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AI-Based Detection and Analysis of Phishing Domains: Leveraging Machine Learning for Enhanced cybersecurity

AI-Based Detection and Analysis of Phishing Domains: Leverag...

引用

2024 international conference on System, Computation, automation and Networking, ICSCAN 2024

作者： Dhanalakshmi, R. Vijayaraghavan, N. Kumar, Akhil Beni Prathiba, B. Sahaya School of Computer Science and Engineering Vellore Institute of Technology - Chennai Center for Cyber Physical Systems Chennai India Kcg College of Technology Department of Mathematics Chennai India Scset Bennett University Greater Noida India School of Computer Science and Engineering Vellore Institute of Technology Center for Cyber Physical Systems Chennai India

ISBN: (纸本)9798331510022

In the ever-evolving landscape of cyber security, the prevalence of phishing attacks poses a formidable threat to information security systems worldwide, compromising data integrity and eroding user trust. This paper introduces an innovative solution harnessing artificial intelligence to identify and analyze phishing domains, particularly focusing on newly registered domains from public databases like WHOIS. This approach is crucial as traditional security measures often prove insufficient against the sophistication of phishing tactics. Our proposed AI-driven system employs an analysis strategy. It utilizes machine learning to conduct an in-depth backend code and content analysis. This involves comparing suspect and legitimate sites for structural and syntactical disparities, utilizing deep learning models trained on extensive datasets of known phishing and authentic domains. These methodologies offer a nuanced evaluation, crucial for distinguishing sophisticated phishing attempts from genuine domains. Additionally, the system excels at identifying malicious links within these domains, enhancing its overall protective capabilities. The efficiency of our solution lies in its capacity for real-time, accurate threat detection. We introduce a probabilistic scoring mechanism that assesses the likelihood of a domain being a phishing site, facilitating informed decision-making for cyber security personnel. Furthermore, our system is designed for seamless integration into existing cyber security frameworks, providing versatility and ease of use. © 2024 ieee.

关键词： Phishing

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Towards Sustainable cyber-Physical Manufacturing systems 22

Towards Sustainable Cyber-Physical Manufacturing Systems

引用

22nd IFAC conference on technology, Culture and international Stability (TECIS)

作者： Brennan, Robert W. Lyu, Guolin Univ Calgary Calgary AB T2N 1N4 Canada

We propose a self-managing services architecture for automated manufacturing systems to enable sustainable manufacturing operations. The architecture utilises both software agents and IEC 61499 function blocks to realise manufacturing systems that quickly respond to change while maintaining stable system operation and efficient use of available resources. To explore the system's ability to adapt to disturbances, a stochastic agent-based simulation of the automated manufacturing system with random equipment failures was developed. The results of the simulation demonstrate that the proposed self-managing services architecture is capable of rapidly reconfiguring part routings in order to reduce work in progress and maintain stable system operation. Copyright (C) 2024 The Authors.

关键词： Artificial Intelligence and Applications intelligent systems and Applications Sustainable Design and control

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Incentive Mechanism for Collaborative Sensing in intelligent Transportation systems with Mixed Traffic: A Stackelberg Game Approach 5

Incentive Mechanism for Collaborative Sensing in Intelligent...

引用

5th international conference on Computer Engineering and intelligent control, ICCEIC 2024

作者： Huang, Xumin Zhong, Weifeng Lu, Binbin Wu, Yuan Xie, Shengli Kuzin, Victor School of Automation Guangdong University of Technology Guangzhou China University of Macau State Key Lab of IoT for Smart City Macau China 111 Center for Intelligent Batch Manufacturing based on IoT Technology Guangzhou China The Russian Academy of Engineering Moscow Russia

ISBN: (纸本)9798331507992

intelligent Transportation systems (ITS) simultaneously collects driving data of both the intelligent Connected Ve-hicles (ICVs) and non-ICVs for traffic management in the mixed traffic environment. To this end, a set of ICVs can be scheduled to cooperatively sense a target non-ICV and collect the traffic data to a roadside unit (RSU). An incentive mechanism is necessitated to provide proper incentives for the selfish ICVs. In this paper, we resolve the incentive problem of collaborative sensing in the ITS with the mixed traffic, according to a Stackelberg game approach. We investigate the strategic interactions of the RSU and ICVs in which there exist leader-follower relationships among them. After that, we analyze the Stackelberg equilibrium, and derive the close-form solution of the Stackelberg game. Finally, we provide numerical results to demonstrate the effectiveness and efficiency of the proposed Stackelberg game. © 2024 ieee.

关键词： Information management

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Permanent Magnet Synchronous Motor control and Implementation of this control into the Microprocessor and its Realization

Permanent Magnet Synchronous Motor Control and Implementatio...

