiandong Huang College of Civil and Environmental Engineering Hunan University of Science and EngineeringYongzhou425006China Hunan Provincial Key Laboratory of Intelligent Protection and Utilization Technology in Masonry Artifacts Hunan University of Science and EngineeringYongzhou425006China School of Civil Engineering Guangzhou UniversityGuangzhou510006China Institute of Research and Development Duy Tan UniversityDa Nang550000Vietnam School of Engineering&Technology Duy Tan UniversityDa Nang550000Vietnam

Blasting in surface mines aims to fragment rock masses to a proper ***,flyrock is an undesirable effect of blasting that can result in human *** this study,support vector regression(SVR)is combined with four algorithms:gravitational search algorithm(GSA),biogeography-based optimization(BBO),ant colony optimization(ACO),and whale optimization algorithm(WOA)for predicting flyrock in two surface mines in ***,three other methods,including artificial neural network(ANN),kernel extreme learning machine(KELM),and general regression neural network(GRNN),are employed,and their performances are compared to those of four hybrid SVR *** modeling,the measured and predicted flyrock values are validated with some performance indices,such as root mean squared error(RMSE).The results revealed that the SVR-WOA model has the most optimal accuracy,with an RMSE of 7.218,while the RMSEs of the KELM,GRNN,SVR-GSA,ANN,SVR-BBO,and SVR-ACO models are 10.668,10.867,15.305,15.661,16.239,and 18.228,***,combining WOA and SVR can be a valuable tool for accurately predicting flyrock distance in surface mines.

关键词： Flyrock induced by blasting optimization algorithms SVR GRNN

High resolution sequence stratigraphy of the Mishrif Formation(Cenomanian-Early Turonian)at zubair oilfield(al-rafdhiah dome),southern Iraq

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Petroleum Research 2024年第1期9卷 61-71页

作者： Aymen A.Lazim Maher J.Ismail Maher M.mahdi Geoscience Department Zubair Field Operation DivisionBasra Oil CompanyIraq Basrah Oil Company WQ1 FODBasrahIraq University of Basrah College of ScienceGeology Dept.BasrahIraq

The Mishrif Formation(Cenomanian-E Turonian)is one of the most important geological formations in the Middle East and Iraq because it contains enormous petroleum *** is considered to be the first reservoir in the region,and is still being studied because of its economic *** carbonate of the Mishrif Formation derives from a variety of depositional settings,including mid-ramp,shoal,lagoon,and *** five main microfacies discussed in this paper are wackestone,packstone,grainstone,floatstone,and *** most frequent fossilised components found in the Mishrif Formation are rudists,benthic foraminifera,echinoderms,burrows molluscs,and *** to the microfacies and analysed wireline log data,the sequence stratigraphy of the studied formation is composed of two regression *** parasequences of transgressive-regressive cycles make up the depositional sequence of the Mishrif *** standard depositional environments seem to demonstrate a gradual regression,beginning with a short period of the outer ramp,then a steady period of the mid-ramp,and ending in the intertidal ***,the study recorded two regional maximum flooding surfaces:K-135 and *** former is present in the lowermost part of the formation,while the other lies in the *** study shows a close relationship between facies(environments)and hydrocarbon *** increased accumulation focuses on the lower part of the studied formation,and seems to be lower in the upper part of the formation as a result of changes in the environment of deposition.

关键词： Mishrif formation Cenomanian Sequence stratigraphy Zubair oilfield Iraq

An Electrical Impedance Imaging System Towards Edge Intelligence for Non-Destructive Testing of Concrete

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Tsinghua Science and Technology 2024年第3期29卷 883-896页

作者： Abolfazl Roshanpanah mahdi Abbasi Hani Attar Ayman Amer Mohammad R.Khosravi Ahmed A.Solyman Department of Electrical Engineering Islamic Azad UniversityScience and Research BranceTehran ***Iran Department of Computer Engineering Bu-Ali Sina UniversityHamedan ***Iran Department of Energy Engineering Zarqa UniversityZarqa 13110Jordan Department of Computer Engineering Persian Gulf UniversityBushehr ***Iran Department of Electrical and Electronics Engineering Faculty of Engineering and ArchitectureNişantaşıUniversityIstanbul 34398Turkey

