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Advanced BERT and CNN-Based Computational Model for Phishing Detection in Enterprise Systems

computer Modeling in engineering & Sciences 2024年第12期141卷 2165-2183页

作者： Brij B.Gupta Akshat Gaurav Varsha Arya Razaz Waheeb Attar Shavi Bansal Ahmed Alhomoud Kwok Tai Chui Department of Computer Science and Information Engineering Asia UniversityTaichung413Taiwan Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India University Centre for Research and Development(UCRD) Chandigarh UniversityChandigarh140413India Computer Engineering Ronin InstituteMontclairNJ 07043USA Department of Business Administration Asia UniversityTaichung413Taiwan Department of Electrical and Computer Engineering Lebanese American UniversityBeirut1102Lebanon College of Business Administration Management DepartmentPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Research and Innovation Insights2TechinfoJaipur302001India Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Department of Electronic Engineering and Computer Science Hong Kong Metropolitan University(HKMU)Hong Kong518031China

Phishing attacks present a serious threat to enterprise systems,requiring advanced detection techniques to protect sensitive *** study introduces a phishing email detection framework that combines Bidirectional Encoder Representations from Transformers(BERT)for feature extraction and CNN for classification,specifically designed for enterprise information ***’s linguistic capabilities are used to extract key features from email content,which are then processed by a convolutional neural network(CNN)model optimized for phishing *** an accuracy of 97.5%,our proposed model demonstrates strong proficiency in identifying phishing *** approach represents a significant advancement in applying deep learning to cybersecurity,setting a new benchmark for email security by effectively addressing the increasing complexity of phishing attacks.

关键词： Phishing BERT convolutional neural networks email security deep learning

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Smart Water Level River Monitoring System with IoT 13

Smart Water Level River Monitoring System with IoT

引用

13th IEEE Global Conference on Consumer electronic, GCCE 2024

作者： Ibrahim, Iffan Darwis Bin Mohd Kadir, Herdawatie Abdul Saon, Sharifah Mahamad, Abdul Kadir Isa, Khalid Ahmadon, Mohd Anuaruddin Yamaguchi, Shingo Universiti Tun Hussein Onn Malaysia Faculty of Electric and Electronic Engineering Johor Batu Pahat Malaysia Universiti Teknologi Petronas Department of Computer and Information Sciences Perak Seri Iskandar Malaysia Yamaguchi University Graduate School of Sciences and Technology for Innovation Japan

ISBN: (纸本)9798350355079

This project aims to design and develop a smart IoT system for monitoring river water levels to alert the community and authorities to prevent flooding. The system comprises a water level sensor, a temperature sensor, a low-cost, Wi-Fi-enabled microcontroller with a full TCP/IP stack, a 32-bit RISC processor for Internet of Things (IoT) development, and a custom dashboard for monitoring purposes. Leveraging the Favoriot platform for data visualization, the system enables real-time monitoring of water levels and incorporates an alert notification system via Telegram. The water level and temperature sensors provide real-time data, allowing the system to promptly trigger alerts when necessary. The seamless integration of software and hardware demonstrates the effective functionality of this system in detecting relevant parameters. The alert notification will be sent if the distance between the level sensor and the water surface is less than 7 cm. Real-time data transmission to the Favoriot platform ensures continuous monitoring of river water levels, thereby significantly assisting users and authorities in implementing effective flood risk mitigation strategies. © 2024 IEEE.

关键词： Wi-Fi

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ELENA: EPIGENETIC LEARNING THROUGH EVOLVED NEURAL ADAPTATION

arXiv

引用

arXiv 2025年

作者： Boris, Kriuk Keti, Sulamanidze Fedor, Kriuk Department of Computer and Electronic Engineering Hong Kong University of Science and Technology Hong Kong School of Science and Technology IE University Spain Faculty of Engineering and Information Technology University of Technology Sydney Australia

Despite the success of metaheuristic algorithms in solving complex network optimization problems, they often struggle with adaptation, especially in dynamic or high-dimensional search spaces. Traditional approaches can become stuck in local optima, leading to inefficient exploration and suboptimal solutions. Most of the widely accepted advanced algorithms do well either on highly complex or smaller search spaces due to the lack of adaptation. To address these limitations, we present ELENA (Epigenetic Learning through Evolved Neural Adaptation), a new evolutionary framework that incorporates epigenetic mechanisms to enhance the adaptability of the core evolutionary approach. ELENA leverages compressed representation of learning parameters improved dynamically through epigenetic tags that serve as adaptive memory. Three epigenetic tags (mutation resistance, crossover affinity, and stability score) assist with guiding solution space search, facilitating a more intelligent hypothesis landscape exploration. To assess the framework’s performance, we conduct experiments on three critical network optimization problems: the Traveling Salesman Problem (TSP), the Vehicle Routing Problem (VRP), and the Maximum Clique Problem (MCP). Experiments indicate that ELENA achieves competitive results, often surpassing state-of-the-art methods on network optimization tasks. Copyright © 2025, The Authors. All rights reserved.

