Optimization mechanism of attack and defense strategy in honeypot game with evidence for deception by Lihua SONG, Yangyang JIANG, Changyou XING, Guomin ZHANG

“…Using game theory to optimize honeypot behavior is an important method in improving defender’s trapping ability.Existing work tends to use over simplified action spaces and consider isolated game stages.A game model named HoneyED with expanded action spaces and covering comprehensively the whole interaction process between a honeypot and its adversary was proposed.The model was focused on the change in the attacker’s beliefs about its opponent’s real identity.A pure-strategy-equilibrium involving belief was established for the model by theoretical analysis.Then, based on the idea of deep counterfactual regret minimization (Deep-CFR), an optimization algorithm was designed to find an approximate hybrid-strategy-equilibrium.Agents for both sides following hybrid strategies from the approximate equilibrium were obtained.Theoretical and experimental results show that the attacker should quit the game when its belief reaches a certain threshold for maximizing its payoff.But the defender’s strategy is able to maximize the honeypot’s profit by reducing the attacker’s belief to extend its stay as long as possible and by selecting the most suitable response to attackers with different deception recognition abilities.…”
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Optimized detection of insertions/deletions (INDELs) in whole-exome sequencing data. by Bo-Young Kim, Jung Hoon Park, Hye-Yeong Jo, Soo Kyung Koo, Mi-Hyun Park

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Optimization of microwave components using machine learning and rapid sensitivity analysis by Slawomir Koziel, Anna Pietrenko-Dabrowska

“…Domain confinement reduces the cost of surrogate model establishment and improves its predictive power. …”
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Shape optimization of non-uniform parametric piezoelectric energy harvester beam by Milad Hasani, Hossein Shahverdi

“…Results indicate that optimization significantly improves the power density of conventional cantilever piezoelectric beams, achieving high power outputs without the need for complex structures. …”
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Binary program taint analysis optimization method based on function summary by Pan YANG, Fei KANG, Hui SHU, Yuyao HUANG, Xiaoshao LYU

“…Taint analysis is a popular software analysis method, which has been widely used in the field of information security.Most of the existing binary program dynamic taint analysis frameworks use instruction-level instrumentation analysis methods, which usually generate huge performance overhead and reduce the program execution efficiency by several times or even dozens of times.This limits taint analysis technology’s wide usage in complex malicious samples and commercial software analysis.An optimization method of taint analysis based on function summary was proposed, to improve the efficiency of taint analysis, reduce the performance loss caused by instruction-level instrumentation analysis, and make taint analysis to be more widely used in software analysis.The taint analysis method based on function summary used function taint propagation rules instead of instruction taint propagation rules to reduce the number of data stream propagation analysis and effectively improve the efficiency of taint analysis.For function summary, the definition of function summary was proposed.And the summary generation algorithms of different function structures were studied.Inside the function, a path-sensitive analysis method was designed for acyclic structures.For cyclic structures, a finite iteration method was designed.Moreover, the two analysis methods were combined to solve the function summary generation of mixed structure functions.Based on this research, a general taint analysis framework called FSTaint was designed and implemented, consisting of a function summary generation module, a data flow recording module, and a taint analysis module.The efficiency of FSTaint was evaluated in the analysis of real APT malicious samples, where the taint analysis efficiency of FSTaint was found to be 7.75 times that of libdft, and the analysis efficiency was higher.In terms of accuracy, FSTaint has more accurate and complete propagation rules than libdft.…”
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Stability Evaluation Method for Rock Slope-Anchorage Systems Based on Genetic Algorithms and Discrete Element Analysis by Peng Xia, Bowen Zeng, Yiheng Pan

“…The findings indicate that (1) the proposed evaluation method effectively accounts for the interaction between the anchorage structure and the rock slope, ensuring accurate results; (2) the method leverages the discrete element numerical model to quantitatively assess deformation and stress distribution within the system; (3) the integration of genetic algorithms significantly enhances the efficiency of identifying the most representative numerical model, and thereby the efficiency of stability evaluation is improved; and (4) the evaluation framework is capable of performing dynamic analyses of the stability evolution throughout the entire operational lifecycle of the rock slope anchorage system.…”
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Classification of finger movements through optimal EEG channel and feature selection by Murside Degirmenci, Yilmaz Kemal Yuce, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Yalcin Isler

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Enhancing LoRaWAN Performance Using Boosting Machine Learning Algorithms Under Environmental Variations by Maram A. Alkhayyal, Almetwally M. Mostafa

