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Deep Learning-Driven Cloud Intrusion Detection: Internet of Things and Cloud Networks 1

Deep Learning-Driven Cloud Intrusion Detection: Internet of ...

1st International Conference on Advances in computer science, electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Moon, Iffath Tanjim Islam Mondal, Md. Nazrul Rajshahi University of Engineering & Technology Dept. of Computer Science & Engineering Rajshahi6204 Bangladesh

ISBN: (纸本)9798331518578

In this paper, we have utilized deep learning approaches to detect cloud intrusion for the Internet of Things (IoT). The emerging growth of IoT and cloud environments has revolutionized many industries by allowing real-time data sharing and storage. Cloud platforms offer the essential infrastructure for managing the massive volumes of data produced by IoT devices. However, due to several flaws, including insufficient encryption, insecure APIs, and weak authentication, intruders can exploit the vulnerabilities to interrupt services and obtain unauthorized access. Therefore, deep learning can be an effective solution to detect cloud intrusion in IoT. In this research, we have developed individual convolutional neural network (CNN) and long short-term memory (LSTM) models, along with a hybrid CNN-LSTM model for multiclass classification and binary classification to detect cloud intrusion. In addition, we have examined which models perform the best for cloud intrusion detection for IoT among the individual and hybrid models. The proposed models are effective in detecting cloud intrusion, as CNN can extract spatial features, and LSTM can capture temporal dependencies from network traffic data. Furthermore, we have utilized one of the most recent and comprehensive datasets for IoT, the ToN-IoT dataset, containing real-world data. In multiclass classification, the hybrid CNN-LSTM has given the best performance, achieving an accuracy of 97.65%, precision of 97.72%, recall of 97.65%, f1 score of 97.67%, and AUC of 99.93%. In binary classification, all CNN, LSTM, and hybrid CNN-LSTM have demonstrated high performance, where LSTM has achieved the highest accuracy of 99.97%. Moreover, we have evaluated the performance of multiclass classification for detecting nine distinct kinds of attacks. In this instance, CNN has shown better performance in detecting backdoor attacks. Thus, this research can make the IoT platform more secure by efficiently detecting cloud intrusion. © 2025

关键词： Network intrusion

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A 4x4 MIMO Antenna Array for the Wi-Fi7Access Point on a Metal Wall Application

A 4x4 MIMO Antenna Array for the Wi-Fi7Access Point on a Met...

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2024 International Symposium on Antennas and Propagation, ISAP 2024

作者： Su, Hsin-Lung Zhan, You-Sheng Dept. of Computer and Communication National Pingtung University Taiwan Dept. of Computer Science and Information Engineering National Pingtung University Taiwan

ISBN: (纸本)9798350364774

A 4×4 CPW MIMO Antenna array with an artificial magnetic conductor (AMC) reflector is presented for Wi-Fi7 access point on a metal wall application in the study. The 10-dB impedance of the integrated MIMO antenna array covers the Wi-Fi 7 operating bands, and the transmission coefficients are under -15 dB in the whole Wi-Fi7 bands. This proposed integrated MIMO antenna is low profile and has good total radiation efficiency (over 60%). The height of the integrated MIMO antenna array is 6.325 mm. © 2024 IEEE.

关键词： Wireless local area networks (WLAN)

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IMPROVED INDOOR FORMALDEHYDE MONITORING SYSTEM USING ENHANCED SELF-DEVELOPED CIRCUITS AND LOCAL OUTLIER FACTOR ALGORITHM

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: electrical engineering and computer science 2022年第2期84卷 137-152页

作者： Li, Bin Zhong, Kai Niu, Yongyue Cui, Peng Xue, Liang Ji, Nan Wei, Dahui Dept. of Electrical and Computer Engineering Jilin Jianzhu University China

An indoor distributed formaldehyde monitoring system has been developed with multiple self-developed sensor nodes and wireless communication circuits. Local outlier factor algorithm has been adopted to increase the accuracy of the system. In addition, software has been developed based on LabVIEW for data receiving, data storing, data displaying and remote accessing. Experiments were carried out to evaluate the performance of this improved system. Compared to our previous work, the proposed system exhibits some improvements in performance of formaldehyde sensing ability, software function and quality of wireless communication due to the enhancement of hardware and software in the system. © 2022, Politechnica University of Bucharest. All rights reserved.

