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3rd International Conference on Intelligent Cybernetics technology and Applications, ICICyTA 2023

作者： Singh, Hakam Witarsyah, Deden Misra, Alok Tiwari, Raj Gaurang Chitkara University School of Engineering and Technology Department of Computer Science and Engineering Himachal Paradesh Baddi India Telkom University School of Industrial and System Engineering Information System Departement Bandung Indonesia Lovely Professional University School of Computer Application Punjab Phagwara India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350394559

Due to its many applications in a variety of domains, including clustering, cloud computing, and power systems, metaheuristic algorithms have attracted a lot of interest from the scholarly community. By using their self-explorative and adaptive processes, these algorithms provide certain benefits over conventional methods. One well-known metaheuristic approach is effective in resolving optimization problems with constraints and without constraints. This technique was inspired by nature, notably the echolocation ability of bat species. The Bat Algorithm (BA) makes use of a powerful search mechanism to provide the best results when compared to other algorithms of the same class. The theoretical underpinnings of the BA are explored in depth in this research, along with several changes and advancements that have improved its functionality. These enhancements include adjustments to search tactics as well as other developments. The report also thoroughly examines how the BA may be used across a variety of fields, demonstrating its competence and adaptability. The BA has been effectively used in several real-world applications, from cloud computing to clustering, and each one is carefully investigated. The study also offers a thoughtful examination of the BA's possible advancements and future possibilities. It also entails investigating novel modifications and tactics that might improve its effectiveness in handling challenging optimization issues. This study seeks to direct practitioners and academics toward more effective and efficient metaheuristic algorithms, thereby stimulating improvements in optimization approaches. It does this by summarising the present state of the BA and imagining its future development. © 2023 IEEE.

关键词： Cloud computing

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DarkSAM: Fooling Segment Anything Model to Segment Nothing 38

DarkSAM: Fooling Segment Anything Model to Segment Nothing

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38th Conference on Neural information Processing systems, NeurIPS 2024

作者： Zhou, Ziqi Song, Yufei Li, Minghui Hu, Shengshan Wang, Xianlong Zhang, Leo Yu Yao, Dezhong Jin, Hai National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Cluster and Grid Computing Lab China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China School of Computer Science and Technology Huazhong University of Science and Technology China School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Information and Communication Technology Griffith University Australia

Segment Anything Model (SAM) has recently gained much attention for its outstanding generalization to unseen data and tasks. Despite its promising prospect, the vulnerabilities of SAM, especially to universal adversarial perturbation (UAP) have not been thoroughly investigated yet. In this paper, we propose DarkSAM, the first prompt-free universal attack framework against SAM, including a semantic decoupling-based spatial attack and a texture distortion-based frequency attack. We first divide the output of SAM into foreground and background. Then, we design a shadow target strategy to obtain the semantic blueprint of the image as the attack target. DarkSAM is dedicated to fooling SAM by extracting and destroying crucial object features from images in both spatial and frequency domains. In the spatial domain, we disrupt the semantics of both the foreground and background in the image to confuse SAM. In the frequency domain, we further enhance the attack effectiveness by distorting the high-frequency components (i.e., texture information) of the image. Consequently, with a single UAP, DarkSAM renders SAM incapable of segmenting objects across diverse images with varying prompts. Experimental results on four datasets for SAM and its two variant models demonstrate the powerful attack capability and transferability of DarkSAM. Our codes are available at: https://***/CGCL-codes/DarkSAM. © 2024 Neural information processing systems foundation. All rights reserved.

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On Big Data Forensic and Forensic Cloud Environment

On Big Data Forensic and Forensic Cloud Environment

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2022 International Conference on Smart Applications, Communications and Networking, SmartNets 2022

作者： Tabona, Oteng Ramokapane, Kopo M. Maupong, Thabiso M. Higher Colleges of Technology Faculty of Computer and Information Systems Abu Dhabi United Arab Emirates University of Bristol Department of Computer Science Bristol United Kingdom Botswana International University of Science and Technology Department of Computer Science and Information System Palapye Botswana

