检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Saxena, Deepika Swain, Smruti Rekha Kumar, Jatinder Patni, Sakshi Gupta, Kishu Singh, Ashutosh Kumar Lindenstruth, Volker Division of Information Systems University of Aizu Aizuwakamatsu9650006 Japan Department of Computer Science The University of Economics and Human Sciences Warsaw01-043 Poland Department of Computer Applications National Institute of Technology Kurukshetra Kurukshetra136119 India Department of Computing Gachon University Seongnam461701 Korea Republic of Department of Computer Science and Engineering National Sun Yat-sen University Kaohsiung804 Taiwan Department of Computer Science and Engineering Indian Institute of Information Technology Bhopal Bhopal462003 India Department of Computer Science and Engineering Goethe University Frankfurt60438 Germany

Secure resource management (SRM) within a cloud computing environment is a critical yet infrequently studied research topic. This paper provides a comprehensive survey and comparative performance evaluation of potential cyber threat countermeasure strategies that address security challenges during cloud workload execution and resource management. Cybersecurity is explored specifically in the context of cloud resource management, with an emphasis on identifying the associated challenges. The cyber threat countermeasure methods are categorized into three classes: defensive strategies, mitigating strategies, and hybrid strategies. The existing countermeasure strategies belonging to each class are thoroughly discussed and compared. In addition to conceptual and theoretical analysis, the leading countermeasure strategies within these categories are implemented on a common platform and examined using two real-world virtual machine (VM) data traces. Based on this comprehensive study and performance evaluation, the paper discusses the trade-offs among these countermeasure strategies and their utility, providing imperative concluding remarks on the holistic study of cloud cyber threat countermeasures and secure resource management. Furthermore, the study suggests future methodologies that could effectively address the emerging challenges of secure cloud resource management. © 2025, CC BY-SA.

关键词： Cloud security

来源：评论

学校读者我要写书评

暂无评论

A Survey of Lung Nodules Detection and Classification from CT Scan Images

引用

computer Systems science & Engineering 2024年第6期48卷 1483-1511页

作者： Salman Ahmed Fazli Subhan Mazliham Mohd Su’ud Muhammad Mansoor Alam Adil Waheed Faculty of Computing and Technology IQRA UniversityIslamabad44000Pakistan Faculty of Engineering and Computer Science National University of Modern LanguagesIslamabad44000Pakistan Faculty of Computing and Informatics Multimedia UniversityCyberjaya63100Malaysia Faculty of Computing Riphah International UniversityIslamabad44000Pakistan Department of Information Sciences Division of Sciences and TechnologyUniversity of EducationLahore54770Pakistan

In the contemporary era,the death rate is increasing due to lung ***,technology is continuously enhancing the quality of *** improve the survival rate,radiologists rely on Computed Tomography(CT)scans for early detection and diagnosis of lung *** paper presented a detailed,systematic review of several identification and categorization techniques for lung *** analysis of the report explored the challenges,advancements,and future opinions in computer-aided diagnosis CAD systems for detecting and classifying lung nodules employing the deep learning(DL)*** findings also highlighted the usefulness of DL networks,especially convolutional neural networks(CNNs)in elevating sensitivity,accuracy,and specificity as well as overcoming false positives in the initial stages of lung cancer *** paper further presented the integral nodule classification stage,which stressed the importance of differentiating between benign and malignant nodules for initial cancer ***,the findings presented a comprehensive analysis of multiple techniques and studies for nodule classification,highlighting the evolution of methodologies from conventional machine learning(ML)classifiers to transfer learning and integrated ***,while accepting the strides formed by CAD systems,the review addressed persistent challenges.

关键词： Lung nodules computed tomography scans lung cancer deep learning

来源：评论

学校读者我要写书评

暂无评论

Cryptographically Secure Pseudo-Random Number Generation (CS-PRNG) Design using Robust Chaotic Tent Map (RCTM)

arXiv

引用

arXiv 2024年

作者： Irfan, Muhammad Khan, Muhammad Asif Division of Information and Computing Technology College of Science and Engineering Hamad Bin Khalifa University Qatar Foundation Doha Qatar Department of Computer Engineering University of Engineering and Technology Taxila47050 Pakistan

