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Taxonomy of Technical Challenges in Digital Forensics 7

Taxonomy of Technical Challenges in Digital Forensics

引用

7th international conference on Image information processing, ICIIP 2023

作者： Kumari, Nisha Sharma, Tejpal Gupta, Anuj Kumar Dua, Gaurav Chandigarh Engineering College-CGC Landran Department of Computer Science & Engineering Mohali India Chitkara University Institute of Engineering & Technology Chitkara University Punjab Rajpura India CGC-College of Engineering Landran Department of Computer Science & Engineering Mohali India

ISBN: (纸本)9798350371406

Digital investigations face numerous challenges in today's landscape, particularly with the widespread adoption of cloud computing. Acquiring evidence stored in cloud environments raises concerns as criminals exploit and dispose of it easily. While some aspects of digital investigation remain unchanged, cloud computing also offers opportunities for supporting digital forensics and enhancing investigative capabilities. However, there is still a need for a formal classification of the challenges faced, and addressing cognitive biases source of error requires further attention. Current investigative techniques are limited, necessitating the proactive use of intelligent techniques like artificial intelligence. Understanding the real challenges in digital forensics is crucial due to factors such as increasing data volume, diverse technology platforms, and encryption. A holistic view of digital investigation emphasizes resilience, security, and forensic preparedness in combating heterogeneous adversarial threats. the convergence of data science and digital forensics presents both opportunities and challenges, requiring adaptation of big data analysis techniques. Cloud investigations pose unique technical, legal, and architectural challenges, demanding the development of new methods, tools, and standards. Effective testing relies on well-constructed and documented datasets, highlighting the need for reliable standards and best practices © 2023 IEEE.

关键词： Taxonomies

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Slice allocation of 5G network for smart grid with deep reinforcement learning ACKTR 7

Slice allocation of 5G network for smart grid with deep rein...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Zhong, Lijun Hu, Jingbo Shen, Haocong Xu, Chen Huang, Zhenyu Ren, Baoping State Grid Jiaxing Electric Power Supply Company Information and Communication Branch Jiaxing China Jiaxing Hengchuang Electric Power Group Co. Ltd. HuaChuang Information Technology Branch Jiaxing China

ISBN: (纸本)9781665478571

Smart grid is one of the representative applications for 5G network. In this scenario, different business types of smart grid have diverse requirements in service quality, isolation level, and maintenance management. Moreover, the quantity, location and distribution of 5G terminals lack a comprehensive prior description. To improve resource utilization efficiency and reduce the operating cost of power companies, real-time resource management for network slicing has become an urgent problem to be solved. In this paper, we propose a slice request allocation method for smart grid based on the framework of deep reinforcement learning. We innovatively encode the allocated and free resources with the slice request into a unified tensor, and then design the corresponding action and reward function. We employ the deep reinforcement learning ACKTR algorithm based on the actor-critic framework to find the optimal decision policy. the simulation experiments show that compared with the previous slice resource allocation methods based on Q-learning and Deep Dueling, our method can achieve better long-term rewards and effectively improve the utilization efficiency of 5G network for smart grid. © 2022 IEEE.

关键词： Deep learning

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Research on the application of computer vision in the police equipment : Auto-targeting through YOLOv5s as an example 7

Research on the application of computer vision in the police...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Liu, Ruixi Zhang, Wanqiu Xiao, Yuxin Yang, Yinan Chongqing Police College Department of Information Security Chongqing China Chongqing Police College Department of Investigation Chongqing China

ISBN: (纸本)9781665478571

the previous automatic targeting techniques are prone to deviation and low robustness. To address the problem that physiological factors are liable to misfire and miscalculation when police shoot in critical situations, an automatic target recognition assistance system based on a lightweight and efficient YOLOv5s network is proposed. the system first introduces a lightweight feature-enhanced representation module to detect and classify targets according to real-time images captured by RGB cameras, which reduces the false detection rate of the network. then, the user selects a controller based on the system's labeling of the target Head and Cavity. Finally, the feature-enhanced representation module extracts higher resolution maps, which helps in tiny target detection. Experiments show that the system maintains the lightness and efficiency of the YOLOv5s network. It achieves an average detection accuracy of 83.3% for Head and Cavity, which meets the performance requirements of AI models in police application scenarios and provides a theoretical basis for future computer vision applications in police equipment development. © 2022 IEEE.

关键词： Law enforcement

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Comparative Analysis of Different hand gestures Detection and Recognition Techniques 7

Comparative Analysis of Different hand gestures Detection an...

