检索结果-内蒙古大学图书馆

2024 IEEE International Conference on Intelligent Systems and Advanced Applications, ICISAA 2024

作者： Roy, Prince Kumar, Rajneesh Morshed, Md Neaz Fairleigh Dickinson University Dept. of Applied Computer Science United States Dept. of Computer Science & Engineering India

ISBN: (纸本)9798331539948

The process of a supply chain involves a series of activities that distribute, assemble, and manage products, transferring them from the supplier to the end consumer. It operates as a complex, interconnected network regulated by supply and demand. Security in supply chain management is a crucial aspect of its overall security measures, focusing primarily on maintaining essential end-to-end protection. Without this, several attacks can be used to manipulate data and valuable information from the entire chain of networks. This paper explains how encrypted intermediates can secure the entire SCM by validating each intermediate using public-private key encryption. We also demonstrate and assess how the proposed AAF-SCM model can aid in tracing security breaches or unauthorized data tampering. We also validate this model against nefarious attacks like Fabrication, Assertion, Deletion, and Modification. Finally, we propose opportunities to develop innovative systems that enhance security through intermediary steps. © 2024 IEEE.

关键词： Supply chain management

来源：评论

学校读者我要写书评

暂无评论

Improved RGB-D Indoor Semantic Segmentation using Cascaded Loss Fusion 6

Improved RGB-D Indoor Semantic Segmentation using Cascaded L...

引用

6th IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality, AIxVR 2024

作者： Patil, Sonali Sellent, Anita Gerndt, Andreas Albuquerque, Georgia Institute for Software Technology Braunschweig Germany Mainz University of Applied Science Dept. of Geoinformatics and Surveying Mainz Germany

ISBN: (纸本)9798350372021

Semantic segmentation of images promises numerous benefits for augmented reality applications. However, in such applications typical scenes are challenging for current segmentation algorithms due to high variability in object appearances and distribution. We propose a new cascaded loss fusion strategy to improve the training schedule of state-of-the-art realtime RGB-D semantic segmentation architectures. We employ methods developed in the context of multi-task learning to solve the multiclass and multi-loss learning problems in semantic segmentation. Through our quantitative evaluation on the NYUv2 [3] and SUNRGB-D [4] benchmark datasets, we show improvement over the state-of-the-art approaches. Furthermore, our approach improves results qualitatively on both the benchmark datasets as well as on our own recordings of some scenarios that are typical for head-mounted cameras. © 2024 IEEE.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

IMPLICIT NEURAL REPRESENTATION INFERENCE FOR LOW-DIMENSIONAL BAYESIAN DEEP LEARNING 12

IMPLICIT NEURAL REPRESENTATION INFERENCE FOR LOW-DIMENSIONAL...

引用

12th International Conference on Learning Representations, ICLR 2024

作者： Dimitrakopoulos, Panagiotis Sfikas, Giorgos Nikou, Christophoros Dept. of Computer Science & Engineering University of Ioannina Ioannina Greece Dept. of Surveying & Geoinformatics University of West Attica Athens Greece

Bayesian inference is the standard for providing full predictive distributions with well calibrated uncertainty estimates. However, scaling to a modern, overparameterized deep learning setting typically comes at the cost of severe and restrictive approximations, sacrificing model predictive strength. With our approach, we factor model parameters as a function of deterministic and probabilistic components;the model is solved by combining maximum a posteriori estimation of the former, with inference over a low-dimensional, Implicit Neural Representation of the latter. This results in a solution that combines both predictive accuracy and good calibration, as it entails inducing stochasticity over the full set of model weights while being comparatively cheap to compute. Experimentally, our approach compares favorably to the state of the art, including much more expensive methods as well as less expressive posterior approximations over full network parameters. © 2024 12th International Conference on Learning Representations, ICLR 2024. All rights reserved.

关键词： Uncertainty analysis

来源：评论

学校读者我要写书评

暂无评论

A Framework for the Systematic Assessment of Anomaly Detectors in Time-Sensitive Automotive Networks 15

A Framework for the Systematic Assessment of Anomaly Detecto...

