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Emerging Smart Computing and Informatics (ESCI), Conference on

作者： Mareeswari V Vijayan R Ashish Shukla Department of Software and Systems Engineering School of Computer Science Engineering and Information Systems (SCORE) Vellore Institute of Technology (VIT) Vellore India Department of Information Technology School of Computer Science Engineering and Information Systems (SCORE) Vellore Institute of Technology (VIT) Vellore India Master of Computer Applications School of Computer Science Engineering and Information Systems (SCORE) Vellore Institute of Technology (VIT) Vellore India

ISBN: (数字)9798331515683

ISBN: (纸本)9798331515690

Bluetooth technology, which facilitates wireless communication between Billions of devices including smartphones, tablets, laptops, and Internet of Thing (IoT) devices, is a cornerstone of modern connectivity. Its importance lies in its ability to enable seamless data exchange and interaction across a wide range of applications, from personal gadgets to complex industrial systems. Despite its widespread adoption, Bluetooth is not immune to critical security vulnerabilities. Issues like Bluetooth Low Energy (BLE) vulnerabilities and denial-of-service (DoS) attacks can overwhelm devices with excessive traffic, while BLE Forced Connection can lead to unauthorized access, and eavesdropping exposes sensitive data being exchanged. We have discussed these vulnerabilities in detail, examining their mechanisms, potential impacts, and various implementation aspects. Additionally, we have added demonstrations to illustrate how these attacks can be executed and the potential consequences. To prevent these threats, we explored essential measures, including regular firmware updates, secure pairing protocols, and careful management of Bluetooth settings. Adopting best practices like disabling Bluetooth when not in use and monitoring connected devices can further enhance security, ensuring the reliable and safe operation of the vast and growing ecosystem of Bluetooth-enabled devices.

关键词： Wireless communication Ethics Protocols Ecosystems Denial-of-service attack Security Internet of Things Bluetooth Low Energy Microprogramming Guidelines

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Cybersecurity Threat Detection using Machine Learning on Network Traffic

Cybersecurity Threat Detection using Machine Learning on Net...

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International Conference on ent Computing and Control Systems (ICICCS)

作者： R. Rithi N. Nithya A. Akila R. Saravanakumar M. Vargheese S. Jeya Lakshmi Master of Computer Applications Karpagam Academy of Higher Education Coimbatore Tamil Nadu India Department of Computer Applications Karpagam Academy of Higher Education Coimbatore Tamil Nadu India Department of Artificial Intelligence and Data Science R.M.K College of Engineering and Technology Tamil Nadu India Iconix Software Solution Tirunelveli Tamil Nadu India Department of Computer Science and Engineering PSN College of Engineering and Technology Tirunelveli Tamil Nadu India

ISBN: (数字)9798331512088

ISBN: (纸本)9798331512095

Web phishing is a prevalent online attack in which victims are tricked into revealing their personal information by visiting fraudulent websites. Phishers often use URL shortening tools to disguise malicious links, making it easier to steal sensitive data such as usernames, passwords, and banking details. These phishing websites are designed to mimic legitimate ones, making detection more challenging. As phishing techniques continue to evolve rapidly alongside technological advancements, the need for effective anti-phishing systems has become increasingly crucial. Machine learning has emerged as a powerful tool for recognizing and mitigating phishing scams. This article provides a comprehensive overview of machine learning techniques for phishing detection and their effectiveness in combating online threats.

关键词： Uniform resource locators Accuracy Reviews Phishing Scalability Machine learning Telecommunication traffic Passwords Threat assessment Real-time systems

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Integrated system design for vertical takeoff-landing of small unmanned aerial vehicles

Integrated system design for vertical takeoff-landing of sma...