引用

2024 international conference on intelligent systems for cybersecurity, ISCS 2024

作者： Rathnakar, G. Negi, Harendra Singh Shashibhushan, G. Nandankar, Praful V. Vekariya, Daxa Maranan, Ramya Jss Science and Technology University Department of Mechanical Engineering Karnataka Mysuru570006 India Graphic Era Deemed to Be University Department of Computer Science and Engineering Uttarakhand Dehradun248002 India Sir M Visvesvaraya Institute of Technology Department of Electronics and Communication Engineering Karnataka Bengaluru562 157 India Government College of Nagpur Department of Electrical Engineering Maharashtra 441108 India Parul Institute of Engineering and Technology Parul University Department of Computer Science and Engineering Post Limda Gujarat 391760 India Saveetha School of Engineering Simats Department of Research and Innovation Tamil Nadu Chennai602105 India

ISBN: (纸本)9798350375237

Traditional methods of motor control, such as scalar control or field-oriented control (FOC), may struggle to provide the same level of precision and responsiveness as vector control. This work explores the implementation of vector control in the STM32F302R8 microprocessor for precise regulation of speed and torque in electric motors, commonly utilized in industrial automation and electric vehicles. Prior to vector control implementation, the microprocessor interfaces with essential components: the inverter for DC to AC power conversion, the control module housing control algorithms, and the resolver for rotor position feedback. The process involves programming and testing to accurately evaluate the rotor's rotation angle, crucial for effective vector control by ensuring correct voltage application to motor windings. Upon successful implementation and testing, the vector control system demonstrates functionality in regulating motor speed responsively to desired speed changes. © 2024 ieee.

关键词： Vectors

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OmniRace: 6D Hand Pose Estimation for Intuitive Guidance of Racing Drone

OmniRace: 6D Hand Pose Estimation for Intuitive Guidance of ...

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2024 international conference on intelligent Robots and systems

作者： Serpiva, Valerii Fedoseev, Aleksey Karaf, Sausar Abdulkarim, Ali Alridha Tsetserukou, Dzmitry Skolkovo Inst Sci & Technol Moscow Intelligent Space Robot Lab Bolshoy Blvd 30Bld 1 Moscow 121205 Russia

ISBN: (纸本)9798350377712;9798350377705

This paper presents the OmniRace approach to controlling a racing drone with 6-degree of freedom (DoF) hand pose estimation and gesture recognition. To our knowledge, this is the first technology enabling low-level control of high-speed drones through gestures. OmniRace employs a gesture interface based on computer vision and a deep neural network to estimate 6-DoF hand pose. The advanced machine learning algorithm robustly interprets human gestures, allowing users to control drone motion intuitively. Real-time control tests validate the system's effectiveness and its potential to revolutionize drone racing and other applications. Experimental results conducted in simulation environment revealed that OmniRace allows the users to complite the UAV race track significantly (by 25.1%) faster and to decrease the length of the test drone path (from 102.9 to 83.7 m). Users preferred the gesture interface for attractiveness (1.57 UEQ score), hedonic quality (1.56 UEQ score), and lower perceived temporal demand (32.0 score in NASA-TLX), while noting the high efficiency (0.75 UEQ score) and low physical demand (19.0 score in NASA-TLX) of the baseline remote controller. The deep neural network attains an average accuracy of 99.75% when applied to both normalized datasets and raw datasets. OmniRace can potentially change the way humans interact with and navigate racing drones in dynamic and complex environments. The source code is available at https://***/SerValera/***.

关键词： Drones

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Construction of intelligent Building automation control System Based on Fuzzy Clustering Algorithm

Construction of Intelligent Building Automation Control Syst...

引用

2023 international conference on Internet of Things, Robotics and Distributed Computing, ICIRDC 2023

作者： Liu, Jing He, Yu Harbin Huade University Heilongjiang Harbin150025 China

ISBN: (纸本)9798350375275

With the vigorous development of the construction industry, the market demand for automatic control systems is increasing, and it has attracted domestic and foreign automation system manufacturers to continuously improve the software for computer control management, emphasizing the humanized use of interfaces, and ensuring the orderly use of building machinery and fire protection, security, and parking management. In this regard, this article constructs an intelligent building automation control system based on fuzzy clustering algorithm, which can effectively improve the intelligence and prevention level of buildings. The intelligent building equipment automation control system utilizes modern scientific technologies such as communication technology, computer network technology, and intelligent monitoring technology. It uses hierarchical clustering to obtain the initial number of clusters from offline data, and then performs fuzzy clustering on incremental data. However, there is a problem of needing to set parameters to identify outlier samples. Comparative experiments have been conducted to verify the time for receiving control instructions between the traditional system and the system in this paper. The average receiving time of the traditional system is 18.95 seconds, while the average receiving time of the system in this paper is 12.75 seconds, which shortens the receiving time of control instructions by 6.2 seconds compared to the traditional system. The above experimental results once again validate the effectiveness of the system in this paper. © 2023 ieee.