Chaos, a nonlinear dynamical system, favors cryptography due to their inherent sensitive dependence on the initial condition, mixing, and ergodicity property. In recent years, the nonlinear behavior of chaotic maps has been utilized as a random source to generate pseudo-random number generation for cryptographic services. For chaotic maps having Robust chaos, dense, chaotic orbits exist for the range of parameter space-the occurrence of chaotic attractors in some neighborhoods of parameter space and the absence of periodic windows. Thus, the robust chaotic map shows assertive chaotic behavior for larger parameters space with a positive Lyapunov exponent. This paper presents a novel method to generate cryptographically secure pseudo-random numbers (CSPRNG) using a robust chaotic tent map (RCTM). We proposed a new set of equations featuring modulo and scaling operators that achieve vast parameter space by keeping chaotic orbit globally stable and robust. The dynamic behavior of the RCTM is studied first by plotting the bifurcation diagram that shows chaotic behavior for different parameters, which the positive Lyapunov exponent verifies. We iterated the RCTM to generate pseudo-random bits using a simple thresholding method. Various statistical tests are performed that ascertain the randomness of generated secure pseudo-random bits. It includes NIST 800-22 test suite, ENT statistical test suite, TestU01 test suite, key space analysis, key sensitivity analysis, correlation analysis, histogram analysis, and differential analysis. The proposed scheme has achieved larger key space as compared with existing methods. The results show that the proposed PRBG algorithm can generate CSPRNG. © 2024, CC BY-NC-ND.

关键词： Random number generation

来源：评论

学校读者我要写书评

暂无评论

Design of Key-dependent S-Box using Chaotic Logistic Map for IoT-Enabled Smart Grid Devices

Design of Key-dependent S-Box using Chaotic Logistic Map for...

引用

Workshop on Smart Grid and Renewable Energy (SGRE)

作者： Muhammad Irfan Muhammad Asif Khan Gabriele Oligeri Division of Information and Computing Technology (ICT) College of Science and Engineering (CSE) Hamad Bin Khalifa University (HBKU) Doha Qatar Department of Computer Engineering University of Engineering and Technology Taxila Pakistan

In the era of pervasive computing, a generation of lightweight ciphers was needed to provide near-optimal security; officially, NIST announced the standard lightweight cryptographic primitive. The newly announced standard, ASCON, is based on a 5-bit input and 5-bit output Substitution Box (S-box). This paper proposes a key-dependent S-box methodology for small-size S-box for Internet of Things (IoT) devices widely used in many applications such as Smart Grids, healthcare, etc. We aided this study with the chaotic logistic map to generate a robust S-box. The key-dependent S-box can add an extra layer of security to the cryptosystem specifically for lightweight devices at the minimal cost of generation time of a new S-box. We have investigated the proposed methodology with cryptographic properties of S-box, such as Differential Probability (DP), Linear Probability (LP), Nonlinearity, Strict Avalanche Criteria (SAC), Boomerang Connectivity Table (BCT), Key-space analysis, and implementation on Arduino. We also compared the proposed methodology with other state-of-the-art (SOTA) 5 – bit input and output S-boxes. Experimental results witness the robustness of the proposed study.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Smart and Secure Blockchain-based Healthcare System Using Deep Q-Learning 7

Smart and Secure Blockchain-based Healthcare System Using De...

引用

7th IEEE World Forum on Internet of Things, WF-IoT 2021

作者： Al-Marridi, Abeer Z. Mohamed, Amr Erbad, Aiman Guizani, Mohsen Qatar University College Engineering Department of Computer Science and Engineering Qatar College of Science and Engineering Hamad Bin Khalifa University Division of Information and Computing Technology Qatar

ISBN: (纸本)9781665444316

Healthcare is one of the top priorities in modern society to provide better health facilities. Therefore, investments in health care systems increased rapidly, aligned with the population growth rate. Besides, the data generated from the health sectors is incomparable with the amount of data generated in other industries. Therefore, managing data processing and sharing between various healthcare stakeholders is essential. Blockchain is an emerging technology used heavily in various domains, including the healthcare sector, to facilitate secure data sharing. However, mapping the content requirements with the blockchain's configuration was not addressed, especially when addressing security, delays, and cost in healthcare systems. This paper proposes a blockchain-based intelligent Healthcare system (BC-iHealth) to address the mapping between the blockchain entities' needs with the blockchain's configuration while maximizing the security and minimizing the overall delay and cost. The optimization model is formulated as a Markov Decision Process (MDP) and solved intelligently using a Deep Q-Learning approach. Simulation results confirm that the Deep Q-Learning optimizes the BC-iHealth system and outperforms two benchmark strategies: random selection and exhaustive search. © 2021 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

