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2023 Seminar on Signal Processing, SoSP 2023

作者： The, Quan Trong Huy, Nguyen Ba Anh, Pham Tuan Ha Noi University of Science and Technology Falculty of Information Technology Ha Noi Viet Nam University ITMO Falculty of Control Systems and Robotics Saint-Petersburg Russia University ITMO Falculty of Software Engineering and Computer Systems Saint-Petersburg Russia

ISBN: (纸本)9798350371086

Speech processing devices such as mobile telephone, hearing aid, cochlear implant is commonly equipped with a designed microphone array (MA) to capture the acoustic environment. The MA signals often contain a mixture of desired speech component and unwanted surrounding noise (a combination of reverberation, different interferences, complex recording environment, third-party speaker). Minimum Distortionless Variance Response (MVDR) beamformer is one the most useful methods for reducing background noise and improving speech enhancement has been recently studied. MVDR beamformer merges the predefined constraints of response from a priori relative transfer function and the criteria of minimum total output noise power. Because of the microphone mismatches, the different microphone sensitivities, or the error of the direction of arrival of the interest signal, the output final signal of MVDR beamformer often corrupted. In this paper, the authors proposed an additive gain function for reducing speech distortion and enhancing MVDR beamformer's performance. © 2023 IEEE.

关键词： Signal to noise ratio

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Artificial Intelligence Techniques Based Learner Authentication in Cybersecurity Higher Education Institutions

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Computers, Materials & Continua 2022年第8期72卷 3131-3144页

作者： Abdullah Saad AL-Malaise AL-Ghamdi Mahmoud Ragab Information Systems Department Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah21589Saudi Arabia Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Centre of Artificial Intelligence for Precision Medicines King Abdulaziz UniversityJeddah21589Saudi Arabia Mathematics Department Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt

Education 4.0 is being authorized more and more by the design of artificial intelligence(AI)*** education institutions(HEI)have started to utilize Internet technologies to improve the quality of the service and boost *** to the unavailability of information technology(IT)infrastructures,HEI is vulnerable to *** authentication can be used to authenticate a person based on biological features such as face,fingerprint,iris,and so *** study designs a novel search and rescue optimization with deep learning based learning authentication technique for cybersecurity in higher education institutions,named SRODLLAC *** proposed SRODL-LAC technique aims to authenticate the learner/student in HEI using fingerprint ***,the SRODLLACtechnique designs a median filtering(MF)based preprocessing approach to improving the quality of the *** addition,the Densely Connected Networks(DenseNet-77)model is applied for the extraction of ***,search and rescue optimization(SRO)algorithm with deep neural network(DNN)model is utilized for the classification ***,template matching process is done for fingerprint identification.A wide range of simulation analyses is carried out and the results are inspected under several *** experimental results reported the effective performance of the SRODL-LAC technique over the other methodologies.

关键词： Cybersecurity authentication biometrics security higher education institution deep learning

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Optimal Deep Belief Network Enabled Cybersecurity Phishing Email Classification

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Computer systems Science & Engineering 2023年第3期44卷 2701-2713页

作者： Ashit Kumar Dutta T.Meyyappan Basit Qureshi Majed Alsanea Anas Waleed Abulfaraj Manal M.Al Faraj Abdul Rahaman Wahab Sait Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityAd DiriyahRiyadh13713Kingdom of Saudi Arabia Department of Computer Science Alagappa UniversityKaraikudi630003India Department of Computer Science Prince Sultan UniversityRiyadh11586Kingdom of Saudi Arabia Department of Computing Arabeast CollegesRiyadh11583Kingdom of Saudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah23613Kingdom of Saudi Arabia Department of Archives and Communication King Faisal UniversityAl AhsaHofuf31982Kingdom of Saudi Arabia

Recently,developments of Internet and cloud technologies have resulted in a considerable rise in utilization of online media for day to day *** results in illegal access to users’private data and compromises *** is a popular attack which tricked the user into accessing malicious data and gaining the *** identification of phishing emails can be treated as an essential process in the domain of *** article focuses on the design of bio-geography based optimization with deep learning for Phishing Email detection and classification(BBODL-PEDC)*** major intention of the BBODL-PEDC model is to distinguish emails between legitimate and *** BBODL-PEDC model initially performs data pre-processing in three levels namely email cleaning,tokenization,and stop word ***,TF-IDF model is applied for the extraction of useful feature ***,optimal deep belief network(DBN)model is used for the email classification and its efficacy can be boosted by the BBO based hyperparameter tuning *** performance validation of the BBODL-PEDC model can be performed using benchmark dataset and the results are assessed under several *** comparative studies reported the superior outcomes of the BBODL-PEDC model over the recent approaches.