关键词： Remote control

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Hybrid Fake News Detection Model: Bagging and Logistic Regression Approach 14

Hybrid Fake News Detection Model: Bagging and Logistic Regre...

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14th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2025

作者： Kumar, Shivam Tiwari, Naveen Kumar Bajpai, Abhishek Yadav, Shashank Dept. of Computer Science and Engineering Rajkiya Engineering College Kannauj UP Kannauj India

ISBN: (纸本)9798331531935

In Today’s world or from Past Scenario’s Fake News has a Huge Impact on Everyone’s Lives including Politics, Sports, Education, External Foreign Affairs, Defense, etc. This project aims to develop a model for identifying and detecting fake news. In this model, we implement an ensemble method that leverages the TF IDF vectorization technique to extract meaningful textual features and employ a Bagging Classifier with Logistic Regression as the base estimator to enhance classification accuracy. To build this classifier, we utilized the scikit learn library. Our work was implemented using Jupyter Notebook, an online platform. For feature extraction, we employed a well-known vectorizer called Term Frequency Inverse Document Frequency (TF-IDF). We split our data into training sets (75%) and test sets (25%). The proposed model achieves an accuracy of 99.15% on the test dataset, with a precision of 99.45%, a recall of 99%, and an F1-score of 99.17%. It outperforms standalone Logistic Regression, Decision Tree, Random Forest, and Gradient Boosting classifiers. © 2025 IEEE.

关键词： Logistic regression

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Mutiphysics Analysis for Electromagnetics-Structural Deformation-Circuit Coupled Problem of Electromagnetic Expulsive De-icing System

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Transactions of the Korean Institute of electrical Engineers 2022年第11期71卷 1599-1607页

作者： Kang, Sung-Jun Lee, Jun-Sung Rho, Seung-Eun Park, Jong-Oh Jung, Eun-Chae Park, Il-Han Dept. of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

One of the ice protection systems for flights above medium altitudes is the electromagnetic explusive deicing system(EEDS). EEDS is composed of a coil which is structurally deformed by electromagnetic repulsion of electric current supplied by external circuit, a complex multiphysics phenomenon requiring electromagnetic, structural, and circuit analysis simultaneously. In this paper, we suggest electromagnetic(EM)-structural deformation-circuit coupled lumped parameter system for the analysis of EEDS. The results of the numerical analysis using the coupled lumped parameter system is compared with the results of measuring experiment using the EEDS prototype, which showed high concordance in current, electromagnetic force, and displacement. The coupled lumped parameter system enables bi-directional analysis which takes into account the interdependence between the different systems. Furthermore, it can significantly reduce the computational cost, which enables complex performance evaluation on various design variables and saves time and cost in the initial design steps. Copyright © The Korean Institute of electrical Engineers.

关键词： Timing circuits

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An Extension of Interior Point Differential Dynamic Programming for Optimal Control Problems with Second-Order Conic Constraints

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Transactions of the Korean Institute of electrical Engineers 2022年第11期71卷 1666-1672页

作者： Kim, Min-Gyeom Kim, Kwang-Ki Dept. of Electrical and Computer Engineering Inha University Korea Republic of

This paper presents the second-order conic IPDDP (SOC-IPDDP) that modifies interior point differential dynamic programming (IPDDP) to explicitly handle second-order conic constraints. Differential dynamic programming (DDP) has been widely used to solve nonlinear optimal control problems in control and robotics. However, DDP has a big drawback that it cannot handle hard constraints and constraints are usually encoded softly as parts of the cost functions. To overcome this constraint-handling limitation of DDP, interior point differential dynamic programming (IPDDP) is proposed to deal with hard constraints using the interior point method. In this paper, we extend IPDDP to efficiently take care of second-order conic constraints by exploiting their algebraic structures. For demonstration, the performances of SOC-IPDDP are compared with IPDDP in the planar rocket landing optimal control problem. It is shown that the proposed SOC-IPDDP has a comparable convergence rate to the existing IPDDP and is less sensitive to the changes in the parameters of the cost function. Copyright © The Korean Institute of electrical Engineers.

