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Business Intelligence: Security and Privacy-Related Concerns with Cloud Computing

Business Intelligence: Security and Privacy-Related Concerns...

2024 International Conference on Smart Systems for Electrical, Electronics, Communication and computer engineering, ICSSEEC 2024

作者： Hamid, Nagham Al-Tahee, Mustafa Al-Hameed, Mazin Riyadh Ahmed, Wasan Saad Fouad, Rami Al-Chilibi, Haider Hasson, Ahmed Rasol Habelalmateen, Mohammed I. College of Business Informatics University of Information Technology and Communications Baghdad Iraq Al-farahidi University Medical Instruments Engineering Techniques Baghdad Iraq National University of Science and Technology Department of Medical Devices Engineering Technologies Nasiriyah Dhi Qar Iraq Al-Turath University College Computer Technologies Engineering Baghdad Iraq Al-Kitab University Department of Computer Engineering Technologies Kirkuk Iraq Al-Kunooze University College Technical Computer Engineering Department Basrah Iraq Al Mustaqbal University Babil Iraq College of Technical Engineering The Islamic University Department of Computers Techniques Engineering Najaf Iraq

ISBN: (纸本)9798350378177

Internet technology is used in Business Intelligence (BI) and continues to provide centralized control assistance with knowledge from many structured and unstructured information sources. Business intelligence's interrelated limits are complicated, pricey, and restrictive. Resources from cloud computing with cost-effective performance and scalability can be used to upgrade existing BI systems and applications to address these issues. Due to rigorous confidentiality, reliability, interoperability requirements, and many dependencies with the other applications, BI systems are often barred from migrating to cloud applications. The paper addresses the obstacles to implementing BI within a cloud infrastructure. It provides the Security and Privacy-related Concerns in Business Intelligence (SPC-BI) framework, which assists decision-makers in considering the impact and privacy, security, costs, and effectiveness of BI structure migrating to network infrastructure. © 2024 IEEE.

关键词： Cloud security

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Operational Mitigation of Cyberattack-Induced Cascading Failures in Power Systems

Operational Mitigation of Cyberattack-Induced Cascading Fail...

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International Conference on Smart Energy Systems and Technologies (SEST)

作者： Sina Hashemi Mathaios Panteli Vetrivel S. Rajkumar Alexandru Ştefanov Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Department of Electrical Sustainable Energy Delft University of Technology Delft The Netherlands

ISBN: (数字)9798350386493

ISBN: (纸本)9798350386509

Cyber-physical power systems are susceptible to cyber threats and attacks that can lead to cascading failures and widespread power outages. Therefore, mitigating the impact of such attacks requires the timely implementation of operational strategies to prevent cascading blackouts. One Such strategy is the controlled islanding of the affected power grid, serving as a last resort against the propagation of the cascading outages. In this context, this paper introduces a novel detection-informed operational mitigation strategy, i.e., controlled islanding, against cyberattack-induced cascading failures, addressing “when” and “where” to implement controlled islanding. The proposed strategy leverages dynamic cascading failure modeling to quantify the impact of ongoing cyberattacks on power grids, using quantitative metrics such as demand-not-served (DNS). For effective operational mitigation, the strategy initiates controlled islanding when any attack, including fabricated protection trip commands and measurements' replay attacks, are detected, and any operating limits, such as line loading, are violated. It then proceeds to the implementation of controlled islanding, where identified cyberattack-affected elements are effectively surrounded by stable and self-sufficient islanded areas, while minimizing the system DNS. Numerical results on the IEEE 39-bus system demonstrate the effectiveness of the proposed strategy, reducing the DNS value by up to 47% when the controlled islanding strategy is implemented.

关键词： Islanding System dynamics Prevention and mitigation Power system protection Power system dynamics Power grids Software Power system faults computer crime Protection

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Annealing-Based Optimization for Selecting Training Space in Ensemble Learning 10

Annealing-Based Optimization for Selecting Training Space in...