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2018 Systems and Information engineering Design Symposium, SIEDS 2018

作者： Rau, James V. Babiceanu, Radu F. Master of Science in Systems Engineering Embry-Riddle Aeronautical University United States Systems Engineering Department of Electrical Computer Software and Systems Engineering Embry-Riddle Aeronautical University United States

ISBN: (纸本)9781538663431

Due to the advancements in autonomous units, more small unmanned aerial vehicles (sUAV's) are being utilized to accomplish commercial missions. Fixed wing, vertical takeoff-landing (FW-VTOL) sUAV's have been developed to provide similar flight performance characteristics in comparison to fixed wing or multi-copter sUAV's. The hybrid fixed-wing aircrafts offer significant usability and safety advantages over its rival systems. These aircrafts can be deployed in a slow and controlled manner off a vessel or in a small remote location. This is an alternative method that can be used instead of launching the aircraft using conventional high-speed long runways, nets or catapults. Unlike private aircrafts these small vehicles are not as strictly regulated, whether it is the certification of design or the pilot's flight hours and endorsements. A formalized safety system for FW-VTOL sUAV's must be integrated with all autonomous units in order to adhere to similar aircraft safety requirements. The proposed Integrated Flight Safety Plan (IFSP) has been modeled in a finite-state machine to consider all possible events of the unit during flight. These system conditions and criteria allow for the unit to react to internal failures and external changes, autonomously, and acutely control the outcome with bystander safety as a primary consideration. The formal verification and checking of the IFSP model can be tested using an abstract simulation. A predetermined mission replicate is repeatedly tested, based on approximate probabilistic events, to assess the effectiveness of the model adapting during flights that contain one or more system failures. © 2018 IEEE.

关键词： Fixed wings

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Gaussian Differential Privacy Integrated Machine Learning Model for Industrial Internet of Things

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SN computer science 2023年第5期4卷 454页

作者： Lazar, Arokia Jesu Prabhu Soundararaj, Sivaprakash Sonthi, Vijaya Krishna Palanisamy, Vishnu Raja Subramaniyan, Vanithamani Sengan, Sudhakar Department of Computer Science and Engineering AI & ML CMR Institute of Technology Telangana Hyderabad 501401 India Department of Software Systems School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore 632014 India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram 522502 India Department of Computer Science and Engineering Kongu Engineering College Tamil Nadu Perundurai 638060 India Master of Computer Applications M. Kumarasamy College of Engineering Tamil Nadu Karur 638060 India Department of Computer Science and Engineering PSN College of Engineering and Technology Tamil Nadu Tirunelveli 627152 India

Agriculture, energy, mining, healthcare, and transportation are a few of the top industries transformed by the industrial internet of things (IIoT). Industry 4.0 mainly relies on machine learning (ML) to use the vast interconnectedness and large amounts of IIoT data that IIoT primarily drives. ML approaches are trained on confidential data generated by the IIoT environment often exposes privacy to adversarial assaults. Blockchain-based ML is established in the proposed secured IIoT research work to safeguard and enhance privacy. This research proposes a Gaussian differential privacy-integrated machine learning model (GDPIMLM), created for a scalable and controlled IIoT system, fully connected (FC) layer, implemented blockchain benefits to create a privacy-preserving mechanism while considering other limitations and reasonable time. A probability test using two altered Gaussian distributions (GD) forms the basis for defining Gaussian differential privacy (GDP). Due to a central restriction theorem for differential privacy, GDP is the primary privacy term within the family of Federal differential privacy (f-DP) policies. Ethereum is used to implement experimental evaluations. Data collections show that the recommended method enhances digital data privacy with industry-leading security without reducing performance. The performance analysis of the proposed model of secured industrial internet of things (IIoT) is studied using the accuracy of comparison with existing methods and for diverse distributed entities (DE). The proposed secured IIoT attains a minimal time consumption (TC) of 790 Sec—the highest accuracy of 92%, outperforming the existing method. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Blockchain Industry Industry 4.0 Learning Privacy Security Smart objects

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Medicine and Disease Association Prediction via Attention-Based Medical Heterogeneous Information Network Representation Learning

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2022年第1期49卷 69-78页

作者： Zhang, Bin Yang, Dan Lin, Zhihuang Master of Computer Science and Software Engineering Department University of Science and Technology Liao Ning Anshan China School of Computer Science and Software Engineering University of Science and Technology Liao Ning Anshan China