关键词： Cost functions

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Inverter Control of Scheme for IEEE1547-2018 Category3 in Fuel Cell Systems

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Transactions of the Korean Institute of electrical Engineers 2022年第1期71卷 90-97页

作者： Won, Su-Yeon Lee, Kyo-Beum Dept. of Electrical and Computer Engineering Ajou University Korea Republic of

This paper presents an inverter control scheme for fuel cell systems in IEEE1547-2018 Category3. The current configuration of Grid-Connected fuel cell system has limitations Category3's LVRT (Low Voltage Ride Through) reponse, additional inverter are needed. The inverter operates in an abnormal state where the grid voltage is unstable, and normally supplies the voltage to BOP (Balance of Plant) of the fuel cell system. Simulated verification of the inverter control scheme was performed to change the voltage source to the BOP from grid to inverter during abnormal conditions. © 2022 Korean Institute of electrical Engineers. All rights reserved.

关键词： Fuel cells

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Authentication and Authorization in Zero Trust IoT: A Survey 35

Authentication and Authorization in Zero Trust IoT: A Survey

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35th Irish Systems and Signals Conference, ISSC 2024

作者： James, Meha Newe, Thomas O'Shea, Donna O'Mahony, George D. Munster Technological University Dept. Computer Science Cork Ireland University of Limerick Dept. Electronic and Computer Engineering Limerick Ireland

ISBN: (纸本)9798350352986

A critical challenge in implementing Zero trust (ZT) in Internet of Things (IoT) environments is ensuring secure authentication and authorization mechanisms. The work in this article delves into the intricate realm of ZT by critically examining the state-of-the-art authentication and authorization processes within the ZT framework for IoT. Despite the wealth of work on ZT and Zero Trust Architecture (ZTA), notable research gaps persist, specifically in identity authentication and fine-grained access control. Given the vast and diverse ecosystem of IoT devices, device identification complexities arise from a lack of unique hardware identifiers, rendering traditional methods susceptible to cyber-attacks, such as, spoofing. For dynamic IoT environments, achieving the optimal implementation in access policies poses a significant challenge. Numerous ZTA methodologies, integrating access controls, blockchain frameworks, and advancements in Artificial Intelligence (AI) and Machine Learning (ML), have been implemented to tackle these challenges. However, research gaps remain, particularly in understanding the behavioral aspects within these frameworks. As a result, this article focuses on identifying how device behavioral aspects can improve authentication and authorization in ZT for IoT. Finally, the article concludes by highlighting how these challenges can serve as future research directions. © 2024 IEEE.

关键词： Authorization

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Nonlinear HF Propagation in the Ionosphere above HAARP

Nonlinear HF Propagation in the Ionosphere above HAARP

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2025 United States National Committee of URSI National Radio science Meeting, USNC-URSI NRSM 2025

作者： Burch, Harrison R. Moore, Robert C. University of Florida Dept. of Electrical & Computer Engineering GainesvilleFL32611 United States

ISBN: (纸本)9781946815200

The nature of HF radio wave propagation through the lower ionosphere has significant impact on scientific efforts such as ELF/VLF wave generation and ionospheric sounding, as well as operational efforts e.g. over-the-horizon radar and satellite-to-ground communications. Historical interpretation of propagation within the lower ionosphere centers on D-region absorption models, but observations of polar mesospheric echoes in HF and VHF radars and anomalous absorption in HF cross-modulation experiments highlight the potential for other interactions to impact HF radio wave propagation in the lower ionosphere. © 2025 USNC-URSI.

关键词： D region

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K-Band QPSK PMCW Radar with Digital I/Q Constellation Phase Compensation and I/Q Imbalance Correction

K-Band QPSK PMCW Radar with Digital I/Q Constellation Phase ...

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2025 IEEE Topical Conference on Wireless Sensors and Sensor Networks, WiSNeT 2025

作者： Thompson, Derek Li, Changzhi Dept. of Electrical and Computer Engineering Texas Tech University LubbockTX United States

ISBN: (纸本)9798331507336

This paper presents a novel K-Band Quadrature Phase Shift Keying (QPSK) phase-modulated continuous-wave (PMCW) radar front end architecture with digital I/Q constellation phase compensation and I/Q channel imbalance correction. Although QPSK is a very common form of digital phase modulation, it is rarely reported for PMCW radar systems, especially those designed on printed circuit board (PCB) technology. A MATLAB simulation platform is also developed and presented to help verify the benefits of QPSK PMCW radar for range detection. © 2025 IEEE.

关键词： MATLAB

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