关键词： Contrastive Learning

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Mobile Phone Detector in Restricted Area 13

Mobile Phone Detector in Restricted Area

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13th IEEE Global Conference on Consumer electronic, GCCE 2024

作者： Ismail, Abdurrahman Ponniran, Asmarashid Choon, Chew Chang Eh Kan, Chessda Uttraphan Ahmadon, Mohd Anuaruddin Yamaguchi, Shingo Universiti Tun Hussein Onn Malaysia Faculty of Electrical and Electronic Engineering Johor Batu Pahat Malaysia Universiti Teknologi Petronas Department of Computer and Information Sciences Perak Seri Iskandar Malaysia Yamaguchi University Graduate School of Sciences and Technology for Innovation Japan

ISBN: (纸本)9798350355079

The proliferation of smartphones has heightened concerns regarding their unauthorized use in restricted areas, posing significant security risks and compromising data integrity. This paper addresses the challenge of detecting unauthorized mobile phone activity in sensitive locations, focusing on examination rooms as a critical case study. It proposes a mobile phone detector system using RF signal detection and an IoT platform for real-time alerts. The system, built with Arduino and an antenna, uses an AD8318 RF power detector to analyse signals from mobile phones. The system successfully detects 4G and 5G signals within a voltage range of 1.2 V to 0.7 V and an effective range of up to 30 cm. It also features real-time alerts via a buzzer and data transmission to the Blynk IoT platform, enhancing security. Tests confirmed the system's accuracy and reliability, though it has limitations such as inconsistent response times and limited detection range. Future improvements will focus on extending the detection range and refining the alert mechanisms for better performance in various environments. © 2024 IEEE.

关键词： Smartphones

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What's the Real: A Novel Design Philosophy for Robust AI-Synthesized Voice Detection 24

What's the Real: A Novel Design Philosophy for Robust AI-Syn...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Hai, Xuan Liu, Xin Tan, Yuan Liu, Gang Li, Song Niu, Weina Zhou, Rui Zhou, Xiaokang School of Information Science and Engineering Lanzhou University Lanzhou China The State Key Laboratory of Blockchain and Data Security Zhejiang University Hangzhou China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Faculty of Business Data Science Kansai University Osaka Japan

ISBN: (纸本)9798400706868

Voice is one of the most widely used media for information transmission in human society. While high-quality synthetic voices are extensively utilized in various applications, they pose significant risks to content security and trust building. Numerous studies have concentrated on AI-synthesized voice detection to mitigate these risks, with many claiming to achieve promising performance. However, recent research has demonstrated that fake voice detectors suffer from serious overfitting to speaker-irrelative features (SiFs) and cannot be used in real-world scenarios. In this paper, we analyze the limitations of existing fake voice detectors and propose a new design philosophy, guiding the detection model to prioritize learning human voice features rather than the difference between the human voice and the synthetic voice. Based on this philosophy, we propose a novel AI-synthesized voice detection framework named SiFSafer, which uses pre-trained speech representation models to enhance the learning of feature distribution in human voices and the adapter fine-tuning to optimize the performance. The evaluation shows that the average EERs of existing fake voice detectors in the ASVspoof datasets can exceed 20% if the SiFs like silence segments are removed, while SiFSafer achieves an EER of less than 8%, indicating that SiFSafer is robust to SiFs and strongly resistant to existing attacks. © 2024 ACM.

关键词： Fake detection

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Orthogonal matrix of polarization combinations:concept and application to multichannel holographic recording

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Opto-electronic Advances 2024年第10期7卷 4-13页

作者： Shujun Zheng Jiaren Tan Hongjie Liu Xiao Lin Yusuke Saita Takanori Nomura Xiaodi Tan Information Photonics Research Center College of Photonic and Electronic EngineeringFujian Normal UniversityFuzhou 350117China Department of Electrical and Computer Engineering Duke UniversityDurhamNC 27708USA College of Photonic and Electronic Engineering Key Laboratory of Opto-Electronic Science and for Medicine of Ministry of EducationFujian Provincial Key Laboratory of Photonics TechnologyFujian Provincial Engineering Technology Research Center of Photoelectric Sensing ApplicationFujian Normal UniversityFuzhou 350117China Faculty of Systems Engineering Wakayama University930 SakaedaniWakayama640-8510Japan.