Knowledge of medication and disease has been rapidly accumulated. Also, an increasing number of researchers have paid more attention to predicting medicine-disease associations by machine learning methods. The associations of entities in the medical heterogeneous information network involve different association types. In this paper, we propose MHIN-MD, a representation learning of medical heterogeneous network model to solve the association between medicines and diseases in medical heterogeneous information network. Specifically, we first construct a medical heterogeneous information network contains diseases, medicines, diagnosis, etc. Next, we design a neural network model to learn the feature vector representation of medical nodes information. We try to find the association between medicines and diseases through the characteristics of medicines structure and the interaction between medicines. Using the Euclidean distance to calculate medicine similarity and disease similarity, generates a set of similar nodes between medicines and diseases to prediction association between medicines and diseases. Finally, our extensive experiments on MIMIC- III datasets and DrugBank datasets, the result demonstrates that MHIN-MD can outperform baselines in the association prediction. © 2022. All Rights Reserved.

关键词： Diagnosis

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CE-HigherHRNet: Enhancing Channel Information for Small Persons Bottom-Up Human Pose Estimation

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2022年第1期49卷 260-269页

作者： Li, M.Y. Zhao, J. Master’s Student of School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan114051 China School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan114051 China

Accurately detecting the keypoints of small persons in an image using bottom-up multi-person pose estimation algorithms is exceptionally difficult owing to scale variation challenges. HigherHRNet initially solved the challenge of multi-player scale change pose estimation. However, because it uses repeated cross-scale fusion, owing to inherent defects in channel reduction, semantic information is lost. Furthermore, the aliasing effects produced by the miscellaneous feature maps formed after cross-scale fusion have a significant impact on the detection accuracy of small persons. In this paper, we propose a novel bottom-up human pose estimation algorithm based on HigherHRNet, called Channel-Enhanced HigherHRNet (CE-HigherHRNet). CE-HigherHRNet comprises three main components: a multiscale sub_pixel skip fusion module, a lightweight attention mechanism (with channel attention enhanced and spatial attention modules), and a high-resolution feature pyramid with an added Dupsampling module. The lightweight attention mechanism optimizes the feature map after each fusion. Deconvolution is replaced with Dupsampling, which strengthens the network’s scale awareness and makes it more sensitive to robust scale changes. The average precision (AP) of CE-HigherHRNet on the COCO test-dev dataset was 71.9% (an improvement of 1.4% compared with HigherHRNet). Furthermore, the average detection accuracy of small persons was 68.1% AP (an improvement of 1.5% AP). These results verify that the proposed CE-HigherHRNet is more robust in processing scale changes and has a stronger ability to handle crowded environments. Thus, it is more accurate in positioning small persons in images and human bodies in crowded environments. © 2022. All Rights Reserved.

关键词： Semantics

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A Hybrid Harmony Search Algorithm based on Firefly Algorithm and Boltzmann Machine

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2022年第1期49卷 241-251页

作者： Yang, J. Zhang, Xiaoxia Fu, S. Hu, Y.Y. Master Student of School of Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan114051 China Professor of School of computer Science and Software Engineering University of Science and Technology LiaoNing Anshan11041 China

Harmony Search Algorithm (HS) is a new meta-heuristic algorithm based on music creation process. The algorithm has been widely used in many fields because of its simple and flexible structure and fewer controlled parameters. However, HS is easy to be affected by the initial harmony memory and falls into local optimization. In addition, there are also problems, such as low searching accuracy and slow convergence speed of the optimal solution. Therefore, this paper proposes a hybrid harmony search algorithm based on firefly algorithm and boltzmann machine (HSFA-BM). First, in order to avoid the possibility of harmony search algorithm falling into local optimum, boltzmann machine (BM) mechanism is used to update the harmony memory in this paper. Second, in order to enhance the ability of the algorithm to exploit optimal solutions, this paper uses the movement mode of fireflies to generate new solutions. The improved algorithm enhances the ability of global optimization and search precision, and speeds up the convergence speed. In this paper, six classical test functions are used to test the effectiveness of the algorithm, and a very obvious optimization result is obtained. © 2022. All Rights Reserved.

