To solve the low attack path quantification degree and complex path finding in the industrial Internet of Things, a vulnerability assessment method based on attack graph and maximum flow is proposed. The method takes into account the factors influencing the attack behavior and relationship between network nodes. The attack risk is calculated by common vulnerability scoring system, which increases the attack path quantification degree. The maximum loss flow describes the attack path, evaluates the network vulnerability by maximum loss flow and loss saturation and represents the vulnerability relevance. Avoiding the repeat calculation and obtaining the potential key vulnerability path fast, the augmented road algorithm is used to find optimal attack path within global path. The result shows that the method is feasible and can evaluate the vulnerability and risk path objectively.

A Vulnerability Assessment Method in Industrial Internet of Things Based on Attack Graph and Maximum Flow

Stress Distributions in Girder-Arch-Pier Connections of Long-Span Continuous Rigid Frame Arch Railway Bridges

In recent years, with the rapid development of industrial Internet of Things, the rapid growth of data has become a severe challenge and precious opportunity faced by many industries. The information society has entered the era of big data. Feature selection is frequently used to reduce the number of features in many applications of Internet of things, where data of high dimensionality are involved. To the best of our knowledge, a fewer researchers focus on the physical distribution of data and the anisotropy of the data characteristics. To this end, this paper introduces a novel feature selection approach based on potential entropy evaluation criteria (FMPE). The FMPE method considers the distribution of the data itself when measuring the importance of the feature. The data is mapped into a high-dimensional space which has better divisibility by extending data field to generalized multidimensional data field. Related experiments and analyses on UCI data sets and face data sets show that the FMPE algorithm can effectively eliminate the unimportant features or noise features to improve the performance of the classification algorithm. A high classification accuracy is achieved by the combination of the selected feature subset and a variety of classifiers and the FMPE algorithm is independent of the specific classifier.

An Industrial Internet of Things Feature Selection Method Based on Potential Entropy Evaluation Criteria

The control method and dynamic performance of a magnetic suspension system, which is the core component of maglev trains, have a significant influence on the performance of the maglev train. Currently, a control strategy based on the current feedback is widely used. However, the stable range of control parameters is relatively small, making it difficult to identify stable regions for the control parameters. In addition, the strong interactions between the control parameters are cause issues in the control. In this paper, a control strategy based on the flux density observer is proposed using an analysis of the working principle and the structure of the suspension system. A nonlinear dynamic model of a maglev system is established by utilizing the state equation of the flux feedback. Based on the current and voltage feedback, a hybrid magnetic flux density observer is presented. According to the mathematical model, an adaptive sliding mode controller is designed to reduce the upper bound of both uncertainty and interference of the sliding mode controller. Finally, a theoretical analysis and the effectiveness of the proposed control strategy are verified using both simulations and experiments.

Dynamic Modeling and Adaptive Sliding Mode Control for a Maglev Train System Based on a Magnetic Flux Observer

GeFeS: A generalized wrapper feature selection approach for optimizing classification performance.

Complex bridges will inevitably have cracks in operation. Dynamic characteristics with crack structures have been researched central issues. In the past, few researches were conducted from the whole structure of bridges with multi-cracks. In the meanwhile, related experimental research and systematic numerical simulation were lacking. In addition, researches on cracks seldom considered the high-order vibration characteristics of structures with multi-cracks. Aimed at this problem, this paper selected the whole bridge structure which was widely applied in engineering to study dynamic characteristics. For the concrete steel bridge with two cracks, this paper established finite element models for concrete steel beam and bridge with cracks under three different conditions and obtained vibration frequency and three order modes through simulation. Then, this paper analyzed and verified the correctness of numerical simulation result through experiment. Based on the verified model, this paper conducted a systematic analysis and summary, and obtained the following findings: The vibration frequency of concrete steel beams with cracks was obviously affected by cracks. The higher the order was, the greater the impact of cracks on frequency would be and the smaller the impact of cracks on the amplitude of modes would be. With the increased crack depth, the impact on the vibration frequency of concrete steel beams was more obvious. Additionally, crack distance also had some impacts on the dynamic characteristics of concrete steel beams. Numerical simulation model and method in this paper provided foundation and reference for continuing to analyze concrete steel beams with other crack forms or other structural forms. In the meanwhile, the three-dimensional analytical contour in this paper could help engineers to more intuitively understand and valuably apply the change rule of impact of crack depth and position on concrete steel beams.

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Experimental research and finite element analysis on the dynamic characteristics of concrete steel bridges with multi-cracks

The undrained shear strength of clay is an important parameter for the design of embankments, shallow foundations, and pile foundations. Among the various methods of testing undrained strength, the simple shear is essential when the shearing mode of the soil surrounding the pile is similar to that in a simple shear test. This study employs a series of undrained strength tests with a Berkeley simple shear apparatus. Three reconstituted natural clays and one artificial clay were tested with a range of coefficients of consolidation. The influence factors, including sample pre-consolidation pressure, saturation back pressure, shearing rate, height of specimen, consolidation stress, and lateral stress ratio, were investigated in undrained simple shear tests. The failure mode in simple shear and corresponding strength parameters are also examined. Based on the test data set, models for describing the undrained strength with simple shear for high plasticity clays are developed and compared to test data for normally consolidated reconstituted clay. Good agreement between models and intact Onsoy clay is also observed when allowance is made for the coefficient of consolidation and strength parameters of undisturbed clay and in situ stress state.

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Wen-heng Yang

Papers

Experimental research and finite element analysis on the dynamic characteristics of concrete steel bridges with multi-cracks

Undrained strength of clay determined from simple shear test