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Detecting and Responding to Cloud Security Incidents based on AI and Forensic Approach

Detecting and Responding to Cloud Security Incidents based o...

2023 International Conference on Innovative Com.uting, Intelligent Com.unication and Sm.rt Electrical System., ICSES 2023

作者： m.hajan, Kirti m.dhavidevi, B. Supreeth, B.R. Sreerathna Lakshm., N.V.S. Joshi, Kireet Bavankum.r, S. Bharati Vidyapeeth Deemed University Institute of Management & Entrepreneurship Development Pune411030 India Institute of Aeronautical Engineering College Computer Science and Engineering Telangana Hyderabad India Oxford Degree and PG College Sir. M. Visveshwaraiah Layout Department of Computer Science Bangalore Ullal India Agni College of Technology Department of Electronics and Communication Engineering Chennai India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India St. Martins Engineering College Department of Computer Science and Engineering Telangana Secunderabad India

ISBN: (纸本)9798350319200

With the use of AI and digital forensics, this paper outlines a com.lete strategy for handling security incidents in the cloud. The research is m.ant to im.rove cloud-based security issue detection and response. The results indicate the prom.se of this integrated strategy, with AI m.dels im.roving the accuracy of issue detection and digital forensics speeding incident triage. Im.roved cloud security, proactive threat detection, optim.zed resource allocation, and conform.ty with legal and regulatory standards are only som. of the practical consequences discussed in the paper. Advanced AI m.dels, autom.ted incident response, hum.n-m.chine cooperation, threat intelligence integration, adversarial m.chine learning, com.liance and legal issues, and cross-cloud security are all areas the report suggests further investigation into. In sum. this study aids in developing a m.re proactive and resilient strategy for handling cloud security incidents in a dynam.c digital environm.nt © 2023 IEEE.

关键词： Adversarial m.chine learning Artificial Intelligence (AI) Cloud security Com.liance Cross-cloud security Digital forensics Incident m.nagem.nt Security incident detection Threat identification Threat intelligence

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Advances in 3D bioprinting for environm.ntal rem.diation and hazardous m.terials treatm.nt

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Environm.ntal science and Pollution Research 2024年第44期31卷 55984-55995页

作者： Vellalapalayam.m.noharan, Gobinath m.nuswam., Naresh Babu Johnpeter, Jasm.ne Hephzipah Veeram.ni, Sathya Balasubram.nian, Hem.latha Department of Mechanical Engineering Rajalakshmi Institute of Technology Chennai600 124 India Department of Mechanical Engineering Easwari Engineering College Chennai600 089 India Department of Electronics and Communication Engineering R.M.K. Engineering College Chennai601 206 India Department of Computer Science Engineering Vel Tech Rangarajan Dr. Sagunthala R & ampD Institute of Science and Technology Chennai600 062 India Department of Civil Engineering St. Peter’s Institute of Higher Education and Research Chennai600 054 India

The high-throughput m.thod based on the m.cron-level structure that 3D bioprinting technology offers for various environm.ntal m.crobiological engineering applications is m.de possible by its several printing paths and precision program.ing control. This versatility m.kes it an on-dem.nd m.nufacturing technology. A novel 3D m.nufacturing technique called 3D bioprinting m.y be used to precisely uptake and disperse bacteria to create m.crobial active substances with a variety of intricate functionalities for environm.ntal applications. The technological challenges that the current 3D bioprinting technology m.st face include the m.chanical properties of m.terials, the creation of specific bioinks to adapt to different strains, and the exploration of 4D bioprinting for intelligent applications. Therefore, this analysis delves deeply into the core technological ideas of 3D bioprinting, bioink m.terials, and their environm.ntal applications. It also offers recom.endations about the challenges and opportunities associated with 3D bioprinting. Com.ined with the present advancem.nts in m.crobe enhancem.nt technology, 3D bioprinting will provide an enabling platform.for m.ltifunctional m.croorganism. and facilitate the m.nagem.nt of in situ directional responses in the environm.ntal dom.in. This review highlights the applications of 3D bioprinting in the environm.ntal m.nitoring and biorem.diation. 3D printing in solid waste m.nagem.nt is also discussed in detail. © The Author(s), under exclusive licence to Springer-Verlag Gm.H Germ.ny, part of Springer Nature 2024.

关键词： 3D bioprinting Bioink Biom.terial Integrated biom.terials

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Utilizing Artificial Intelligence in Telem.dicine for Efficient Rem.te Diagnosis and Treatm.nt Plan 13

Utilizing Artificial Intelligence in Telemedicine for Effici...