引用

15th IEEE Vehicular Networking Conference, VNC 2024

作者： Meyer, Philipp Hackel, Timo Lubeck, Teresa Korf, Franz Schmidt, Thomas C. Hamburg University of Applied Sciences Dept. Computer Science Germany

ISBN: (纸本)9798350362701

Connected cars are susceptible to cyberattacks. Security and safety of future vehicles highly depend on a holistic protection of automotive components, of which the time-sensitive backbone network takes a significant role. These onboard Time-Sensitive Networks (TSNs) require monitoring for safety and-as versatile platforms to host Network Anomaly Detection Systems (NADSs)-for security. Still a thorough evaluation of anomaly detection methods in the context of hard real-Time operations, automotive protocol stacks, and domain specific attack vectors is missing along with appropriate input datasets. In this paper, we present an assessment framework that allows for reproducible, comparable, and rapid evaluation of detection algorithms. It is based on a simulation toolchain, which contributes configurable topologies, traffic streams, anomalies, attacks, and detectors. We demonstrate the assessment of NADSs in a comprehensive in-vehicular network with its communication flows, on which we model traffic anomalies. We evaluate exemplary detection mechanisms and reveal how the detection performance is influenced by different combinations of TSN traffic flows and anomaly types. Our approach translates to other real-Time Ethernet domains, such as industrial facilities, airplanes, and UAVs. © 2024 IEEE.

关键词： Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Compromising insecure crypto implementations: A deep-learning based cryptosystem-agnostic testing framework

Compromising insecure crypto implementations: A deep-learnin...

引用

2024 International Conference on Artificial Intelligence, computer, Data sciences, and Applications, ACDSA 2024

作者： Hill, Leonard Schimanke, Florian Schiffner, Stefan Mertens, Robert Hsw University of Applied Sciences Dept. of Computer Science Hameln Germany Berufliche Hochschule Hamburg Dept. of Computer Science Hamburg Germany

ISBN: (纸本)9798350394528

The use of insecure implementations of cryptographic systems makes encrypted communications vulnerable to practical attacks. Today, attacking, i.e. testing implementations requires human labour and an understanding of the cryptographic system. Automated systematic testing can reduce the insight needed to discover faulty implementations. The approach presented in this paper employs neural networks as the core of a universal framework for cryptographic attacks on arbitrary black-box encryption schemes. The framework trains a neuronal network to automatically perform decryption of ciphertext without knowing the corresponding decryption key. The network approximates the decryption function by encrypting randomly generated plaintext using an arbitrary encryption function and attempting to learn the relationship between plain-and ciphertext. If the decryption function for a certain key is successfully approximated by the framework, the plaintext of any message encrypted with this key can be restored. © 2024 IEEE.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

A Comparative Analysis of Digital Twins for Advanced Networks 7

A Comparative Analysis of Digital Twins for Advanced Network...

引用

7th IEEE International Conference and Workshop Obuda on Electrical and Power Engineering, CANDO-EPE 2024

作者： Muslim, Urwah Recker, Stephan University of Applied Sciences and Arts Dept. of computer science Dortmund Germany

ISBN: (纸本)9798331531119

A Digital Twin offers a revolutionary approach to analyzing scalable networks. By creating high-fidelity, fine-grained digital replicas of the network environment at a low cost, it facilitates comprehensive and safe analysis of network behavior in controlled settings. Numerous digital twin platforms are available online, each with distinct focuses and limitations. This study systematically investigates open-source digital twin platforms for computer networks by establishing a comprehensive set of criteria to evaluate their features and limitations. Subsequently, the chosen platforms undergo a rigorous evaluation using a large-scale distributed computing test case. This testing enables a detailed analysis of resource utilization metrics, offering valuable insights into the performance characteristics of these platforms. © 2024 IEEE.

关键词： computer network performance evaluation

来源：评论

学校读者我要写书评

暂无评论

Media Competence is the key requirement when using Generative AI in Academic Education in a meaningful way

Media Competence is the key requirement when using Generativ...