引用

7th international conference on Communication and Electronics Systems, ICCES 2022

作者： Kumar, Rajat Sharma, Puneet Verma, Bindu Delhi Technological University Department of Information Technology Delhi India

ISBN: (数字)9781665496346

ISBN: (纸本)9781665496346

Hand Gesture is a wide technology aspect of computer Science. It provides a good technology tool for human computer interaction. With some mathematical algorithms, Humans can interact with computers without using any mechanical devices. Also for deaf and mute people, communication hindrance can be remediate. Hand gesture is the most expressive and frequent among any type of expression language. It can put up sign language recognition to a new level. this paper is oriented towards a comparative analysis of different types of hand gesture Detection and recognition methods. In addition, the result and problems with different approaches are tabulated. these have different gesture types and so different number of gesture classes. Most of these methods produce accuracy of 90-95%. the best accuracy achieved for static hand gestures is 95.7% which is based on the ML algorithm. © 2022 IEEE.

关键词： Palmprint recognition

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Self-Supervised Point Cloud Learning in Few-Shot Scenario by Point Up-Sampling and Mutual information Neural Estimation 7

Self-Supervised Point Cloud Learning in Few-Shot Scenario by...

引用

7th international conference on computer and Communication Systems, ICCCS 2022

作者： Li, Jiawei Huang, Yunan Lei, Yunqi Xiamen University Department of Computer Science and Technology Xiamen China

ISBN: (数字)9781665450607

ISBN: (纸本)9781665450607

Point cloud data is hard to obtain and time-consuming to be labelled. Self-supervised methods can utilize data without label, but it still needs large amount of data. the key to self-supervised methods lies in the design of pretext tasks. In this work, we propose a new self-supervised pretext task in few-shot learning scenario to further alleviate the data scarcity problem. Our self-supervised method learns by training the network to restore the original point cloud from the down-sampled point cloud. Although our point up-sampling pretext task as a kind of reconstruction task can ensure the learned representation contains sufficient information, it cannot guarantee its distinguishability. thus, we introduce a Mutual information Estimation and Maximization task to increase the distinguishability of the learned representation. Classification and segmentation results have shown that our method can learn efficient feature and increase the performance of down-stream models. © 2022 IEEE.

关键词： Supervised learning

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An EMD with Masked WVDs for Cross-terms Reduction in Non-stationary Signals 7

An EMD with Masked WVDs for Cross-terms Reduction in Non-sta...

引用

7th international conference on Digital Arts, Media and technology, DAMT 2022 and 5th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications Engineering, NCON 2022

作者： Kuptametee, Chanin Aunsri, Nattapol Mae Fah Luang University School of Information Technology Thailand Computer and Communication Engineering for Capacity Building Research Center Mae Fah Luang University Thailand

ISBN: (纸本)9781665495103

Signals commonly found in real-world applications are non-linear, multi-component, and non-stationary. For simplicity, they are analyzed and processed in time-frequency (TF) domain. Wigner-Ville distribution (WVD) is a method that provides time-frequency representation (TFR) of a signal with high-sharpness resolutions. However, its bilinear nature causes false frequency components called 'cross-terms' to occur between the real components of the multi-component signal. WVDs of mono-component but non-linear signals also suffer from cross-terms problem. Empirical mode decomposition (EMD) is a data-driven algorithm used to decompose a multi-component signal into subcomponents called intrinsic mode functions (IMFs). this paper applies WVD masking for each extracted signal components obtained from EMD to ensure that the cross-terms will be suppressed, especially if there are non-linear IMFs. Also, masked WVDs using different linear TF methods are also investigated to obtain the comparative results. the results revealed that by using the masked WVDs to EMD, the cross-terms were satisfactory removed. © 2022 IEEE.

关键词： Empirical mode decomposition

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MorphUz: Morphological Analyzer for the Uzbek Language 7

MorphUz: Morphological Analyzer for the Uzbek Language

引用

7th international conference on computer Science and Engineering, UBMK 2022

作者： Abdurakhmonova, Nilufar Alisher, Ismailov Sayfulleyeva, Rano National University of Uzbekistan Uzbek Linguistics Department Tashkent Uzbekistan Andijan Machine Building Institute Innovative Educational Department Andijan Uzbekistan

ISBN: (数字)9781665470100

ISBN: (纸本)9781665470100

the Uzbek language is an agglutinative language in that words are derived from stems (root) by concatenating affixes. this property makes a large number of combinations of morphemes, and greatly increases the word-vocabulary size. therefore, words are split into certain sub-word units and applied to text and speech processing applications. Proper sub-word units not only provide high coverage and smaller lexicon size, but also provide semantic and syntactic information that is necessary for downstream applications. this paper discusses a morphological analyzer tool for natural language processing and machine learning purpose. the tool named MorphUz, which can split a text of words into a sequence of morphemes. Morphological analyzer is one of the main part of the natural language processing. MorphUz analyzer is an open-source morphological analyzer for the Uzbek language. the MorphUz analyzer is available as a website for exploration. MorphUz analyzer implements the morphology of the Uzbek language following a two-level approach using stemming and suffix analyzer. the implementation of MorphUz analyzer done by using PHP and JavaScript scripts and MySQL database. © 2022 IEEE.