关键词： intelligent buildings

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A Novel Multi-Stream Informer Used for Lower Extremity Joint Angle Estimation 12

A Novel Multi-Stream Informer Used for Lower Extremity Joint...

引用

12th international conference on cyber technology in automation, control, and intelligent systems, cyber 2022

作者： Zhou, Xin Zhang, Liming Liu, Jiaqing Ye, Jiancong Wang, Can Wu, Xinyu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology China University of Science and Technology of China China University of Chinese Academy of Sciences China South China University of Technology China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

In lower extremity exoskeleton rehabilitation systems, synergy and proportionality between the human lower extremity and the exoskeleton robot have been a critical goal to pursue. In recent years, changeable deep learning models based on multi-source signals have been used for lower limb continuous motion estimation. During the process, multimode signals are fed into the time processing model as time series. However, there are some deficiencies in this framework, on the one hand, what kind of multi-source combination can be more efficient;on the other hand, most of the existing models need several iterations or network stacking to complete the extraction of temporal information. This study set out to address the above problems, we put forward Multi-Stream Informer (MS-Informer), using Multi-Stream combination and sparse attention mechanisms for lower limb continuous motion estimation. In the experiment, we compare MS-Informer and Temporal Convolutional Network (TCN) and Long Short-term Memory (LSTM) under distinctive multi-source combinations. In summary, MS-informer performs well in multiple evaluations compared with other models. Experimental results illustrate that the MS-Informer is more efficacious in lower limb joint angle estimation and is a promising method for achieving coordinated control of lower limb exoskeletons. © 2022 ieee.

关键词： Motion estimation

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Push-Assisted Functional Grasping Method Based on Prioritized Experience Replay in Clutter

Push-Assisted Functional Grasping Method Based on Prioritize...

引用

ieee international conference on cyber technology in automation, control, and intelligent systems

作者： Fei Wang Manyi Shi Chao Chen Jinbiao Zhu Xinyao Wang Department of Robot Science and Engineering Northeastern University University Shenyang Liaoning Province China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

In life service task scenarios, functional grasping is the basis for robots to perform other complex tasks. Through the exploration of the agent and the environment, we map the insights of local features to the global situation from the visual level, thereby achieving functional capture based on small sample priors. Let the agent's grasping strategy stably converge to the preset grasping posture. In addition, we use the grasp network to evaluate the effect of promoting the network, and use priority experience playback to focus on learning for experiences that have a significant auxiliary role. It can significantly improve the functional capture success rate and system action efficiency in clutter scenes.

关键词： Visualization automation Grasping Reinforcement learning control systems Clutter intelligent systems Robots

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The Analysis of AI Based Algorithms in Personalized and Adaptive E-learning Experiences 2

The Analysis of AI Based Algorithms in Personalized and Adap...

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2nd ieee international conference on IoT, Communication and automation technology, ICICAT 2024

作者： Kumar, Ajay Srivastava, Shashank Buddha Institute of Technology Department of Computer Science & Engineering UP Gorakhpur273209 India

ISBN: (纸本)9798350368109

The integration of Artificial Intelligence (AI) into e-learning systems has heralded a new era of personalized and adaptive learning experiences. This comprehensive review delves into the latest advancements and implications of AI in e-learning. By harnessing machine learning algorithms, natural language processing techniques, and predictive analytics, AI-powered e- learning systems provide personalized content delivery, adaptive assessments, and intelligent tutoring capabilities. Additionally, this review examines how AI enhances learner engagement, improves learning outcomes, and tackles the challenges of scalability and accessibility in education. It also addresses ethical considerations, challenges, and future directions for AI-based e-learning, underscoring the transformative potential of AI in shaping the future of education. © 2024 ieee.

关键词： Adversarial machine learning

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Macro-Mini Manipulator Based on Multi-Force Sensors for Force control Application

Macro-Mini Manipulator Based on Multi-Force Sensors for Forc...

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ieee international conference on cyber technology in automation, control, and intelligent systems

作者： Junjie Dai Chin-Yin Chen Han Chen Guilin Yang Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo Institute of Materials Technology and Engineering Ningbo China University of Chinese Academy of Sciences Beijing China College of Mechanical Engineering Zhejiang University of Technology Hangzhou China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

In polishing, force-controlled performance is affected by manipulator dynamics, end-effector dynamics, and workpiece uncertainty. This paper proposes a new force-controlled method by utilizing multi-force sensors for robotic polishing applications. One of the force sensors is installed between the endpoint of the manipulator and the fixed platform of the end-effector to realize the dynamic decoupling. The other one is added at the back of the workpiece to realize force tracking. The experimental results indicate that the proposed method's contact force response speed and overshoot are both better than those of the conventional force-controlled method.

关键词： Uncertainty Force Dynamics Process control Robot sensing systems End effectors Force sensors Force control intelligent systems Manipulator dynamics

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