关键词： Cybersecurity phishing email data classification deep learning biogeography based optimization hyperparameter tuning

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A new hybrid teaching learning based Optimization -Extreme learning Machine model based Intrusion-Detection system

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Materials Today: Proceedings 2023年 80卷 2701-2705页

作者： Qahatan Alsudani, Mustafa Abbdal Reflish, Salah H. Moorthy, Kohbalan Mundher Adnan, Myasar Computer Techniques Engineering Department Faculty of Information Technology Imam Ja'afar Al-sadiq University Najaf Iraq Faculty of Computer Systems & Software Engineering Universiti Malaysia Pahang Kuantan Malaysia Islamic University Najaf Iraq Faculty of Engineering School of Computing Universiti Teknologi Malaysia Johor Bahru81310 Malaysia

Currently, effective Intrusion-detection systems (IDS) still represent one of the important security tools. However, hybrid models based on the IDS achieve better results compared with intrusion detection based on a single algorithm. But even so, the hybrid models based on traditional algorithms still face different limitations. This work is focused on providing two main goals;firstly, analysis based on the main methods and limitations of the most-recent hybrid model-based on intrusion detection, secondly, to propose a novel hybrid IDS model called TLBO-ELM based on the Firefly algorithm and Fast Learning Network. © 2021

关键词： Optimization

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An Effective Post - Filtering for Minimum Variance Distortionless Response Beamformer

An Effective Post - Filtering for Minimum Variance Distortio...

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2023 Seminar on Signal Processing, SoSP 2023

ISBN: (纸本)9798350371086

An effective hands-free speech interface with an appropriate digital signal processing is essential for teleconference systems and control systems. Beamforming technique, which use a microphone array (MA) is an ideal solution for distant - talking speech acquisition, is one of the most attractive approaches for suppressing background noise and improving the speech intelligibility and speech quality of the processing system. Minimum Variance Distortionless Response (MVDR) has the capacity of maximizing the sensitivity in a certain direction at aiming to extract the desired target speech while removing all total power of surrounding noise. However, in many complex recording environments, due to the error of direction of arrival of interest speaker, the difference of microphone sensitivities, imprecise designed geometry of MA, the performance of MVDR beamformer often degraded. In this contribution, the authors suggested an additive post-filtering to enhance the effectiveness of MVDR beamformer. © 2023 IEEE.

关键词： Signal to noise ratio

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A scalable framework for secure and reliable wireless-based fog cloud communication

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Measurement: Sensors 2025年 37卷

作者： Khairosheva, Kymbat Razaque, Abdul Bektemyssova, Gulnara Yoo, Joon Department of Intelligent Systems and Cybersecurity Astana IT University Kazakhstan School of Computing Gachon University Korea Republic of Department of Computer Engineering and Information Systems International Information Technology University Almaty Kazakhstan

—Wireless telecommunication systems are essential in transferring data through fog cloud servers. However, the fog cloud servers suffer from unreliable and non-secure routing and limited power resources when mobile users are mobile. This paper introduces a scalable framework (SFRRDC) for reliable wireless routing and secure data transfer. We aim to address security and reliability issues by combining pheromone termite (PT) characteristics and ant colony optimization (ACO) algorithms for high-performance, more secure, highly reliable data transfer among the fog cloud servers. For that, the proposed SFRRDC supports a user authentication mining (UAM) algorithm to secure the confidentiality of the users. Based on testing results, it is confirmed that the proposed SFRRDC provides a better solution for confidentiality and fast routing for a wireless telecommunication system. The results show that the proposed SFRRDC framework's energy consumption outperforms competing frameworks' energy consumption with a better-achieved latency. For example, the suggested SFRRDC method uses 748.5 J during 72 h of operation, competing frameworks use more energy, and DDFQFR uses 976.22 J. It also shows that the proposed SFRRDC is immune to malicious attacks. The results show that with 3600 Fog cloud users, the proposed HEE protocol reduces the number of attacks to only 48 compared to 58, 72, and 77415 expected malicious attacks when using the ICDRP-F-SDVN, ACO, and DDFQFR frameworks, respectively. © 2024

关键词： Ant colony optimization

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Security Perspectives in Integrity Verification for Shared Data in Cloud—A Survey 1

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9th International Conference on Cyber Security, Privacy in Communication Networks, ICCS 2023

作者： Pailkar, Harsh Murugan, Thangavel School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh Bhopal India Department of Information Systems and Security College of Information Technology United Arab Emirates University Al Ain Abu Dhabi United Arab Emirates

ISBN: (数字)9789819739738

ISBN: (纸本)9789819739721

As businesses move their data and services to cloud computing environments, it is crucial to ensure the security and integrity of that shared data. In order to study the new security perspectives in the context of integrity verification for shared data in the cloud, this research article conducts an extensive examination of the existing solutions. A key component of cloud security, data integrity, is thoroughly examined with an emphasis on the difficulties it faces and the consequences it may have in cloud-based scenarios. Analyzing the distinctive qualities of shared data in the cloud reveals the complications that develop when organizations access and work together on data inside a shared ecosystem. This article addresses research gaps and limitations within the existing solutions by critically examining prior studies. It emphasizes the requirement for novel strategies and answers to deal with the complex data integrity problems of shared data in cloud. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Data integrity

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Blockchain-Enabled Quality Assurance and Traceability in the Indian Confectionery Market

Blockchain-Enabled Quality Assurance and Traceability in the...

