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检索条件"机构=Dept. of Applied Math and Computer Science"

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AAF-SCM: An Authenticated Framework for Supply Chain Management

AAF-SCM: An Authenticated Framework for Supply Chain Managem...

引用

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

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Analysis of Scanline and Minimum Entropy Selection Heuristics in Model Synthesis and Wave Function Collapse 5

Analysis of Scanline and Minimum Entropy Selection Heuristic...

引用

5th International Conference on Intelligent Computing, Communication, Networking and Services, ICCNS 2024

作者： Harvey, Lucas Srivastava, Gautam Brandon University Dept. of Math and Computer Science Canada

ISBN: (纸本)9798350354690

In this paper, we analyze two versions of a texture synthesis algorithm, study the cases in which they fail to produce a successful result and present modifications that could be made to lessen their rates of failure. This algorithm, Model Synthesis, and its variation Wave Function Collapse are designed to take in a small sample input image, or set of image constraints, and produce a larger pseudorandom output image in which every region of the output image is locally similar to an element of the input image. Both versions of the algorithm accomplish this task by considering their output image as a grid of cells with each cell initially in a superposition of all possibilities for itself and resolving cells one by one until all cells have been resolved from their superposition to a fixed value. One of the key differences between the two versions of the algorithm is the order in which cells are selected to be resolved, one simply selects in a scanline order, while the other resolves first those cells that have the minimum entropy, and thus which we can be most certain of their eventual state. For many inputs, the minimum entropy model reaches a state in which its output is not consistent with the input and thus fails, while the scanline model does not. This paper looks at the cases in which this occurs and concludes that this is often caused by the minimum entropy model creating regions of elevated constraints in its solution. Finally, it presents a possible alteration to the algorithm which allows a minimum entropy model to avoid this manner of failure among a subset of test cases. © 2024 IEEE.

关键词： Image segmentation

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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

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

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

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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

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Advantages of brain parcellation in Multiple Sclerosis Lesion Segmentation

Advantages of brain parcellation in Multiple Sclerosis Lesio...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Pishvai, Dario Samuele Rondinella, Alessia Guarnera, Francesco Battiato, Sebastiano University of Catania Dept. of Math and Computer Science Catania Italy

ISBN: (纸本)9798350386226

Segmentation of multiple sclerosis lesions plays an important role in understanding disease status. In this work, we focus on the effectiveness of brain parcellation in enhancing the performance of segmentation for multiple sclerosis lesions in Magnetic Resonance Imaging. Brain parcellation does not improve the segmentation performance, but make the results more robust in terms of overall variability (e.g. standard deviation), by dividing the brain into physically significant sub-regions that the model can concentrate on. Our approach combines parcellation with the existing diffusion-based model to increase sensitivity, particularly in regions with small anomalies. We conducted a thorough evaluation of a reference dataset on the field using all available modalities. Our results show how the parcellation of the brain when integrated into a diffusion-based pipeline, makes the segmentation of MS more stable, lowering deviations from the average, and improving some of the results w.r.t. state-of-the-art. This method achieves good segmentation capabilities even with small datasets, providing promising indications for further research. © 2024 IEEE.

关键词： Image segmentation

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A Comparative Analysis of Digital Twins for Advanced Networks 7

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

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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

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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...

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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

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Enhancing MQTT Fault Tolerance and Resilience Against Broker Failures and DoS Attacks with Decentralized Blockchain Architecture 4

Enhancing MQTT Fault Tolerance and Resilience Against Broker...

引用

4th Intelligent Cybersecurity Conference, ICSC 2024

作者： Toe, Elisee Jaafar, Fehmi University of Quebec at Chicoutimi Dept. of Math and Computer Science Quebec Canada

ISBN: (纸本)9798350354775

The MQTT (Message Queuing Telemetry Transport) protocol has become the standard for IoT (Internet of Things) communication due to its lightweight nature and efficiency. However, its centralized architecture, with a single broker managing message flow, introduces vulnerabilities to failures and Denial of Service (DoS) attacks. This paper proposes a novel decentralized architecture for MQTT systems that leverages blockchain technology and smartcontracts to enhance resilience against broker failures and DoS attacks. Our approach utilizes a three-layer architecture comprising clients, cluster brokers, and a blockchain-based system to securely manage broker transitions and ensure continuous service. Key contributions of this work include a decentralized failover mechanism, secure recording and access control via blockchain, and a robust algorithm for improving system resilience. The use of blockchain and smartcontracts provides a tamper-proof and transparent method for managing broker transitions and access control, enhancing the security and trustworthiness of the system. These findings suggest that integrating blockchain technology with MQTT can mitigate some of the inherent vulnerabilities of traditional centralized architectures, paving the way for more resilient IoT communications. © 2024 IEEE.

关键词： Denial-of-service attack

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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

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

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

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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

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