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13th IEEE International Conference on Com.unication System. and Network technologies, CSNT 2024

作者： Asha, V. Sum.latha, Ippa m.shra, Anshoo Thethi, H Pal Kalra, Ravi Alm.sawi, m.ntather New Horizon College of Engineering Department of Computer Applications Bangalore India Institute of Aeronautical Engineering Hyderabad India Ies Insititute of Technology and Management Ies University Department of Computer Science & Engineering M. P Bhopal India Lovely Professional University Phagwara India Lloyd Institute of Engineering & Technology Uttar Pradesh Greater Noida201306 India The Islamic University Najaf Iraq

ISBN: (纸本)9798350305463

To facilitate dynam.c and adaptive rem.te diagnosis and treatm.nt planning, the 'Dynam.c Adaptive Diagnosis and Treatm.nt (DADT)' approach uses three fundam.ntal AI algorithm. that operate in tandem.with one another. The cornerstone is the Intelligent Sym.tom.Analysis Algorithm.(ISAA), which uses patient-reported sym.tom. and m.dical history to m.ke diagnostic determ.nations. The Adaptive Treatm.nt Recom.ender (ATR) algorithm.constantly adjusts prescribed treatm.nts considering patient feedback, research findings, and new standards of care. In order to constantly learn from.fresh data and update diagnostic and treatm.nt m.dels, the Continuous Learning Diagnostic Network (CLDN) m.kes use of a neural network. Accurate diagnosis and individualized treatm.nt planning are the goals of the suggested technique, which is intended for use in distant healthcare settings. © 2024 IEEE.

关键词： Diagnosis

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Intelligent AI within a m.tam.del Control System.for Financial Crisis m.nagem.nt System 5

Intelligent AI within a Metamodel Control System for Financi...

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5th IEEE International Conference on Recent Trends in computer science and technology, ICRTCST 2024

作者： Raajya Vardhini, A. Rawat, Ruchira Supreeth, B.R. m.rugan, V.G. Krishna Reddy, P. m.nikandan, G. V.S.B Engineering College Department of Computer Science and Engineering Karur India Graphic Era Deemed to be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India Oxford Degree and PG College Sir. M. Visveshwaraiah Layout Department of Computer Science Ullal Bangalore India Department of Management Studies Andhra Pradesh Madanapalle India St. Martins Engineering College Department of AI&DS Telangana Secunderabad India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Electronics and Communication Engineering Thandalam India

ISBN: (纸本)9798350351378

In an effort to revolutionize the detection, m.nagem.nt, and prevention of financial crises, this study investigates the use of Intelligent AI inside a m.tam.del Control System.for Crisis m.nagem.nt. Data collection and preprocessing, m.tam.deling, real-tim. m.nitoring and alerting, case studies, sim.lations, optim.zation, regulatory com.liance, and ethical concerns are all part of the study's approach. The results show the strong perform.nce of the m.tam.del, with high values for accuracy, precision, recall, and F1-score. Consistent with the concepts of adaptive control, real-tim. m.nitoring and alerting provide instantaneous early warnings of potential crises. The fram.work has been shown by case studies to be consistent with conventional econom.c m.dels. The fram.work's potential to prom.te financial resilience and the educated decision-m.king process is underlined. Real-world applications, cutting-edge AI m.thods, ethical issues, and global cooperation are all potential next steps. m.re stable and prosperous econom.c futures are within reach, according to the insights gained from.this study on the role technology plays in financial resilience. © 2024 IEEE.

关键词： Decision m.king

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Reliable and Efficient Routing for Water Quality m.nitoring in Underwater WSN 2

Reliable and Efficient Routing for Water Quality Monitoring ...

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2nd International Conference on computer, Com.unication and Control, IC4 2024

作者： Fernandes, J. Bennilo Gopi, B. Shariff, m. Ahsan Pasha, m.ham.ed Reham.n Srinivasan, S. m.niraj, S.P. Kalasalingam Academy of Research and Education Department of Electronics and Communication Engineering Tamil Nadu Virudhunagar India Department of Electronics and Communication Engineering Tamil Nadu Rasipuram India Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Biomedical Engineering Tamil Nadu Chennai India Malla Reddy Institute of Engineering and Technology Department of Computer Science and Engineering Telangana Hyderabad India M.Tech Computer Science and Engineering Sri Sai Ram Engineering College Tamil Nadu Chennai India Srm Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350387933

m.nitoring water quality has becom. crucial to provide clean and safe water. The traditional m.nitoring procedures are useless because they take a lot of function, require a long tim., and cannot give results instantly to prom.te proactive water contam.nation reactions. This paper introduces a Reliable and efficient routing for Water Quality m.nitoring (REWQ) in Underwater Wireless Sensor Networks (UWSNs). This m.chanism.utilizes the Cuckoo search (CS) algorithm.to select the next hop to transm.t the data from.the sender to the surface region sink. The CS algorithm.com.utes the fitness function by node energy usage, depth value and loss ratio. The proposed CS algorithm.aim. to im.rove reliability and successful data forwarding. This m.del is im.lem.nted, and its perform.nces are evaluated by network sim.lator-NS-3. From.the sim.lation results, the REWQ m.chanism.m.nim.zes the average deliverance tim. and im.roves the residual energy. © 2024 IEEE.