ISBN: (纸本)9781665487580

The number of electronic devices involved in cyber related crimes has increased significantly in the last few years. This is primarily due to advancements in technology and increased accessibility to devices. This poses significant challenges with respect to forensic investigations as investigators are faced with processing huge volumes of data from various sources within a limited time. Due to the urgency, frequency, and magnitude of some cases, investigators may miss deadlines, and crucial leads. In this paper, we consider these above stated challenges and propose a new definition for big data forensics, which recognises the time aspect and variety of sources when carrying our digital forensics. This definition will help digital forensic tool designers consider these critical aspects and design comprehensive tools to combat the limitations of the current state-of-the-art. We review an existing tool, the Forensic Cloud Environment (FCE), against the proposed definition. We show how its design leverages the power of Hadoop Distributed File system (HDFS), HBase, and MapReduce to provide a comprehensive solution for big data forensics. In conclusion, we provide an argument for FCE as a solution for resolving big data forensic challenges based on general Scientific Working Group on Digital Evidence (SWGDE) forensic principles. © 2022 IEEE.

关键词： Big data

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The Influence of Digital Financial Literacy on Interest in Investing in the Capital Market of Millennial Generation Students 1

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4th International Conference on Inventive Computation and information Technologies, ICICIT 2022

作者： Gaol, Ford Lumban Christopher Dermawan, Gerry Rafif, Muhammad Resnandya Rubianto, Rully Matsuo, Tokuro Doctor of Computer Science Binus Graduate Program Jakarta Indonesia School of Information System Bina Nusantara University Alam Sutera Indonesia Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (数字)9789811974021

ISBN: (纸本)9789811974014

In today's environment, financial knowledge is vital and should be possessed by everyone. Numerous people are financially disadvantaged as a result of the COVID-19 pandemic. This serves as a reminder of the critical nature of financial investment in the future. However, many Indonesians, particularly students, are still unfamiliar with capital market investing. In reality, investing in the stock market can provide a variety of benefits, including financial security, capital appreciation, and passive income. Financial literacy concerns can result in a lack of financial awareness among pupils. Indeed, financial literacy is widely available online and can be accessed at any time and from any location. We employed a quantitative method with a non-experimental research design for this study. A questionnaire survey is used to obtain data. The goal of this study is to determine whether there is a correlation between student interest in capital market investment and their digital financial literacy. As a result, extensive action is required to increase student interest in the capital market, which is precisely what this study wants to do. According to our findings, students who have access to digital financial and investment information have increased their financial literacy and developed a greater interest in investing in the capital market. Individuals are also encouraged by social media trends to try their hand at investing in the stock market. Additionally, students prefer to invest in stocks and mutual funds over other investing options. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Investments

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Nonlinear Deep Subspace Network for Micro-expression Recognition 3

Nonlinear Deep Subspace Network for Micro-expression Recogni...

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3rd Workshop on Facial Micro-Expression: Advanced Techniques for Multi-Modal Facial Expression Analysis, FME 2023

作者： Feng, Weijia Xu, Manlu Chen, Yuanxu Wang, Xiaofeng Guo, Jia Dai, Lei Wang, Nan Zuo, Xinyu Li, Xiaoxue College of Computer and Information Engineering Tianjin Normal University Tianjin China Ping An Technology Shenzhen China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin China

ISBN: (纸本)9798400702853

Deep learning (DL) models have been widely studied in the field of micro-expression recognition (MER). However, micro-expressions (MEs) suffer from small number of samples and difficulty in extracting subtle and transient features, resulting in limited improvement in the recognition performance. In addition, DL models are prone to overfitting problems and are difficult to extract discriminative features of facial actions from ME images or sequences. To address these issues, we propose a MER method that combines a nonlinear deep subspace network and optical flow features. Firstly, facial motion features are captured using optical flow computation, and then the optical flow features are input into a kernel principal component analysis network (KPCANet) to further learn deeper spatio-temporal features. Finally, a linear support vector machine (SVM) is used for ME classification. Experiments conducted on four public spontaneous ME datasets including SMIC, CASME, CASME II and SAMM validate the effectiveness of the proposed method. The experimental results demonstrate that the proposed method achieves even better recognition performance compared to existing state-of-the-art MER methods. © 2023 ACM.