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2024 International Conference on Innovative computing, Intelligent Communication and Smart Electrical systems, ICSES 2024

作者： Subashini, B. Shanthi, P. Venkatesh, K. School of Computing Srm Institute of Science and Technology Department of Data Science and Business Systems Tamilnadu kattankulathur India St. Joseph's Institute of Technology Department of Information Technology OMR Chennai119 India School of Computing Srm Institute of Science and Technology Department of Networking and Communications Tamilnadu kattankulathur India

ISBN: (纸本)9798331543617

India, whose population growth is its greatest asset cannot afford to let its people eat confectionery that is either tainted or somehow polluted, since this would lead to extensive malnutrition. Traditional food supply chains are characterized by centralization and the problems associated with it such as having a single point of failure and producing inconsistent products while compromising the quality, along with data loss. With the need for daily reports in all regions of India regarding food fraud, contamination, and adulteration, a clearly advanced decentralized model is sought after for the creation of a supply chain. This paper introduces the supply chain network for the Indian confectionery market based on blockchain to better address quality claims, contamination, and transparency. This enables real-time traceability within the ecosystem, by using IoT strategies along with the Ethereum blockchain leading to better product authentication and resulting in higher consumer confidence. Blockchain creates a secure data tracking function, while smart contracts can be used to define the process - such as IoT monitoring of temperature. The united method enables verified data to be available to the consumer, energy efficiency, and trust across the supply chain. © 2024 IEEE.

关键词： Smart contract

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Arithmetic Optimization with Deep Learning Enabled Anomaly Detection in Smart City

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Computers, Materials & Continua 2022年第10期73卷 381-395页

作者： Mahmoud Ragab Maha Farouk S.Sabir Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Centre of Artificial Intelligence for Precision Medicines King Abdulaziz UniversityJeddah21589Saudi Arabia Mathematics Department Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt Information Systems Department Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah21589Saudi Arabia

In recent years,Smart City Infrastructures(SCI)have become familiar whereas intelligent models have been designed to improve the quality of living in smart ***,anomaly detection in SCI has become a hot research topic and is widely explored to enhance the safety of *** increasing popularity of video surveillance system and drastic increase in the amount of collected videos make the conventional physical investigation method to identify abnormal actions,a laborious *** this background,Deep Learning(DL)models can be used in the detection of anomalies found through video surveillance *** current research paper develops an Internet of Things Assisted Deep Learning Enabled Anomaly Detection Technique for Smart City Infrastructures,named(IoTAD-SCI)*** aim of the proposed IoTAD-SCI technique is to mainly identify the existence of anomalies in smart city ***,IoTAD-SCI technique involves Deep Consensus Network(DCN)model design to detect the anomalies in input video *** addition,Arithmetic Optimization Algorithm(AOA)is executed to tune the hyperparameters of the DCN ***,ID3 classifier is also utilized to classify the identified objects in different *** experimental analysis was conducted for the proposed IoTADSCI technique upon benchmark UCSD anomaly detection dataset and the results were inspected under different *** simulation results infer the superiority of the proposed IoTAD-SCI technique under different metrics.

关键词： Object detection anomaly detection smart city infrastructure deep learning parameter tuning

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GENSIMO - A Generic Framework for Modelling Social Insurance systems 25th

GENSIMO - A Generic Framework for Modelling Social Insuranc...

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25th International Workshop on Multi-Agent-Based Simulation, MABS 2024

作者： de Haan, Fjalar J. Thompson, Jason School of Computing and Information Systems Faculty of Engineering and Information Technology The University of Melbourne Parkville Australia Melbourne Centre for Data Science The University of Melbourne Parkville Australia Department of Psychiatry Faculty of Medicine Dentistry and Health Sciences The University of Melbourne Parkville Australia

ISBN: (纸本)9783031880162

We report on the design, development and prototype testing of gensimo (GENeric Social Insurance MOdeling), a free and open-source software framework for modelling and simulation of social insurance systems. We discuss the conceptual and software design considerations of the framework in general before demonstrating how it works in detail by setting it up to model a particular social insurance scheme. We then present how we used this prototype set up to model the impact of a policy intervention on the workload of the insurer. While gensimo is under active development and we are a while away from serious verification and validation, this prototype testing shows realistic results. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： software testing

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