In the construction industry,to prevent accidents,non-destructive tests are necessary and *** impedance tomography is a new technology in non-invasive imaging in which the image of the inner part of conductive bodies is reconstructed by the arrays of external electrodes that are connected on the periphery of the *** equipment is cheap,fast,and edge *** this imaging method,the image of electrical conductivity distribution(or its opposite;electrical impedance)of the internal parts of the target object is *** image reconstruction process is performed by injecting a precise electric current to the peripheral boundaries of the object,measuring the peripheral voltages induced from it and processing the collected *** an electrical impedance tomography system,the voltages measured in the peripheral boundaries have a non-linear equation with the electrical conductivity *** paper presents a cheap Electrical Impedance Tomography(EIT)instrument for detecting impurities in the concrete.A voltage-controlled current source,a micro-controller,a set of multiplexers,a set of electrodes,and a personal computer constitute the structure of the *** conducted tests on concrete with impurities show that the designed EIT system can reveal impurities with a good accuracy in a reasonable time.

关键词： non-destructive testing system concrete electrical impedance tomography

Efficient ECG classification based on Chi-square distance for arrhythmia detection

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Journal of Electronic Science and Technology 2024年第2期22卷 1-15页

作者： Dhiah Al-Shammary Mustafa Noaman Kadhim Ahmed M.mahdi Ayman Ibaida Khandakar Ahmedb College of Computer Science and Information Technology University of Al-QadisiyahAl Diwaniyah58001Iraq Intelligent Technology Innovation Lab Victoria UniversityMelbourne3011Australia

This study introduces a new classifier tailored to address the limitations inherent in conventional classifiers such as K-nearest neighbor(KNN),random forest(RF),decision tree(DT),and support vector machine(SVM)for arrhythmia *** proposed classifier leverages the Chi-square distance as a primary metric,providing a specialized and original approach for precise arrhythmia *** optimize feature selection and refine the classifier’s performance,particle swarm optimization(PSO)is integrated with the Chi-square distance as a fitness *** synergistic integration enhances the classifier’s capabilities,resulting in a substantial improvement in accuracy for arrhythmia *** results demonstrate the efficacy of the proposed method,achieving a noteworthy accuracy rate of 98% with PSO,higher than 89% achieved without any previous *** classifier outperforms machine learning(ML)and deep learning(DL)techniques,underscoring its reliability and superiority in the realm of arrhythmia *** promising results render it an effective method to support both academic and medical communities,offering an advanced and precise solution for arrhythmia detection in electrocardiogram(ECG)data.

关键词： Arrhythmia classification Chi-square distance Electrocardiogram(ECG)signal Particle swarm optimization(PSO)

Using neural network modeling to improve the detection accuracy of land subsidence due to groundwater withdrawal

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Journal of Mountain Science 2024年第7期21卷 2320-2333页

作者： Ali M.RAJABI Ali EDALAT Yasaman ABOLGHASEMI mahdi KHODAPARAST Department of Engineering Geology University of TehranTehran ***Iran Department of Civil Engineering University of QomQom ***Iran

Despite the high efficiency of remote sensing methods for rapid and large-scale detection of subsidence phenomena,this technique has limitations such as atmospheric impact and temporal and spatial decorrelation that affect the accuracy of the *** paper proposes a method based on an artificial neural network to improve the results of monitoring land subsidence due to groundwater overexploitation by radar interferometry in the Aliabad plain(Central Iran).In this regard,vertical ground deformations were monitored over 18 months using the Sentinel-1A SAR *** model the land subsidence by a multilayer perceptron(MLP)artificial neural network,four parameters,including groundwater level,alluvial thickness,elastic modulus,and transmissivity have been *** model's generalizability was assessed using data derived for 144 *** to the results,the neural network estimates the land subsidence at each ground point with an accuracy of 6.8 mm.A comparison between the predicted and actual values indicated a significant *** MLP model can be used to improve the results of subsidence detection in the study area or other areas with similar characteristics.

关键词： DInSAR Land subsidence Groundwater withdrawal Aliabad plain Artificial neural network