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10th International Conference on Advanced informatics: Concept, Theory and Application, ICAICTA 2023

作者： Yulianti, Lenny Putri Trisetyarso, Agung Santoso, Judhi Surendro, Kridanto School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia School of Computer Science Bina Nusantara University Department of Mathematics Jakarta Indonesia

ISBN: (纸本)9798350329919

Ensemble learning integrates many learners to achieve better performance, however, it can increase the complexity dramatically. Redundant learners should be pruned to reduce ensemble complexity while allowing for increased accuracy. There are two common ways to achieve this, which include selecting the optimal training space and the optimal trained learners. This study contributes to reducing redundant learners by selecting the optimal training space using annealing-based optimization. The optimal training space was defined by 1) measuring the similarity between training spaces (clusters) and 2) searching for the best set of training spaces by minimizing the similarity between the selected training spaces. The proposed method was tested on 10 datasets from the UCI repository and compared to five state-of-The-Art random subspace methods. The results showed that the proposed method could reduce the size of the ensemble while significantly increasing its accuracy. © 2023 IEEE.

关键词： Annealing

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Pulmonary Diseases Decision Support System Using Deep Learning Approach

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computers, Materials & Continua 2022年第10期73卷 311-326页

作者： Yazan Al-Issa Ali Mohammad Alqudah Hiam Alquran Ahmed Al Issa Department of Computer Engineering Yarmouk UniversityIrbid21163Jordan Department of Biomedical Systems and Informatics Engineering Yarmouk UniversityIrbid21163Jordan Department of Biomedical Engineering Jordan University of Science and TechnologyIrbid 22110Jordan Pediatrician Mediclinic HospitalAl Ain14444UAE

Pulmonary diseases are common throughout the world,especially in developing *** diseases include chronic obstructive pulmonary diseases,pneumonia,asthma,tuberculosis,fibrosis,and recently *** general,pulmonary diseases have a similar footprint on chest radiographs which makes them difficult to discriminate even for expert *** recent years,many image processing techniques and artificial intelligence models have been developed to quickly and accurately diagnose lung *** this paper,the performance of four popular pretrained models(namely VGG16,DenseNet201,DarkNet19,and XceptionNet)in distinguishing between different pulmonary diseases was *** the best of our knowledge,this is the first published study to ever attempt to distinguish all four cases normal,pneumonia,COVID-19 and lung opacity from ChestX-Ray(CXR)*** models were trained using Chest-X-Ray(CXR)images,and statistically tested using 5-fold cross *** individual models,XceptionNet outperformed all other models with a 94.775%accuracy and Area Under the Curve(AUC)of Receiver Operating Characteristic(ROC)of 99.84%.On the other hand,DarkNet19 represents a good compromise between accuracy,fast convergence,resource utilization,and near real time detection(0.33 s).Using a collection of models,the 97.79%accuracy achieved by Ensemble Features was the highest among all surveyed methods,but it takes the longest time to predict an image(5.68 s).An efficient effective decision support system can be developed using one of those approaches to assist radiologists in the field make the right assessment in terms of accuracy and prediction time,such a dependable system can be used in rural areas and various healthcare sectors.

关键词： Pulmonary diseases deep learning lung opacity classification majority voting ensemble features

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Fused Transformers: Fused Information of Arabic long Article for Summarization 6

Fused Transformers: Fused Information of Arabic long Article...

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6th International Conference on AI in Computational Linguistics, ACLing 2024

作者： Ezzat, Zeyad Khalfallah, Ayman Khoriba, Ghadad Center for Informatics Science Information Technology and Computer Science School Nile University Giza Egypt Computer and Systems Department Faculty of Engineering Alexandria University Alexandria Egypt Applied Innovation Centre Egypt Faculty of Computers and Artificial Intelligence Helwan University Cairo Egypt

This paper introduces a novel approach for extending the applicability of pre-trained models to accommodate longer texts. Addressing the inherent limitation of quadratic performance in attention models within transformers, we propose the concept of fused transformers. By integrating new adaptor techniques, we enhance the encoding of lengthy text segments by breaking them into shorter spans. Subsequently, these segments are fused to increase the model's effectiveness in processing extended texts. This fusion mechanism serves to fortify the model's capacity for fine-tuning. Furthermore, we implement a length-based curriculum for expedited training Our experiments yielded 16 Rouge-2 points, representing a doubling of the score achieved by the vanilla fine-tuning method on the newly introduced "Mukhtasar" dataset for summarization. This highlights the effectiveness of managing complex relations among text segments and confirms that our method can outperform conventional training approaches. © 2024 Elsevier B.V.. All rights reserved.

关键词： Distribution transformers

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Integrating Data Protection at Interface of RISC-V Processor Core

Integrating Data Protection at Interface of RISC-V Processor...

