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Technique for Evaluating the Effectiveness of the Information Security Department 16

Technique for Evaluating the Effectiveness of the Informatio...

16th IEEE International Scientific and Technical Conference Actual Problems of Electronic Instrument engineering, APEIE 2023

作者： Belov, Viktor M. Pestunova, Tamara M. Belova, Nadezhda V. Kosov, Dmitry L. Information Security Dept. Novosibirsk State Technical University Novosibirsk Russia Computer Systems Dept. Novosibirsk State University Novosibirsk Russia Economics and Planning Dept. PJSC Rosneft Oil Company Moscow Russia

ISBN: (纸本)9798350330885

This article proposes a technique that establishes the procedure for evaluating the level of efficiency of the information security department (an employee performing information security functions). The technique uses performance evaluation criteria based on the apparatus of fuzzy logic, the composition of fuzzy relations. The technique describes the procedure for evaluating the effectiveness of the information security department (information security officer) during audits in the area of "Organization and state of work on information protection", self-assessment of the effectiveness of work. The method of assessing the level of efficiency consists in presenting with the help of a set of measurements (both at the quantitative and qualitative level) the features collected to build a classification of the effectiveness of the information security department (information security officer). Based on a set of measurements of signs, the decision-maker must determine (classify) the effectiveness of work using the criteria for assessing the quality of their work. In the future, the methodology can be expanded for additional purposes of predicting the level of security of informatization objects. © 2023 IEEE.

关键词： Classification (of information)

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Double Layer Message Security for 3D Object Using Mathematical Sequences and Secret Keys

Double Layer Message Security for 3D Object Using Mathematic...

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2023 International Telecommunications Conference, ITC-Egypt 2023

作者： Alkhamese, Aya Elgawalby, Hewayda Eid, Ahmad Hanafy, Ibrahim Awad, Wael Port Said University Faculty of Engineering Dept. Physics and Engineering Mathematics Port Said Egypt Port Said University Faculty of Engineering Electrical Engineering Department Port Said Egypt Port Said University Faculty of Science Dept. Mathematics and Computer Science Port Said Egypt Damietta University Faculty of Computers and Artificial Intelligence Dept. Computer Science Damietta Egypt

ISBN: (纸本)9798350326062

It's It's been so crucial lately to emphasize data security applying as the world depends on data exchange extensively almost in all domains. Steganography is one of the main techniques used to ensure information security in storage and during communication. We accomplish this novel technique by using two main layers. In the first layer, the secret message is compressed using Gzip or encrypted using Advanced Encryption Standard (AES). In the next layer, the binary representation of the secret message is embedded into vertices of x, y, and z-coordinates of the 3D object using the Gray code sequence, Recamán's sequence, and Lucas sequence. This binary representation of secret message is embedded using the Least Significant Bit (LSB) technique according to the value of the used sequence. Different performance measurements are computed and evaluated to ensure that the 3D object quality remains preserved such as Mean Square Error (MSE), Peak Signal-to-Noise Ratio (PSNR), embedding rate (ER), Normalized Hausdorff Distance (NHD) and maximum embedding capacity. The proposed scheme is compared with its counterparts in the literature. Outstanding numerical results are achieved, showing the superiority of the proposed schemes in the terms of performance, capacity, and security. © 2023 IEEE.

关键词： Steganography

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WNetMon: An ML Approach for Real-time DoS Attack Detection in Wireless Networks

WNetMon: An ML Approach for Real-time DoS Attack Detection i...

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Australasian Telecommunication Networks and Applications Conference, ATNAC

作者： Fahim Faisal Birupaxha Mondal Md Fahad Monir Tarem Ahmed Md Zahangir Alam Dept. of Computer Science and Engineering Independent University Bangladesh Dept. of Electrical and Computer Engineering Virginia Tech Blacksburg VA USA

ISBN: (数字)9798350379112

ISBN: (纸本)9798350379129

Denial of Service (DoS) attacks have emerged as sophisticated threats that exploit the known vulnerabilities of wireless communication, potentially sabotaging their operations and causing extensive downtime. Among these, de-authentication, disassociation and beacon flooding are particularly concerning due to their efficiency in disrupting network services. This paper delves into different types of Denial of Service (DoS) attacks and proposes a state-of-the-art detection mechanism. Most of the current state-of-the-art ML and DL-based IDSs are evaluated on the training dataset, which needs more variation in real-time attack data and requires substantial computational resources. In the following work, we propose a lightweight software solution named WNetMon, developed using the AWID2 dataset and evaluated using a new dataset generated using our custom testbed. Moreover, it can perform real-time Denial of Service (DoS) flooding attack detection on edge devices in wireless networks. Our results show that, while being small and effective, WNetMon achieves an overall accuracy of 99% for attack detection, benchmarked in real-time network traffic generated in our testbed. Therefore, it demonstrates the potential for using extensible ML solutions for Denial of Service (DoS) attack detection on edge systems that cannot execute industrial network monitoring tools due to resource constraints.