“…Bayesian Optimization was applied to fine-tune hyperparameters to improve model accuracy. …”
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Research on Path Optimization of Vehicle-Drone Joint Distribution considering Customer Priority by Xiaoye Zhou, Yuhao Feng

“…Second, a two-stage hybrid algorithm is proposed for the problem model. In the first stage, the deep neural network and the grid search improved support vector machine algorithm (DNN-GSM-SVM) are used to screen and classify customer priority features, and in the second stage, adaptive large-scale neighborhood search improved genetic algorithms (ALNS-GA) are used to solve the problem of vehicle-drone joint distribution path planning problem. …”
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Robust Adaptive Path Tracking Control Scheme for Safe Autonomous Driving via Predicted Interval Algorithm by Cong Phat Vo, Jungeun Lee, Jeong Hwan Jeon

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Smallest-Small-World Cellular Harmony Search for Optimization of Unconstrained Benchmark Problems by Sung Soo Im, Do Guen Yoo, Joong Hoon Kim

“…Harmony search has successfully been applied to a wide variety of practical optimization problems. Most of the previous researches have sought to improve the performance of the HS algorithm by changing the pitch adjusting rate and harmony memory considering rate. …”
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Optimization of Flight Scheduling in Urban Air Mobility Considering Spatiotemporal Uncertainties by Lingzhong Meng, Minggong Wu, Xiangxi Wen, Zhichong Zhou, Qingguo Tian

“…Additionally, the proposed phased artificial lemming algorithm (ALA) outperforms traditional optimization algorithms in terms of solution quality. …”
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Selective opposition based constrained barnacle mating optimization: Theory and applications by Marzia Ahmed, Mohd Herwan Sulaiman, Md. Maruf Hassan, Md. Atikur Rahaman, Masuk Abdullah

“…In addition to increasing efficiency by cutting down on wasted time spent exploring, this also increases the likelihood of stumbling onto optimal solutions. After that, it is put through its paces in a real-world case study, where it proves to be superior to the most cutting-edge algorithms available.…”
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Tuning of Kalman Filter Parameters via Genetic Algorithm for State-of-Charge Estimation in Battery Management System by T. O. Ting, Ka Lok Man, Eng Gee Lim, Mark Leach

“…This is the motivation for the application of a metaheuristic algorithm. Hence, the result is further improved by applying a genetic algorithm (GA) to tune Q and R parameters of the KF. …”
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Precision Measurement and Feature Selection in Medical Diagnostics using Hybrid Genetic Algorithm and Support Vector Machine by Gowri Subadra K, Sathish Babu P

“…In the proposed method, GA is used to identify the most relevant features from the breast cancer diagnosis data, to improve the efficiency of the classification process. …”
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AI-Driven Predictive Maintenance for Workforce and Service Optimization in the Automotive Sector by Şenda Yıldırım, Ahmet Deniz Yücekaya, Mustafa Hekimoğlu, Meltem Ucal, Mehmet Nafiz Aydin, İrem Kalafat

“…However, conventional approaches frequently do not successfully forecast which clients are most likely to need or utilize maintenance services. …”
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Comparative analysis of software optimization methods in context of branch predication on GPUs by I. Yu. Sesin, R. G. Bolbakov

“…Covered approaches include: optimizing compilers, JIT-compilation, branch predictor, speculative execution, adaptive optimization, run-time algorithm specialization, profile-guided optimization. …”
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Radial Basis Function Coupling with Metaheuristic Algorithms for Estimating the Compressive Strength and Slump of High-Performance Concrete by Amir Reza Taghavi Khangah, Erfan Khajavi, Hasti Azizi, Amir Reza Alizade Novin

“…This work's significance consists of improving the concrete mix design by giving correct predictions of HPC performance, which will lead to optimized resource utilization, minimized costs, and reduced negative environmental impacts due to construction. …”
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Optimal integrated location and dispatching decisions for feeder bus route design problem by Bo Sun, Ming Wei, Chunfeng Yang

“…The methodology facilitates obtaining solutions using the design of an improved double population Bacterial Foraging Optimization (BFO) algorithm. …”
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An Efficient Path Planning Algorithm Based on Delaunay Triangular NavMesh for Off-Road Vehicle Navigation by Ting Tian, Huijing Wu, Haitao Wei, Fang Wu, Jiandong Shang

“…Considering that the improved road-off path planning A* algorithm could identify a chain of path triangles for calculating the shortest path, the funnel algorithm was then introduced to transform the path planning problem into a dynamic geometric problem, iteratively approximating the optimal path by maintaining an evolving funnel region, obtaining a shortest path closer to the Euclidean shortest path. …”
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