关键词： Speech processing

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Investigating Electromagnetic Acoustic Emission Signal processing Based on Optimized Variational Mode Decomposition 7

Investigating Electromagnetic Acoustic Emission Signal Proce...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Li, Qiuyue Lai, Yushu Yang, Chenglong Cao, Difei Chongqing Three Gorges University School of Electronic & Information Engineering Chongqing China North China University of Science and Technology College of Artificial Intelligence Tangshan China

ISBN: (纸本)9781665478571

Electromagnetic acoustic emission (EMAE) signal is a kind of faint signal and susceptible to noise interference. In order to obtain pure and representative impairment signal in metal devices, which is crucial to the subsequent impairment identification and early warning, an optimized VMD method is implemented. Moreover, to realize the denoising of EMAE signal properly, we compare common denoising ways in the simulation and real collected signal. Aiming at the serious influence of the decomposed level K and penalty factor α, and uncertainties of parameter selection in the variational mode decomposition (VMD), we utilize genetic algorithm (GA) for optimizing VMD, namely GAVMD. Firstly, this approach views sample entropy as fitness function, and global minimum fitness value is used as optimization objective to screen out the best VMD parameter combination. then, a series of intrinsic mode functions (IMFs) are obtained, and the denoising signals are reconstructed according to the correlation coefficients. the results show that the improved GAVMD algorithm has the better effect in the suppression of non-stationary signal noise, with SNR of 18.4684 and RMSE of 0.0017. In addition, we also develop the reservoir computing modeling approach to predict the noise-reduced data to further validate the superiority of GAVMD. © 2022 IEEE.

关键词： Genetic algorithms

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Blockchain in HRM:Application and Future Perspective 7

Blockchain in HRM:Application and Future Perspective

引用

7th international conference on Computing, Communication and Security, ICCCS 2022 and 2022 4th international conference on Big Data and Computational Intelligence, ICBDCI 2022

作者： Meharwal, Namrata Tyagi, Shagun Kumar, Rajesh Joshi, Kapil Rastogi, Neha Hussien, Nadia Mahmood UPES Department of CSE Dehradun India School of Management Graphic Era Hill University Dehradun India Meerut Institute of Technology Department of CSE Meerut India Uttaranchal Institute of Technology UttaranchalUniversity Department of CSE Dehradun India Uttaranchal Institute of Management Uttaranchal University Dehradun India Mustansiriyah University College of Science Computer Science Department Baghdad Iraq

ISBN: (纸本)9798350309904

To effectively perform some of the basic HR activities, HR professionals are equipping themselves with cutting-edge technologies. HR staff deal with some of the financial transactions with the highest volume in a business. Utilizing blockchain technology can help stop internal and external hacks of private data. We looked at articles from the Scopus and Web of Science databases that were published between 2018 and 2022. Literature review shows that as more companies suffer from data breaches, it is critical that steps be taken to prevent fraud and maintain security. Blockchain technology may be used to help a void internal and external hack of private data. For aerospace and defense firms, Lockheed Martin employs it for risk management and software security. the use of blockchain technology offers the ability to automate many manual procedures and speed up processing. © 2022 IEEE.

关键词： Blockchain

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Remote sensing image registration based on fusion of local features and self-similar features 7

Remote sensing image registration based on fusion of local f...

引用

7th international conference on Intelligent Informatics and Biomedical Sciences, ICIIBMS 2022

作者： Song, Zhili Li, Zhixiang Shanghai Institute of Technology College of Computer Science and Information Engineering Shanghai China

ISBN: (数字)9781665482295

ISBN: (纸本)9781665482295

Remote sensing image registration is the core problem of further processing of remote sensing images, and has been widely used in urban development planning, ecological environment monitoring, geographical change detection and other fields. In this paper, a remote sensing image registration method based on fusion of local features and self-similar features is proposed. Firstly, the self-similar features are generated by the self-similar module, and then the local convolution features and the self-similar features are fused to reduce the influence of background clutter-induced distraction on the extracted features. Moreover, a improved parameter regression model that filters false matches is used to output the affine transformation parameters. Finally, the image to be registered can be transformed by the affine transformation parameters to achieve the intent of registration. the qualitative and quantitative assessments show that this method improves the registration accuracy of remote sensing image registration compared to the comparison methods. © 2022 IEEE.

关键词： Urban growth

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