Orthogonal matrices have become a vital means for coding and signal processing owing to their unique distributional *** orthogonal matrices based on amplitude or phase combinations have been extensively explored,the orthogonal matrix of polarization combinations(OMPC)is a novel,relatively unexplored ***,we propose a method for constructing OMPCs of any dimension encompassing 4n(where n is 1,2,4,8,…)mutually orthogonal 2ncomponent polarization *** the field of holography,the integration of polarization multiplexing techniques with polarization-sensitive materials is expected to emerge as a groundbreaking approach for multichannel hologram multiplexing,offering considerable enhancements in data storage capacity and security.A multidimensional OMPC enables the realization of multichannel multiplexing and dynamical modulation of information in polarization holographic *** consolidating all information into a single position within the material,we effectively avoided extraneous crosstalk during the reconstruction *** results show that achieving four distinct holographic images individually and simultaneously depends on the polarization combination represented by the incident *** discovery opens up a new avenue for achieving highly holographic information storage and dynamically displayed information,harnessing the potential of OMPC to expand the heretofore limited dimensionality of orthogonal polarization.

关键词： orthogonal matrix of polarization combinations polarization-modulated multiplexing multichannel recording polarization holography dynamical information modulation

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SDSFusion: A Semantic-Aware Infrared and Visible Image Fusion Network for Degraded Scenes

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IEEE Transactions on Image Processing 2025年 34卷 3139-3153页

作者： Chen, Jun Yang, Liling Yu, Wei Gong, Wenping Cai, Zhanchuan Ma, Jiayi China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China China University of Geosciences Faculty of Engineering Wuhan430074 China Macau University of Science and Technology School of Computer Science and Engineering Taipa China Wuhan University Electronic Information School Wuhan430072 China

A single-modal infrared or visible image offers limited representation in scenes with lighting degradation or extreme weather. We propose a multi-modal fusion framework, named SDSFusion, for all-day and all-weather infrared and visible image fusion. SDSFusion exploits the commonality in image processing to achieve enhancement, fusion, and semantic task interaction in a unified framework guided by semantic awareness and multi-scale features and losses. To address the disparity between infrared and visible images in degraded scenes, we differentiate modal features in a unified fusion model. Unlike existing joint fusion methods, we propose an adversarial generative network that refines the reconstruction of low-light images by embedding fused features. It provides feature-level brightness supplementation and image reconstruction to refine brightness and contrast. Extensive experiments in degraded scenes confirm that our approach is superior to state-of-the-art approaches in visual quality and performance, demonstrating the effectiveness of interaction improvement. © 1992-2012 IEEE.

关键词： Image coding

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Optimal site selection for utility-scale solar PV projects using a RETscreen-AHP-TOPSIS framework: application to the southern Cameroon

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Sustainable Energy Research 2025年第1期12卷 1-18页

作者： Ayuketah, Yvan Edimu, Milton Mwikirize, Cosmas Department of Electrical and Computer Engineering College of Engineering Design Art and Technology Makerere University P.O. Box 7062 Kampala Uganda Department of Electrical and Electronic Engineering Faculty of Engineering and Technology University of Buea P.O. Box 63 Buea Cameroon

Several countries have renewable energy portfolios aimed at reducing energy sector emissions while diversifying their generation mixes. A cornerstone in these global portfolios is solar photovoltaics (PV) which offer a mature and rapidly deployable solution. Selecting optimal sites for utility-scale solar PV projects remains a complex challenge, requiring the integration of technical, economic, environmental and social criteria. This study proposes a hybrid decision-making framework that embeds financial viability metrics such as net present value (NPV) and greenhouse gas (GHG) emissions savings into multi-criteria analysis. The framework integrates RETScreen Expert for technoeconomic evaluation, the analytical hierarchy process (AHP) for criteria weighting, and the Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) for ranking alternatives. Applied to fourteen locations in the Southern Interconnected Grid in Cameroon, the model considers a hypothetical 10MW grid-connected solar PV plant. Results identify Baffousam as the optimal location due to its higher solar potential, favorable land use, and grid proximity. Sensitivity analysis reveals the influence of subjectivity weighting in AHP, with land use criterion contributing significantly to site selection, underscoring the need for stakeholder engagement. By bridging traditional energy planning tools (RETScreen) with MCDM techniques, this study addresses a critical gap in existing frameworks which often neglect the time value of money and financial viability. The modular design allows adaptation to regional priorities, offering policy makers and investors a replicable blueprint for emerging economies. This approach advances sustainable energy transitions while balancing technical, economic, and environmental priorities in site selection. © The Author(s) 2025.