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Panhellenic Conference on Electronics and Telecommunications (PACET)

作者： Ján Mach Lukáš Kohútka Pavel Čičák Institute of Computer Engineering and Applied Informatics Slovak University of Technology Slovakia Institute of Informatics Information Systems and Software Engineering Slovak University of Technology Slovakia

Fulfilling increasing performance demands of space and automotive applications can be problematic as high dependability is required. Memory is one of the most radiationsensitive parts, so it is often protected with information redundancy. This paper describes an integration of error correction and detection techniques into the interface of RISC-V processor to protect the data stored in the memory. We also provide a hardware-software interface for reporting errors and software routines for correcting data in memory. Our solution has a negligible impact (-3.9%) on the overall performance of the core with a small area and power consumption overhead.

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Exploring Seasonal Coastal Water Quality Parameter Interactions Through the Self-Organizing Map Neural Network in Eastern Mediterranean: Lebanon as a Case Study

SSRN

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SSRN 2025年

作者： Hadjisolomou, Ekaterini El Rahman Hassoun, Abed Fakhri, Milad Ghanem, Abeer Mina, Roula Herodotou, Herodotos Michaelides, Michalis Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Limassol3036 Cyprus National Center for Marine Sciences P.O. Box 189 Jounieh Lebanon GEOMAR Helmholtz Centre for Ocean Research Kiel Kiel Germany

Coastal water pollution poses significant environmental challenges, leading to severe ecological and public health consequences. Thus, new assessment tools should be developed and refined to manage water quality more efficiently. In this paper, we present the results of Self-Organizing Map (SOM) neural network models utilized to simulate several water quality parameter interactions monitored from several coastal stations in the South-Eastern Mediterranean Sea, namely in Lebanon. Four seasonal SOM models were developed and calibrated based on the available dataset. The SOM’s visualization of the Component Planes (CPs) enabled the examination of water quality parameter interactions and associations on a seasonal basis. Additionally, Pearson correlation analysis between the SOM’s Best Matching Units was calculated for each monitored parameter to augment the CPs analysis. SOM’s clustering of the data samples and assessment of anthropogenic activities nearby the associated monitoring stations, enabled the evaluation of the potential effects from the existing human activities in nearby areas for each monitoring station. Specifically, the seasonal models revealed that specific land uses nearby the monitoring stations like the ANT-2 (near river mouth), SEL-2 (near a chemical plant), BEY- 6 (public beach) are responsible for the coastal water quality degradation in Lebanon. Overall, this paper demonstrates that the SOM model is not only capable of revealing the parameters’ interactions, but also to identify sources of anthropogenic pollution. Therefore, the SOM models might be used as valuable tools in coastal water quality management. © 2025, The Authors. All rights reserved.

关键词： Eutrophication

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Designing a Code Obfuscation Scheme for Software Protection

Designing a Code Obfuscation Scheme for Software Protection

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2024 International Conference on Electrical and computer engineering Researches, ICECER 2024

作者： Azeta, Ambrose A. Awal, Abdulganiyu Azeta, Joy I. Hamunyela, Suama L. Santos, Albano dos Namibia University of Science and Technology Department of Software Engineering Windhoek Namibia Covenant University Department of Computer Science and Information Sciences Ota Nigeria Covenant University Department of Biological Sciences Ota Nigeria Namibia University of Science and Technology Department of Informatics Windhoek Namibia

ISBN: (纸本)9798331539733

Software piracy and intellectual property theft has brought about a financial decrease in revenue for the producers of software systems. Moreso, malicious end-users act as Man-At-The-End (MATE) attackers and dangerously inspect software codes either statically or dynamically to steal them. Developers need to create client applications that contain confidential information and data. As a result, large scale software firms constantly strive to secure hidden algorithms and vital programming components contained in their applications in order to have competitive advantage. The focus of this study is to design a code obfuscation scheme for software and intellectual property protection. The methodology employed includes use of programming tool and algorithms that described the key processes of the scheme. To demonstrate the strength and capability of our approach, user evaluation was conducted to arrive at the cost, potency and resilience of the scheme. Results indicate that majority of the respondents believe that the developed obfuscator is inexpensive and that it does not adversely affect memory and execution time. The current study would provide software developers the tool to obscure their intellectual property against theft. © 2024 IEEE.

