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AP-EH: An Encryption Hopping Method Based on Action Program Enabled SDN

IEEE ACCESS 2024年 12卷 148868-148879页

作者： Zhao, Zheng Fan, Xiaoya Mao, Qian Xue, Haixiao Zhao, Qi Dalian Maritime Univ Coll Artificial Intelligence Dalian 116026 Peoples R China Dalian Univ Technol Sch Software Technol Dalian 116024 Peoples R China Liaoning Univ Coll Light Ind Shenyang 110036 Peoples R China Northeastern Univ Coll Med & Biol Informat Engn Shenyang 110819 Peoples R China

Sniffing attack is one of the typical passive network attack methods, which poses a serious threat to network communication security. Detecting and defending against sniffing attacks is challenging due to their stealthy nature. In this paper, we propose an encryption hopping method based on a programmable data plane named AP-EH to defend against sniffing attacks. By leveraging the concept of Moving Target Defense (MTD), AP-EH greatly elevates the complexity and cost for attackers to crack the communication data by dynamically modifying the encryption algorithm and key. Experimental results and analysis demonstrate the security and performance of the proposed method.

关键词： Encryption Security Heuristic algorithms IP networks Protocols Routing Costs software algorithms Quality of service Complexity theory Telecommunication traffic Encrypted traffic moving target defense programmable data plane sniffing attack

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Intelligent Optimization for a Full-Sized PDC Bit with Composite Percussive Rock Breaking Drilling

Journal of Intelligent Construction

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Journal of Intelligent Construction 2025年第4期1卷 1-11页

作者： Liping Li Xuegang Liu Yu Zhou Chengshuai Qin Zhihui Liu Lige Wang Chongqiang Zhu Zizheng Sun School of Qilu Transportation Shandong University Jinan China Institute of Mechanics Chinese Academy of Sciences Beijing China School of Science and Engineering University of Dundee Dundee UK

Intelligent drilling has obtained a lot of attention in mining engineering, oil and gas production, and tunnelling engineering. The optimization of drilling parameters is one of the most important technologies of intelligent drilling while determining the key values to improve the drilling efficiency is still a difficulty. In this paper, we established a composite percussive rock breaking model of a full-size polycrystalline diamond compact (PDC) bit based on the continuous-discontinuous element method (CDEM). The evolution of rock fragmentation under the action of composite impact is analysed by the rock breaking volume and the torque applied on the drill bit during drilling. Based on actual construction, two key parameters, axial impact velocity and impact frequency, affecting the process of composite impact rock breaking were selected, to further investigate their effect on composite impact rock breaking. The fitting curves obtained from the sensitivity analysis of the rock breaking effect under different construction parameters were proposed to guide the intelligent drilling. Furthermore, the construction parameters of a diversion inclined shaft in the #2 construction branch hole of Tiantai Mountain pumped storage power station in Zhejiang Province were collected, which provides validation data for the proposed optimizing theory of the drilling parameters.

关键词： Drilling Shafts Solid modeling Torque software algorithms Tunneling Rocks Data models software Optimization

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Multimodal Recommendation of Messenger Channels

Multimodal Recommendation of Messenger Channels

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19th International Conference on Mining software Repositories (MSR)

作者： Koshchenko, Ekaterina Klimov, Egor Kovalenko, Vladimir JetBrains Res Amsterdam Netherlands JetBrains Res St Petersburg Russia

ISBN: (纸本)9781450393034

Collaboration platforms, such as GitHub and Slack, are a vital instrument in the day-to-day routine of software engineering teams. The data stored in these platforms has a significant value for data-driven methods that assist with decision-making and help improve software quality. However, the distribution of this data across different platforms leads to the fact that combining it is a very time-consuming process. Most existing algorithms for socio-technical assistance, such as recommendation systems, are based only on data directly related to the purpose of the algorithms, often originating from a single system. In this work, we explore the capabilities of a multimodal recommendation system in the context of software engineering. Using records of interaction between employees in a software company in messenger channels and repositories, as well as the organizational structure, we build several channel recommendation models for a software engineering collaboration platform, and compare them on historical data. In addition, we implement a channel recommendation bot and assess the quality of recommendations from the best models with a user study. We find that the multimodal recommender yields better recommendations than unimodal baselines, allows to mitigate the overfitting problem, and helps to deal with cold start. Our findings suggest that the multimodal approach is promising for other recommendation problems in software engineering.