A Blockchain-Based Distributed Collaborative Sensing and Spectrum Access Approach for Consumer Electronics

引用

IEEE Transactions on Consumer Electronics 2025年

作者： Peng, Yuhuai Li, Yuan Guo, Yu Zhang, Dawei Khan, Fazlullah Alturki, Ryan Alshawi, Bandar Northeastern University College of Computer Science and Engineering Shenyang110819 China Zhiyuan Research Institute Xihu District Hangzhou China Zhengzhou University School of Computer and Artificial Intelligence Henan Zhengzhou450001 China University of Nottingham Ningbo China School of Computer Science Faculty of Science and Engineering Zhejiang Ningbo315104 China KKR and KSR Institute of Technology and Sciences Department of Computer Science and Engineering Andhra Pradesh Guntur India Division of Research and Development Lovely Professional University Phagwara India University Centre of Research and Development Chandigarh University Mohali India Umm Al-Qura University Department of Software Engineering College of Computing Makkah Saudi Arabia Umm Al-Qura University College of Computing Department of Computer and Network Engineering Makkah Saudi Arabia

Cognitive radio (CR) provides key technical support for the seamless communication of consumer electronic (CE) devices through distributed cooperative sensing and spectrum access. However, its openness and dynamic nature introduce potential security risks and challenges. Due to the openness of wireless communication, spectrum sensing and access are vulnerable to malicious attacks, and resource-constrained devices cannot effectively implement artificial intelligence (AI)-driven encryption and access control strategies. To address these limitations, this study proposes a blockchain-based distributed collaborative sensing method for CE devices. In the proposed method, after sensing, the smart contracts verify node legitimacy using the ring signature method. The malicious users are rejected by the outlier detection method, which improves the collaborative anti-interference ability. In addition, by using a centralized training and distributed execution architecture, a secure spectrum sensing strategy based on multi-agent reinforcement learning is designed. The proposed strategy ensures that each node makes independent decisions, which enhances the adaptability of the CE ecosystem. The proposed method is verified by extensive simulations, and the results show that it can maintain spectrum awareness of more than 95.72% and an access success rate of 91.19% under malicious attacks. Moreover, communication overhead is significantly reduced by approximately 93.53%. © 1975-2011 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Shaping Connectivity: Channel Modeling and Performance Analysis of Reconfigurable Intelligent Surfaces for IoV Visible Light Communication

引用

IEEE Transactions on Vehicular Technology 2025年

作者： Eldeeb, Hossien B. Qaraqe, Marwa Muhaidat, Sami Ghrayeb, Ali Tavakkolnia, Iman Haas, Harald University of Cambridge Electrical Engineering Division Department of Engineering Cambridge United Kingdom Hamad Bin Khalifa University Division of Information and Computing Technology College of Science and Engineering United Kingdom Qatar Foundation Doha Qatar Khalifa University Computer and Communication Engineering Abu Dhabi United Arab Emirates

This paper presents a promising solution for enhancing the reliability and data rate of Internet-of-vehicles (IoV) visible light communication (VLC) systems through the utilization of optical reconfigurable intelligent surfaces (RISs). The focus is on the infrastructure-to-vehicle (I2V) scenario, where streetlights serve as internet access points. The IoV-VLC system is modeled using an advanced non-sequential raytracing approach. A novel closed-form channel model expression is proposed, incorporating transceiver, RIS, and infrastructure parameters. The proposed model is then validated against broadband raytracing simulation results considering different combinations of system parameters, including, receiver aperture size, streetlight pole height, spacing between the poles, and RIS height. Moreover, based on the derived channel model, the error rate and data rate performances of the system are analyzed. The required numbers of RIS elements allocated to each vehicle's location, to achieve a target error rate and data rate values, are further derived. Finally, this paper demonstrates the impact of various transceiver, RIS, and infrastructure parameters on the system performance. The obtained results reveal that the proposed IoV-VLC system with optimal RIS deployment effectively addresses system outage issues and meets reliability and data speed requirements regardless of the vehicle's location. The results also shed light on the influence of various factors on system performance. Notably, the total number of required RIS elements is significantly affected by factors such as receiver aperture size, space between the poles, and transmit power budget. For instance, when considering the same power budget and error rate target, the required number of RIS elements for spacing distances of 20 m, 22 m, and 24 m are determined as 132, 244, and 428 elements, respectively. Conversely, the impact of pole height is found to be minimal as long as the space between the poles remains

关键词： Budget control

来源：评论

学校读者我要写书评

暂无评论

BERT-Driven Deep Learning Approach for Depression Detection in Social Media Posts

BERT-Driven Deep Learning Approach for Depression Detection ...