关键词： Attackers intellectual property obfuscation scheme software protection

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Multi-Partner Project: Safe, Secure and Dependable Multi-UAV Systems for Search and Rescue Operations

Multi-Partner Project: Safe, Secure and Dependable Multi-UAV...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Panagiota Nikolaou Antonis Savva Ioannis Sorokos Koorosh Aslansefat Sondess Missaoui Akram Mohammed Naveed Daniel Hillen Marc Lorenz Martin D. Walker Manos Papoutsakis Simos Gerasimou Panayiotis Kolios Yiannis Papadopoulos Jan Reich Sotiris Ioannidis Maria K. Michael University of Central Lancashire Cyprus KIOS Research and Innovation Center of Excellence University of Cyprus Fraunhofer IESE Germany University of Hull UK University of York UK Institute of Computer Science Foundation for Research and Technology Greece Computer-Science Department University of Cyprus Electrical and Computer Engineering Department University of Cyprus

ISBN: (数字)9783982674100

ISBN: (纸本)9798331534646

Unmanned Aerial Vehicles (UAVs) have become essential in search and rescue operations, especially in disaster management scenarios. Their effective navigation and the integration of a plethora of sensors assist in efficient person detection, making them an essential technological tool to first responders. Multi-UAV systems extend these benefits by using coordinated strategies to cover large areas efficiently, reducing overall mission response time and enhancing its success. Despite these advantages, challenges remain in ensuring the safety, security, and dependability of (mutli-)UAV missions. Issues such as navigation risks, potential cyber threats, and hardware-/software-related reliability issues can impact the mission results. Additionally, UAVs are highly constrained devices with limited battery capacity, requiring the use of lightweight technologies. In this paper, we present part of the results of the SESAME project, an EU multi-partner project that aims to develop safe and secure multi-robot Systems. In particular, we present some of the developed SESAME Executable Digital Dependability Identities (EDDI) technologies based on Markov models, statistical distance measures, and other advanced approaches for enhancing safety, security and dependability of the UAV platform and underlying models. These EDDI technologies are seamlessly integrated using the ConSerts framework in a multi-UAV platform and tested using search and rescue scenarios. The results demonstrate significant improvements in multi-UAV safety, with an availability rate of 91% and a search and rescue algorithmic accuracy of 99.8%. Additionally, the system achieves precise detection of spoofing attacks, using collaborative localization as a mitigation technique to guide the UAV to a safe landing, even in the absence of GPS signals,

关键词： Location awareness Navigation System performance Collaboration Autonomous aerial vehicles Safety Sensors Security Reliability Time factors

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Design and Modeling of a Proton Exchange Membrane Electrolyzer-Compressed Hydrogen Storage-Proton Exchange Membrane Fuel Cell Green Hydrogen Subsystem for Integration to a Solar Photovoltaic-Battery Nanogrid

Design and Modeling of a Proton Exchange Membrane Electrolyz...

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International Conference on Energy Transition in the Mediterranean Area (SyNERGY MED)

作者： Alexandros Arsalis Fanourios Kourougianni Andreas V. Olympios Panos Papanastasiou George E. Georghiou Charalampos Konstantinou Department of Electrical and Computer Engineering PV Technology Laboratory University of Cyprus Nicosia Cyprus PHAETHON Centre of Excellence for Intelligent Efficient and Sustainable Energy Solutions Nicosia Cyprus Department of Civil and Environmental Engineering University of Cyprus Nicosia Cyprus

ISBN: (数字)9798350375923

ISBN: (纸本)9798350375930

A Photovoltaic-Battery-Green Hydrogen nanogrid system is designed and modeled to investigate its potential as a decentralized energy solution able to satisfy the load profile of Near Zero Energy Buildings. Such a system could potentially maximize self-consumption through onsite power generation, which also achieves minimization of dependence on the central power grid. The proposed system includes battery and hydrogen energy storage for various purposes. Such a combination could succeed in satisfying both the need for rapid power supply when needed (through battery energy storage), but it can also provide seasonal energy storage when the weather pattern of available solar energy changes between summer and winter (through hydrogen energy storage). The Green Hydrogen subsystem includes electrolyzer and fuel cell units, both based on proton exchange membrane technology, a hydrogen storage unit, and auxiliary components. The proposed system generates 110 kg of hydrogen per year, with electrolyzer and fuel cell efficiencies (at full load design conditions) at 58.4% and 45.8%, respectively. Self-sufficiency rate is close to 100%, while self-consumption rate is slightly below 48%.

关键词： Protons Photovoltaic systems Power supplies Fuel cells Solar energy Green hydrogen Minimization Power grids Batteries Load modeling

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