关键词： Principal component analysis

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Analyzing Code Injection Attacks on Applications of Android Devices and Emulator 9

Analyzing Code Injection Attacks on Applications of Android ...

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9th IEEE International Conference on Computing, Engineering and Design, ICCED 2023

作者： Erfina, Adhitia Hidayat, Rahmat Rizaldi, Rafli Radya Puput Maulana, Riko Sembiring, Falentino Nusa Putra University Faculty of Engineering Computing and Design Departement of Infomation System Sukabumi Indonesia Budi Luhur University Master of Computer Science Faculty of Information Technology Jakarta Indonesia

ISBN: (纸本)9798350370126

The Android operating system released by Google in 2007 has experienced very significant development. In 2019, the number of Android application users reached 2.5 billion. One of the contributing factors is the nature of the android application, which is very flexible and easy to install. Users can download APK files on the internet. Generally, APK files are stored in archive format, so they are pretty easy to manage. However, APK files may be used to spread malware behind this convenience. This study aims to provide an overview of the process of planting malware/backdoor on Android applications and how to prevent it. This study initiated the injection of malicious code on five android applications, namely WhatsApp, Telegram, DroidCam, Fifa Mobile, and Tokopedia. According to the results, four applications were successfully injected, while one application failed. The failure most likely occurred as a result of the application's source code being obfuscated. Obfuscation is therefore strongly advised for Android applications to prevent code injection that could potentially lead to malware insertion. © 2023 IEEE.

关键词： Android (operating system)

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The Effect of E-Commerce on Increasing Consumption Behavior During a Pandemic 4th

The Effect of E-Commerce on Increasing Consumption Behavior ...

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4th International Conference on Inventive Computation and information Technologies, ICICIT 2022

作者： Gaol, Ford Lumban Tompunu, Sherina Gloria Larissa, Jessica Adine Wijaksana, Arista Prajnawira, Ferdianto Matsuo, Tokuro Binus Graduate Program—Doctor of Computer Science Jakarta Indonesia School of Information System Bina Nusantara University Alam Sutera Indonesia Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (纸本)9789811974014

The rapid development of technology and ease of information today greatly affects all aspects of life. During the COVID-19 pandemic, technology played an important role in maintaining community activities continued smoothly despite being hampered by several health policies during the COVID-19 pandemic. Many phenomena develop with new technologies in several fields, one in the economic field is e-commerce. E-commerce is a site that makes it easier for buyers to get the goods desired by the community, as well as the various interesting promos that are the attractiveness of the community to constantly shop in e-commerce so that the community applies consumptive behavior. So that the problem that will be discussed in this study is the development of e-commerce technology that affects people’s behavior in shopping which tends to be consumptive and hedonic. The purpose of this study is to determine the impact or effect of the use of e-commerce on consumptive behavior during the pandemic period and provide an overview of the potential regarding e-commerce in the future. This research method is quantitative. The data collection technique used for this study is to use a questionnaire. Thus, this research is expected to minimize the negative impacts that can be caused by the increasing consumptive behavior of society during the pandemic and provide wise e-commerce use. The results of this study can be seen from calculations using a formula that respondents tend to be more extravagant during the pandemic and for future potential, respondents will certainly enjoy the convenience provided by e-commerce. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： COVID-19

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Exploring Global and Local information for Anomaly Detection with Normal Samples

Exploring Global and Local Information for Anomaly Detection...

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Xu, Fan Wang, Nan Zhao, Xibin School of Computer Science and Technology University of Science and Technology of China Hefei230026 China School of Software Beijing Jiaotong University Beijing100044 China Key Laboratory for Information System Security Beijing100084 China