关键词： Training Performance evaluation Wireless networks Image edge detection Telecommunication traffic Benchmark testing Real-time systems Software Communications technology Monitoring

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AI-Driven Panic Detection and Alert System Using Smartwatch and LLM Model

AI-Driven Panic Detection and Alert System Using Smartwatch ...

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International Conference on Parallel Distributed and Grid Computing (PDGC)

作者： Balaram Pal Anubhab Gupta Soumyajit Paul Munshi Mustafijur Rahaman Dept. of Computer Science Engineering Bengal Institute of Technology Kolkata India Dept. of Computer Science Engineering GCECT Kolkata India

ISBN: (数字)9798331521349

ISBN: (纸本)9798331521356

Technologically, most existing systems cannot detect distress autonomously through pattern recognition, further compounding the challenge of providing timely help. This research paper identifies the significant gap in the market for an automated, real-time alert system that provides a solution that does not require manual engagement. In response, an LLM-based Smartwatch-Based Panic Alert System (SBPAS) is proposed to integrate into smartwatches that continuously monitor heart rate, motion, and location biometric signals. By applying advanced machine learning models, the system detects abnormal patterns consistent with panic or distress and automatically triggers alerts to emergency contacts and local authorities. This eliminates the need for manual intervention, offering a faster, more reliable response in critical situations. The significance of this solution lies in its ability to reduce response times, improve the likelihood of timely assistance, eliminate the chance of not being notified about an emergency, and close the existing technological gap in safety infrastructure, particularly in regions where crimes against individuals are prevalent.

关键词： Biometrics Heart rate Manuals Machine learning Real-time systems Time factors Reliability Biomedical monitoring Wearable devices Monitoring

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Experimental Demonstration of Hybrid LED-LD Based UOWC Link 2

Experimental Demonstration of Hybrid LED-LD Based UOWC Link

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2nd International Conference on Microwave, Optical and Communication engineering, ICMOCE 2023

作者： Krishna, Gopal Mathew, Jimson Santhanakrishnan, T. Gupta, Sumanta Indian Institute of Technology Patna Dept. of Electrical Engineering India Indian Institute of Technology Patna Dept. of Computer Science and Engineering India DRDO Naval Physical and Oceanographic Laboratory India

ISBN: (纸本)9798350321609

In this paper, we have designed and experimentally characterized a hybrid light emitting diode (LED) and laser diode (LD) based underwater optical wireless communication (UOWC) link, which can be suitable for providing high-speed optical connectivity between onshore and submerged systems. An LED-based system is efficient for short-range communication whereas an LD-based system is for long distances. In this paper, we have experimentally demonstrated the establishment of a hybrid LED-LD UOWC link at a data rate of 10 Mbps over a 2.5 m water channel using a return to zero on-off keying (RZ-OOK) modulation scheme using an FPGA-based transmitter and receiver. We have also used offline data processing to quantify the bit error rate (BER) performance as a function of received optical power for tap water and turbid water channels. For the tap water channel, we have achieved a BER as low as 3.5 ×10-6 at - 35.1 dBm received optical power, whereas for turbid water the achieved BER is 1.8 × 10-5 at -31. 6 dBm of received optical power in absence of air bubble. In turbid water (and tap water) channel in presence of air bubbles the minimum achievable BER is around 3 × 10-4 (3 × 10-4) for -31.5 dBm (-35.5 dBm) of received power. © 2023 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Latent Semantic Analysis based Real-world Application of Topic Modeling: A Review Study 2

Latent Semantic Analysis based Real-world Application of Top...

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2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022

作者： Gupta, Isha Chatterjee, Indranath Gupta, Neha Mriirs Faculty of Computer Applications Faridabad India Tongmyong University Dept. of Computer Engineering Busan Korea Republic of

ISBN: (纸本)9781665400527

Today, we are living in the digital world. Much information is available on the internet about| every topic. But merely the availability of information is not enough. There is a need for automated tools that can extract hidden patterns or topics from a large number of files or data. Topic modeling is one tool available in data mining that plays a significant role in finding those unknown topics. The paper's objective is to study the importance of topic modeling and discuss the various works done in this field. The author concludes the various fields where more work is required. © 2022 IEEE.

关键词： Semantics

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Towards Personalized Fitness with Multi-modal Wearable Heart Rate Monitors: A Proposal 6

Towards Personalized Fitness with Multi-modal Wearable Heart...

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6th International Conference on Vocational Education and Electrical engineering, ICVEE 2023

作者： Nugraha, Alfian Dwi Puspitaningayu, Pradini Hidayatullah, Rahmat Pramukantoro, Eko Sakti Widayaka, Parama Diptya Rochmawati, Naim State University of Surabaya Dept. of Informatics Engineering Surabaya Indonesia State University of Surabaya Dept. of Electrical Engineering Surabaya Indonesia Brawijaya University Faculty of Computer Science Malang Indonesia