引用

Optimization Techniques for Learning (ICOTL), International Conference on

作者： Prashant Karna Sonu Kumar Keshari Ashis Kumar Mandal Basabi Chakraborty Department of Computer Science and Engineering Hajee Mohammad Danesh Science and Technology University Dinajpur Bangladesh Department of Computer Science University of Saskatchewan Saskatoon Canada Research and Regional Cooperation Division Iwate Prefectural University Takizawa Japan School of Computing Madanapalle Institute of Technology and Science Madanapalle India

Depression constitutes a worldwide health emergency, impacting countless individuals daily. However, timely diagnosis and treatment for depression are infrequent. Recent research has revealed affirmative links between the use of social media and the presence of depression. The use of learning techniques has become increasingly popular in detecting signs of depression in social media posts. This study introduces a method that utilizes transformer based models like BERT and RoBERTa. During the methodology phase we carefully preprocess the data followed by word embedding procedures. We then employ a combination of deep learning architectures such as LSTM, CNN with BiLSTM, RNN, BERT with Dense and RoBERTa with Dense to thoroughly evaluate and validate our models performance. Interestingly our results consistently show that the BERT with Dense and RoBERTa with Dense approaches outperform methods achieving an accuracy rate of 98%. This refined approach allows for accurate identification of signals in social media posts offering promising potential to make significant contributions, to the field of mental health advancement.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Artificial Intelligence based Healthcare Knowledge Structure for Automatic Medical Report Generation 7

Artificial Intelligence based Healthcare Knowledge Structure...

引用

7th International Conference on Contemporary computing and Informatics, IC3I 2024

作者： Kumar, Pramod Alghayadh, Faisal Yousef Tamta, Vinay Prasad Anand, Monika Soni, Mukesh Chaudhary, Jitendra Kumar Ganga Institute of Technology and Management Bhadana- Bahadurgarh Road Kablana Haryana Jhajjar India AlMaarefa University Computer Science and Information Systems Department College of Applied Sciences Riyadh Saudi Arabia Department of Information Technology Uttarakhand Srinagar India Chandigarh University Department Cse Punjab Mohali India Lovely Professional University Division of Research and Development Punjab Phagwara India Graphic Era Hill University School of Computing Bhimtal Campus Uttarakhand India

ISBN: (纸本)9798350350067

Automatic medical report production is a key text summarization application. Traditional text summarizing systems cannot completely interpret and use medical texts' complicated vocabulary due to the disparities between medical consultation data and general domain data. The crucial knowledge in medical consultations has not been successfully harnessed. Traditional text summary algorithms cannot automatically identify, and filter key information based on medical reports' structure and generate structured text. An AI-based knowledge-assisted structured medical report creation solution addresses these difficulties. This method uses entity-guided previous domain knowledge and structure-guided task decoupling to fully utilize medical consultation data and medical report structure. The suggested strategy improves ROUGE scores by 2% to 3% compared to similar methods, resulting in more accurate medical reports, according to IMCS21 dataset experiments. © 2024 IEEE.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

Influence of Contextual Information on Bengali-English Forward and Backward Transliteration Using Binary Coding

Influence of Contextual Information on Bengali-English Forwa...

引用

Optimization Techniques for Learning (ICOTL), International Conference on

作者： Md. Fahad Amrita Das Tipu Ashis Kumar Mandal Basabi Chakraborty Department of Computer Science and Engineering Hajee Mohammad Danesh Science and Technology University Dinajpur Bangladesh Department of Computer Science University of Saskatchewan Saskatoon Canada Research and Regional Cooperation Division Iwate Prefectural University Takizawa Japan School of Computing Madanapalle Institute of Technology and Science Madanapalle India

Transliteration of words across different scripts carries importance for both social media platforms and messaging apps. It preserves the phonetic meaning of words across various writing systems. This study evaluates the influence of contextual information within words on the transliteration of Bengali and English language pair. It utilizes the Dakshina and NEWS 2018 datasets and binary encoding for feature representation. With the random forest classifier, the results demonstrate that using neighboring transliteration units as context yields the best performance on both datasets, obtaining the highest accuracy of 81.04%. These findings highlight the vital role of contextual information within words in enhancing the performance of transliteration.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：