关键词： Instruments software algorithms Decision making Collaboration software quality Data models Data mining

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Autonomous Navigation and Control System for Capturing a Moving Drone

Field Robotics

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Field Robotics 2025年 2卷 34-54页

作者： Hong Tao Tao Song Defu Lin Ren Jin Bin Li Beijing Key Laboratory of UAV Autonomous Control Beijing Institute of Technology Beijing China

This paper describes an autonomous navigation and control system for capturing the maneuvering drones. A vision-based navigation method seeks and detects the intruding drone, then, the target trajectory is predicted by fusing onboard vision and inertial-measurement resources. The target's relative position, velocity and acceleration are also obtained at the same time. Then, we present a modified proportional-derivative (PD) algorithm based on the estimated target states. In addition, the boundary constraints of the protected area are considered to avoid a collision. The proposed capture navigation and control system has demonstrated its efficiency both in simulation, flight experiments, and MBZIRC 2020, where our team won the Challenge I competition.

关键词： Drones Trajectory Prediction algorithms Control systems Hardware software algorithms Vectors software Autonomous robots Accuracy

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UWRange: An Open ROS Framework for Simulating Acoustic Ranging and Localization for Underwater Robots under Realistic Conditions

UWRange: An Open ROS Framework for Simulating Acoustic Rangi...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Steinmetz, Fabian Duecker, Daniel A. Sichert, Nils Busse, Christian Kreuzer, Edwin Renner, Bernd-Christian Hamburg Univ Technol Hamburg Germany

ISBN: (数字)9781665479271

ISBN: (纸本)9781665479271

Considering realistic characteristics of acoustic localization methods is crucial for roboticists when developing guidance and control algorithms for small and agile underwater robots. Current simulators either rely purely on geometric distancing, i. e. do not consider dynamic effects such as robot motion during acoustic signal propagation, or they are too complex for usage by non-communication experts and, thus, vulnerable to misconfiguration. We propose an open ROS-based framework that extends existing robot simulators (e. g. Gazebo) by simulating the effects of realistic acoustic ranging for underwater robot localization. Thus, our simulator enables realistic real-time analysis and evaluation of guidance, navigation, and control algorithms in software in-the-loop systems. For this purpose, we incorporate and encapsulate the non-trivial characteristics of acoustic communication and ranging such as robot motion during signal propagation, packet reception failure, and modem timings. This ensures the applicability of the tool by roboticists who are typically non-experts in acoustic communication and guarantees accurate and realistic simulation results. We demonstrate the functionality and performance of our framework and validate it on real-world experimental data on the example of a two-way ranging method. Our open-source release includes well-defined interfaces and parameters as well as a tutorial. This targets other roboticists who can either use our framework directly or easily adapt it to their individual setup, e. g., by adding further acoustic-ranging protocols.

关键词： Location awareness Robot motion Autonomous underwater vehicles Adaptation models Acoustic communication (telecommunication) software algorithms Tutorials

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Extended Abstract of E-SC4R: Explaining software Clustering for Remodularisation

Extended Abstract of E-SC4R: Explaining Software Clustering ...

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IEEE International Conference on software Analysis, Evolution and Reengineering (SANER)

作者： Alvin Jian Jia Tan Chun Yong Chong Aldeida Aleti Software Engineering Monash University Malaysia Software Engineering Monash University Australia

Maintenance of existing software requires a large amount of time for comprehending the source code. The architecture of a software, however, may not be clear to maintainers if up-to-date documentations are not available. software clustering is often used as a remodularisation and architecture recovery technique to help recover a semantic representation of the software design. However, due to the diverse domain and structure of software systems, the suitability of different clustering techniques for different software systems are not investigated thoroughly. Research that introduce new clustering techniques usually validate their approaches on a specific domain, which might limit its generalisability. If the chosen test subjects only represent a narrow perspective of the whole picture, researchers risk not being able to address the external validity of their findings. This work aims to fill this gap by introducing a new approach, Explaining software Clustering for Remodularisation (E-SC4R), to evaluate the effectiveness of different software clustering approaches. This work focuses on hierarchical clustering and Bunch clustering algorithms and provides information about their suitability according to the features of the software, which, as a consequence, enables the selection of the optimum technique for a particular software system. The E-SC4R framework is able to characterise both the strengths and weaknesses of the analysed software clustering algorithms using software features extracted from the code. The proposed approach also provides a better understanding of the algorithms’ behaviour by showing a 2D representation of the effectiveness of clustering techniques on the feature space through the application of dimensionality reduction techniques.

关键词： Visualization software design Source coding software algorithms Semantics Clustering algorithms Computer architecture

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Nonlinear Model Predictive Control for Thermal Management of Bio-Implants

Nonlinear Model Predictive Control for Thermal Management of...