引用

2024 IEEE International Conference of Artificial Intelligence x Humanities, Education, and Art, AIxHEART 2024

作者： Schimanke, Florian Dept. of Computer Science HSW University of Applied Sciences Hameln Germany

ISBN: (纸本)9798350391015

With the release of ChatGPT, Pandora's box of generative AI has been opened and the new technology is here to stay. This also impacts academic education, where it provides new opportunities while also bearing certain challenges. Students and educators alike will have to adapt to the newly available technology and find ways to use it in a meaningful and profitable way. Summarized, this means that both parties need to develop media competence in using generative AI on their end in academic education. New ways of learning and teaching are required, as well as a change in how educators grade the students' learning status. While the latter should be made aware of the opportunities that generative AI provides them with, educators should actively make use of it in their courses in order to enhance their teaching. © 2024 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Robust Line-Convex Polygon Intersection Computation in E2 using Projective Space Representation

引用

Machine Graphics and Vision 2023年第3-4期32卷 3-16页

作者： Skala, Vaclav Dept. of Computer Science and Engineering Faculty of Applied Sciences University of West Bohemia Pilsen Czech Republic

This paper describes modified robust algorithms for a line clipping by a convex polygon in E2 and a convex polyhedron in E3. The proposed algorithm is based on the Cyrus-Beck algorithm and uses homogeneous coordinates to increase the robustness of computation. The algorithm enables computation fully in the projective space using the homogeneous coordinates and the line can be given in the projective space, in general. If the result can remain in projective space, no division operation is needed. It supports the use of vector-vector operations, SSE/AVX instructions, and GPU. © 2023 Institute of Information Technology, Warsaw University of Life sciences - SGGW. All rights reserved.

关键词： computer graphics

来源：评论

学校读者我要写书评

暂无评论

Enhancing Security: A Haar Cascade-based Face Recognition System for PGs and Hostels 9

Enhancing Security: A Haar Cascade-based Face Recognition Sy...

引用

9th IEEE International Conference for Convergence in Technology, I2CT 2024

作者： Kumar, Pallavi R. Janani, K. Sri Vaishnavi, N. Sai Pradeep Rao, K. Reddy, D. J. Yashwanth Ms Ramaiah University of Applied Sciences Dept. of Computer Science Bangalore India

ISBN: (纸本)9798350394474

This work introduces an innovative security system prototype tailored explicitly for paying guest accommodations or hostels, blending Internet of Things (IoT), artificial intelligence (AI), machine learning algorithms, and web crawling technologies. The core emphasis revolves around facial recognition, precisely distinguishing between known and unknown individuals to manage entry effectively. The system, integrating camera technology, captures visitor images and employs advanced face recognition algorithms for precise face classification. In instances where faces remain unrecognized, the system leverages web crawling to retrieve potential intruder details. Immediate notifications, featuring captured images, are swiftly dispatched to users through email and smartphone alerts, enabling prompt responses. Operated within a wireless infrastructure governed by a Raspberry Pi, this system prioritizes cost-effectiveness and user-friendliness. Rigorously tested across diverse environments encompassing homes, paying guest accommodations, and office spaces, this research establishes a remarkable balance between cutting-edge technology and pragmatic security applications. This solution offers an affordable and efficient security option tailored explicitly for the unique needs of contemporary hostels and paying guest accommodations, ensuring heightened security without exorbitant expenses. © 2024 IEEE.

关键词： Electronic mail

来源：评论

学校读者我要写书评

暂无评论

Computational Web Drug Discovery Application forSARS- Cov-2 Disease Using Predictive and Analytical Approach 10

Computational Web Drug Discovery Application forSARS- Cov-2 ...

引用

10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Hemkiran, S. Kartik, R. Aswath, S. Rathan Kabilan, K. Sudha Sadasivam, G. Psg Institute of Technology and Applied Research Dept. of Computer Science and Engineering Coimbatore India Psg College of Technology Dept. of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350384369

In response to the urgent need for coronavirus treatments, this research focuses on leveraging bioactivity data collection and processing for efficient drug discovery, employing computational methods to predict potential antiviral compounds. Exploratory data analysis was performed to identify patterns and trends, and various molecular descriptors were computed for the Mpro inhibitors in the descriptor dataset preparation step. A regression model was trained using the developed random forest algorithm to predict the bioactivity of new compounds against the standard value and compared with other regression models. Additionally, a web-based application was created using the random forest model to allow users to obtain predicted bioactivity values against Mpro by providing information about molecular structures. Machine learning-based bioactivity prediction offers an intriguing plan for drug discovery, and the proposed work provides a comprehensive workflow for COVID- 19 drug discovery. The web application provides a user-friendly interface for drug discovery researchers to evaluate the potential of compounds against the Mpro target quickly. © 2024 IEEE.

关键词： COVID-19

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：