关键词： Site selection

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A Study of Localization in 5G Green Network (5G-GN) for Futuristic Cellular Communication 3rd

A Study of Localization in 5G Green Network (5G-GN) for Futu...

引用

3rd International Conference on Communication, Devices and Computing, ICCDC 2021

作者： Pradhan, Devasis Sahu, P.K. Rajeswari Tun, Hla Myo Department of Electronics & Communication Engineering Acharya Institute of Technology Karnataka Bengaluru India National Institute of Technology Odisha Rourkela India Department of Electronic Engineering Faculty of Electrical and Computer Engineering Yangon Technological University Yangon Myanmar

ISBN: (纸本)9789811691539

The fifth-generation (5G) remote environment will be fundamental for a horde of new applications dependent on precise area mindfulness and other logical data. Such a remote environment will be empowered by cutting-edge 5G remote innovations coordinated with existing advancements for the Internet-of-things (IoT) and the worldwide route satellite framework. With immense mm-Wave range and tight shaft reception apparatus innovation, exact position area is currently conceivable in 5G and future portable correspondence frameworks. As yet being a field being developed, a restriction is relied upon to be completely unavoidable in the following not many years. Albeit the improvement of such strategies is driven by the commercialization of area-based administrations (e.g., route), its application to help cell the executives are considered to be a vital methodology for improving its flexibility and execution. This paper gives a depth of the concept, requirements, and signal processing advancement in localization for accurate positioning. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Signal processing

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New 5G Kaiser-Based Windowing to Reduce Out of Band Emission

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computers, Materials and Continua 2022年第2期71卷 2721-2738页

作者： Hammoodi, Ahmed Audah, Lukman Al-Jobouri, Laith Mohammed, Mazin Abed Aljumaily, Mustafa S. Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia Johor Batu Pahat86400 Malaysia School of Engineering Arts Science and Technology University of Suffolk IP4 1QJ United Kingdom College of Computer Science and Information Technology University of Anbar Anbar 31001 Iraq Electrical Engineering and Computer Science Department University of Tennessee KnoxvilleTN37901 United States

OFDM based waveforms are considered as the main part of the latest cellular communications standard (namely 5G). Many inherited problems from the OFDM-Based LTE are still under investigation. Getting rid of the out of band emissions is one of these problems. Ensuring low out of band emission (OOBE) is deemed as one of the most critical challenges to support development of future technologies such as 6G and beyond. Universal Filtered Multi Carrier (UFMC) has been considered as one of the candidate waveforms for the 5G communications due to its robustness against Inter Carrier Interference (ICI) and the Inter Symbol Interference (ISI). It is also a preferred option because it is the most appropriate for low latency scenarios. In this paper, a novel approach is proposed that makes use of modified Kaiser-Bessel filter-based pulse windowing instead of standard Dolph-Chebyshev filter for UFMC based waveform. The aim of proposing the new approach is to enable the reduction of spectral leakage into nearby sub-bands. A comprehensive study for the modified Kaiser-Bessel filters is performed and the results are presented in terms of several Key Performance Indicators (KPIs). Based on the results of the simulation, the UFMC Kaiser-Hankel window demonstrated lower sidebands and better power spectral density, when compared with the traditional Orthogonal frequency-division multiplexing (OFDM) and UFMC as well as the normal UFMC Kaiser window. In addition, the real test for the kaiser window with 5G waveform is lower OOBE than conventional 5G waveform (CP-OFDM and UFMC). The OOBE reduction of 31% of the Kaiser vs. the Dolph-Chebyshev filter, 68% of Kaiser Hankel over the Dolph-Chebyshev, and 20% of Kaiser Hankel over Kaiser filter have been reported in this paper. The Power Spectral Density has been improved accordingly. © 2022 Tech Science Press. All rights reserved.

关键词： Orthogonal frequency division multiplexing

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