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American Control Conference (ACC)

作者： Ermis, Ayca Lai, Yen-Pang Zhang, Ying Georgia Tech Sch Elect & Comp Engn Atlanta GA 30332 USA

ISBN: (数字)9781665451963

ISBN: (纸本)9781665451963

Thermal management of bio-implant and implantable medical devices (IMDs) has gained growing attention to prevent overheating in the surrounding tissue of IMDs in certain applications, such as neural prostheses like deep brain stimulators (DBS). This paper focuses on implementation of nonlinear model predictive control (NMPC) methods for adaptive thermal management of IMDs with multiple heat sources. Thermal dynamics of the IMD is modelled using an identification algorithm introduced in previous papers. Interior point optimization method is implemented with the NMPC to solve for the nonlinear optimization problem for adaptive thermal management of IMDs with multiple heat sources. The NMPC implementation is validated using the COMSOL software simulations.

关键词： Heating systems Temperature measurement Adaptation models Medical devices software algorithms Predictive models Thermal management

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software Effort Estimation using ANN (Back Propagation)

Software Effort Estimation using ANN (Back Propagation)

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International Conference on Computing Methodologies and Communication (ICCMC)

作者： Ravi Kumar B N Yeresime Suresh Dept. of Computer Science and Engineering BMS Institute of Technology and Management Bangalore India Dept. of Computer Science and Engineering Ballari Institute of Technology and Management Ballari India

Project managers often use Effort Estimating strategies to manage the human resources of current or upcoming software projects. Prior to project implementation, cost, time, and personnel estimation are basically necessary. For every project of software, getting an accuracy in Effort Estimation has always been difficult. In case of this study, estimating the labor involved in developing software determined using a Back Propagation Model. This model's goal is to investigate the capabilities and potential uses of utilizing Artificial Neural Networks (ANN) as a tool for forecasting the effort required for software development. In order to estimate the software work, we are attempting to implement a machine learning technique in this research. Out of all machine learning methods, we are applying an algorithm based on Artificial Neural Networks that is Back propagation. The Desharnais dataset, a well-known publicly available dataset for estimation of software effort, is used to test the approach. The performance and accuracy of the tested model have been evaluated using three metrics: MMRE, MRE, and Pred (0.25). In the sections below that follows, I explain the algorithm and its results.

关键词： Backpropagation Computational modeling software algorithms Estimation Artificial neural networks Machine learning Predictive models

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Implementation and Comparison of Artificial Intelligence Techniques in software Testing

Implementation and Comparison of Artificial Intelligence Tec...

引用

International Conference on Information Systems and Computer Networks (ISCON)

作者： Isha Verma Deepak Kumar Rajni Goel AIIT Amity University Noida Uttar Pradesh India Howard University Washington DC USA

AI is a prominent innovation of the current digital world. It powers most of the cutting-edge digital devices. It is a blend of unique technologies from machine learning (ML) to mixed reality (MR), and more. AI has significantly touched many sectors including healthcare, life sciences, manufacturing, retail, and agriculture. AI, as many expect, is going to be the future of the computing world. Artificial Intelligence has been a boon to the software industry as well. The software testing area has been highly touched by AI. Any applications that are built, need to be tested before providing it to the client. It becomes tedious if it’s a complex timebound application. Manual testing in those scenarios doesn’t seem to be a feasible solution. Although test automation has been incorporated in many companies, they aren’t efficient in all cases. AI, on the other hand, helps test the applications effectively. Machine learning and deep learning technologies of AI are playing a crucial role in training and inferring massive amounts of data resulting in faster testing of the application. In this paper, we discuss the implementation and comparison of machine learning and deep learning techniques in software Testing.

关键词： software testing Deep learning Training Technological innovation Machine learning algorithms Automation software algorithms

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Dynamic Program Slicing of Agent-oriented software

Dynamic Program Slicing of Agent-oriented Software

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Innovation in Technology (INOCON), IEEE International Conference for

作者： Alina Mishra M R Kabat D.P. Mohapatra Department of Computer Science and Engineering Veer Surendra Sai University of Technology Department of Computer Science and Engineering National Institute of Technology

Slicing programs is an essential aspect of program development and maintenance. Because numerous statements might be discarded in the procedure of locating a bug, dynamic program slicing approaches are commonly utilized for debugging. Only the statements that have a consequence on the variable are included in a dynamic program slice with regard to that variable. Agent-oriented programming is a novel paradigm which uses agents as their basic entity. Agents are defined as an object which achieves an explicit action in an atmosphere known to it and responds to the variations. In this paper, a different approach for computation of relevant slices in agent-oriented programs is presented. We have taken a single-agent program as our working example. First, we have developed an intermediate representation for the agent-oriented program. Then, we have developed an algorithm based on dependencies among the nodes in the graph to compute slices.

关键词： Technological innovation Heuristic algorithms Computational modeling software algorithms Programming Maintenance engineering software systems

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