关键词： Flexible structures

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Milling Force Prediction of Titanium Alloy Based on Support Vector Machine and Ant Colony Optimization

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2021年第2期48卷 1-12页

作者： Zhang, Xiaoxia Yu, Ziqiao Hu, Yinyin Yang, Jiao A Professor of School of Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan11041 China A Master Student of School of Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan114051 China

Milling force prediction of titanium alloy plays an important role in titanium alloy milling process. In the article, the milling process of titanium alloy materials is analyzed, and this material quality is affected directly by the milling force. Support vector machine (SVM) has shown prominent performance for many real-world problems. However, SVM computational complexity increases, as the number of samples increases. How to effectively apply it to massive datasets is still a serious challenge. Although there are some literatures on parameter optimization techniques of SVM regression, the performance of this model still needs to be further studied and improved. We present a new milling force predicting model, namely ACO&SVM, which integrate SVM regression with ACO algorithm to enhance the prediction accuracy of milling force for mill process of titanium alloy. The primary innovation feature of hybrid model is to apply the ACO to automatically determine parameters of SVM regression model. In addition, as being applied to discrete optimization, to solve continuous optimization problems, ACO algorithm needs to transform continuous variables into discrete ones by discretizing of continuous variables. The results have shown that proposed ACO&SVM model yields better prediction accuracy, and thus it can be widely applied to the fields of material processing optimization. © 2021. All Rights Reserved.

关键词： Titanium alloys

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A New Hybrid Cuckoo Search for the Resources-Constrained Project Scheduling Problem

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2021年第2期48卷 1-12页

作者： Shen, Xin Zhang, Xiaoxia Yu, Ziqiao X. Shen is a Master Student of School of Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan114051 China X. X. Zhang is a Professor of School of Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan11041 China A Master Student of School of Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan114051 China

Resource-constrained project scheduling problem (RCPSP) is a kind of representative practical engineering problem, the purpose is to schedule activities in the project through rational use of limited resources in the minimum time. This paper proposes an improved hybrid cuckoo algorithm (CS&SA) to solve the RCPSP problem. Firstly, the individual elements are randomly coded into priority vectors, and the population is decoded using serial scheduling to convert the individual into a set of task scheduling sequences. Secondly, the Levy flight is redesigned to change the algorithm from random walk to adaptive as the population fitness changes. Then, this article adds three neighborhood update techniques to meet the update requirements of the algorithm at different stages. Finally, in order to prevent the algorithm from falling into a local optimum, this paper introduces a simulated annealing strategy to allow the algorithm to accept some individuals with poor quality with a certain probability in each iteration. In the testing part, this paper firstly tests the effectiveness and optimization of three different-scale examples in the classic example library PSPLIB for RCPSP problems. Among them, the average error of the CS&SA algorithm in the small-scale J30 is 0.25%, and the average error in the medium-scale J60 is 11.21%, and the average error of the large-scale J120 is 19.83%. Then, by comparing other intelligent optimization algorithms, it is proved that NCS&SA is superior to other algorithms in optimization and accuracy. © 2021. All Rights Reserved.

关键词： Combinatorial optimization

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A light-weight tool for teaching the development and evaluation of requirements documents

A light-weight tool for teaching the development and evaluat...

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113th Annual ASEE Conference and Exposition, 2006

作者： Garbers, Ben Periyasamy, Kasi University of Wisconsin La Crosse United States Master of Software Engineering Program University of Wisconsin La Crosse United States IBM Computer Science Department Program University of Wisconsin La Crosse United States

Writing correct and consistent software requirements specification (SRS) is one of the most important goals of a requirements engineering process. The SRS serves as the basis for subsequent design, testing and maintenance of the software product. The more errors and inconsistencies contained in an SRS, the more time and efforts are required to correct them at a later stage in the development process. Most SRS documents are manually typed using a word processor and hence the writer is responsible for ensuring the correctness and consistency of the document. Without adequate tool support, the manual construction and analysis of SRS documents is a tedious process and is error-prone. This paper describes an interactive tool developed at the University of Wisconsin-La Crosse that assists students preparing an SRS document based on the IEEE standard 83019981. The tool provides an easy-to-use interface and the ability to create, edit, load and save SRS documents. In addition, it evaluates the requirements document based on criteria published by the software Metrics program at the software Assurance Technology Center, NASA2. A function-point metrics analyzer is also built into the tool so that the efforts required to complete the project specified in the document can be evaluated. © American Society for engineering Education, 2006.

关键词： computer aided software engineering

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