ISBN: (纸本)9798350326642

Nowadays, the trend for home workouts is getting more and more popular. The growth of wearable fitness trackers from basic accelerometers, pedometers, pulse detectors, and ECGs also supports the advancement of personal fitness monitoring. Everyone has a distinct level of fitness, in theory. The heart rate, which is correlated with physical activity, such as sports, demonstrates how this organ functions. As the muscles work harder at a high intensity, the heart rate will also rise. This paper presents the design and implementation of a multimodal wearable heart rate monitoring system. The software is Android-based and is designed to be able to receive heart rate data sent by two different wearable heart rate monitors simultaneously using Bluetooth low-energy protocol. One uses an optical heart monitor and the other uses an electrocardiogram or ECG. The implementation also includes IoT for real-Time data acquisition and a web-based application for wider accessibility. The system is evaluated by collecting packets from two devices for 60 minutes. The results underscore the feasibility of the system in collecting users' heart rate data either using different devices. Furthermore, it serves as a foundation for future studies aiming to expand the personalization capabilities of wearable devices in healthcare and fitness. © 2023 IEEE.

关键词： Electrocardiograms

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5G User Equipment (UE) Positioning and Localization Estimation using Machine Learning

5G User Equipment (UE) Positioning and Localization Estimati...

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Electrical Electronics and Computing Technologies (ICEECT), International Conference on

作者： Sanket Survase Raman Diwan Kumari Nidhi Lal Shishupal Kumar Dept. of Computer Science and Engineering VNIT Nagpur Nagpur India Dept. of Computer Science and Engineering IIIT Nagpur Nagpur India

ISBN: (数字)9798350378092

ISBN: (纸本)9798350378108

The emergence of 5G technology has ushered in a new era of connectivity, making communications faster and cheaper. One of the main challenges of 5G networks is accuracy and efficiency, which are important for many applications such as driver less cars, smart cities and virtual reality. This research paper explores the integration of machine learning techniques to improve the accuracy and reliability of 5G infrastructure. The plan uses rich data generated by 5G networks, combining various parameters such as signal strength, flight time and angle of arrival. Machine learning algorithms are used to process this data and create good models for the correct location. The system is designed to adapt to dynamic and complex urban environments where traditional methods often encounter limitations. The main contribution of this research includes the development of a new machine learning-based distribution algorithm suitable for 5G networks, a comprehensive evaluation of performance comparison with the existing system, and evaluation of recommendations for feasibility and implementation. The results showed significant improvements in accuracy and reliability, demonstrating the potential of machine learning to revolutionize the 5G workplace.

关键词： Meters Solid modeling Accuracy Machine learning algorithms 5G mobile communication Smart cities Linear regression Refining Virtual reality Reliability

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Analyzing File Access Characteristics for Deep Learning Workloads on Mobile Devices

Analyzing File Access Characteristics for Deep Learning Work...

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Advances in Electrical engineering and computer Applications( AEECA), 2020 IEEE International Conference on

作者： Jeongha Lee Soojung Lim Hyokyung Bahn Dept. of Computer Engineering Ewha University Seoul Republic of Korea Dept. of Computer Engineering Ewha University Seoul Republic of Koera

ISBN: (纸本)9798350355260

Recent advances in artificial intelligence technologies have led to a significant increase in deep learning workloads on mobile devices. Given the limited resources of smartphones, much of the research in mobile deep learning has concentrated on offloading these workloads to edge or cloud servers. While computing resources are crucial, storage I/O remains a critical performance bottleneck for mobile devices, yet the file access characteristics of deep learning have not been thoroughly explored. This paper investigates the file access traces of deep learning workloads on mobile devices, comparing them to traditional workloads. The main findings include: 1) Write access constitutes 48-94% of total file accesses, aligning with conventional mobile apps but contrasting with most desktop applications; 2) Write access in mobile deep learning workloads exhibits repetitive long-loop patterns, offering insights for enhancing file cache performance; 3) Despite its prevalence, write access demonstrates low access skewness; 4) Frequency of file accesses proves more informative than recency in predicting re-access likelihood. The insights from this study are expected to guide the efficient management of future smartphone systems by addressing the unique file access dynamics of deep learning.

关键词： Deep learning Performance evaluation Electrical engineering Mobile applications Servers Artificial intelligence Smart phones

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Image inpainting for corrupted images by using the semi-super resolution GAN

arXiv

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arXiv 2024年

作者： Momen Tayefeh, Mehrshad Momen Tayefeh, Mehrdad Ghahramanie, S. AmirAli Ghafourian Dept. Computer Engineering Sharif University of Technology Tehran Iran Dept. Electrical and Computer Engineering University of Tehran Tehran Iran

Image inpainting is a valuable technique for enhancing images that have been corrupted. The primary challenge in this research revolves around the extent of corruption in the input image that the deep learning model must restore. To address this challenge, we introduce a Generative Adversarial Network (GAN) for learning and replicating the missing pixels. Additionally, we have developed a distinct variant of the Super-Resolution GAN (SRGAN), which we refer to as the Semi-SRGAN (SSRGAN). Furthermore, we leveraged three diverse datasets to assess the robustness and accuracy of our proposed model. Our training process involves varying levels of pixel corruption to attain optimal accuracy and generate high-quality images. © 2024, CC BY-NC-ND.

关键词： Gallium nitride

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