ISBN: (纸本)9798350337020

Anomaly detection aims to detect data that do not conform to regular patterns, and such data is also called outliers. The anomalies to be detected are often tiny in proportion, containing crucial information, and are suitable for application scenes like intrusion detection, fraud detection, fault diagnosis, e-commerce platforms, et al. However, in many realistic scenarios, only the samples following normal behavior are observed, while we can hardly obtain any anomaly information. To address such problem, we propose an anomaly detection method GALDetector which is combined of global and local information based on observed normal samples. The proposed method can be divided into a three-stage method. Firstly, the global similar normal scores and the local sparsity scores of unlabeled samples are computed separately. Secondly, potential anomaly samples are separated from the unlabeled samples corresponding to these two scores and corresponding weights are assigned to the selected samples. Finally, a weighted anomaly detector is trained by loads of samples, then the detector is utilized to identify else anomalies. To evaluate the effectiveness of the proposed method, we conducted experiments on three categories of real-world datasets from diverse domains, and experimental results show that our method achieves better performance when compared with other state-of-the-art methods. © 2023 IEEE.

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Automated Grading of Breast Cancer Histopathology Images Using Multilayered Autoencoder

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computers, Materials & Continua 2022年第5期71卷 3407-3423页

作者： Shakra Mehak M.Usman Ashraf Rabia Zafar Ahmed M.Alghamdi Ahmed S.Alfakeeh Fawaz Alassery Habib Hamam Muhammad Shafiq Knowledge Unit of System and Technology University of Management&TechnologySialkot Campus51310Pakistan Department of Computer Science University of Management and TechnologySialkot Campus51310Pakistan Faculty of Computing and Technology University of Engineering&TechnologyNarowal51610Pakistan College of Computer Science and Engineering University of Jeddah21493Saudi Arabia Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaifSaudi Arabia Faculty of Engineering Moncton UniversityNBE1A3E9Canada Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

Breast cancer(BC)is the most widely recognized cancer in women *** 2018,627,000 women had died of breast cancer(World Health Organization Report 2018).To diagnose BC,the evaluation of tumours is achieved by analysis of histological *** present,the Nottingham Bloom Richardson framework is the least expensive approach used to grade BC *** contemplate three elements,*** count,*** formation,and *** atypia,which is a laborious process that witness’s variations in expert’s ***,some algorithms have been proposed for the detection of mitotic cells,but nuclear atypia in breast cancer histopathology has not received much *** atypia analysis is performed not only to grade BC but also to provide critical information in the discrimination of normal breast,non-invasive breast(usual ductal hyperplasia,atypical ductal hyperplasia)and pre-invasive breast(ductal carcinoma in situ)and invasive breast *** proposed a deep-stacked multi-layer autoencoder ensemble with a softmax layer for the feature extraction and classification *** classification results show the value of the multilayer autoencoder model in the evaluation of nuclear *** proposed method has indicated promising results,making them more fit in breast cancer grading.

关键词： Breast cancer nuclear atypia autoencoder

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Utilization of Waste Banks system in the COVID-19 Pandemic 4th

Utilization of Waste Banks System in the COVID-19 Pandemic

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4th International Conference on Inventive Computation and information Technologies, ICICIT 2022

作者： Pradanang, Riyan Aditya, Bima Rayhan, Adhitya Winarlie, Michael Adrian Gaol, Ford Lumban Matsuo, Tokuro School of Information System Bina Nusantara University Alam Sutera Tangerang Indonesia Computer Science Binus Graduate Program Jakarta Indonesia Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (纸本)9789811974014

People’s perspectives and behaviors altered in a variety of ways during the pandemic period, most notably in areas related to health, environment, and most notably waste management. Many people still prefer to work from home and this in turn leads to a large accumulation of garbage without having any proper means of disposal. As a result, the garbage area will serve as a breeding ground for illness. Garbage is usually composed of a residual waste generated from a product or object that has outlived its useful life, but can still be recycled into a valuable item. On this basis, the solution is to use a waste bank;it is a collection point for sorted garbage. It is claimed that using a waste bank can help in preventing the garbage accumulation. The main purpose of this study is to determine the contribution of the waste bank to end garbage accumulation. The information gathered through a review of the literature and direct interviews with multiple informants. According to the findings of the literature review, waste banks can provide a variety of benefits to users, as well as the community and surrounding environment. The proposed research study's findings show that the changes in community activity patterns contribute to an increase in garbage, and that the community plays an important role in waste control. From the performed research study, it is evident that m any individuals are interested about garbage banks and their benefits based on this presumption. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Recycling

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