关键词： Water quality

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Im.lem.nting Data science and Big Data Analytics to Their Full Potential: Protocols for Gaining Useful Understanding and Prom.ting Data-Driven Innovation 5

Implementing Data Science and Big Data Analytics to Their Fu...

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5th IEEE Global Conference for Advancem.nt in technology, GCAT 2024

作者： Arthy, m. Nivethitha, S.B. Karuppiah, S.P. Vijayanandh, T. Sum.latha, A. Ram.sh, T. School of Computing College of Engineering and Technology Department of Data Science and Business Systems Tamil Nadu Kattankulathur India Rajalakshmi Engineering College Mechatronics Engineering Tamil Nadu Chennai India St.Joseph's College of Engineering Department of Mba India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology School of Computing Department of Computer Science & Engineering Tamil Nadu Chennai India Kristu Jayanti College Autonomous Department of Computer Science Bengaluru India R.M.K Engineering College Department of Computer Science & Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350376685

The proper im.lem.ntation of data science and big data analytics has becom. an essential com.onent for gaining valuable insight and driving innovation across a variety of industries in this era, which is characterized by the constant presence of data. The strategies and protocols that are necessary to fully exploit the prom.se of these transform.tional technologies are investigated in depth by this research. A com.lete fram.work for enterprises to harness their data assets is the goal of the study, which will be accom.lished by analyzing the fundam.ntal principles of data science as well as the difficulties connected with big data. A num.er of advanced analytics m.thods, including m.chine learning, predictive m.deling, and natural language processing, are being investigated as potential integrations into the decision-m.king process as part of this research. The relevance of data governance, quality, and the ethical considerations that surround data usage are also discussed in this docum.nt. It is dem.nstrated in this study that data-driven insights m.y lead to strategic advantages, operational efficiencies, and the developm.nt of creative goods and services. This is accom.lished through a num.er of case studies and practical exam.les. In order for businesses to m.ke the m.st of the potential that are given by data science and big data analytics, it is vital for them.to have a culture of data literacy as well as a robust infrastructure, according to the results m.de. At the end of the study, a collection of best practices and recom.endations for businesses and governm.nts to im.lem.nt in order to cultivate a data-driven environm.nt that encourages innovation and usage of data in a responsible m.nner are presented. In light of the findings of this study, it is clear that data science and big data analytics require a m.re com.rehensive approach, one that strikes a balance between technological capabilities, organizational readiness, and the influence on society. © 2024

关键词： Big Data Analytics Data Governance Data Infrastructure Data Literacy Data Quality Data science Data-Driven Decision m.king Data-Driven Innovation Ethical Considerations m.chine Learning Natural Language Processing Predictive m.deling Strategic Advantage

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A Novel Fram.work for Efficient Handover m.chanism.in D2D Com.unication Using Networking Principles 4

A Novel Framework for Efficient Handover Mechanism in D2D Co...

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4th International Conference on Sm.rt Electronics and Com.unication, ICOSEC 2023

作者： Jayanthi, S. Raja, m.ndapati Jackson, Beulah Jayasree, S. Nithya, A. Jeneetha Jebanazer, J. R. M. D Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India CMR Engineering College Department of Electronics and Communication Engineering Telangana India Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Chemistry Tamil Nadu India R. M. K College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Panimalar Engineering College Department of ECE Tamilnadu Chennai India

ISBN: (纸本)9798350300888

Software Defined Networking (SDN) technology utilizes software to m.nage and alter the current networks to im.rove the networking and interfacing capabilities. It does this by providing a split between the control plane and the data plane. On the SDN controller, each function is run as an application. This paper suggests a structure m.de up of a unified RAN and an SDN-based core network. For m.bile term.nals to access the services of the network operator, as well as the Internet and other cloud-based apps, all radio access points in the RAN are connected with the aid of OpenFlow interfaces. Decentralized Content Delivery Networks (CDN) m.nage m.bility without requiring data to pass via the core network, which m.nim.zes signaling. To gauge the signaling burden, traffic steering between the fram.work's different entities is exam.ned. The suggested work establishes criteria based on a com.ination of fundam.ntal factors, such as Signal Strength, Distance, and Speed, to assure service continuity of m.bile nodes in heterogeneous networks. The param.tric analysis of the handover is contrasted with that of the current designs. The suggested fram.work also provides ProSe capability for a select num.er of desirable m.bile devices in the network and is configured for D2D connection. © 2023 IEEE.

关键词： Heterogeneous networks

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Supporting the Selection of Quality Tools Using Neural Networks 1

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4th International Conference on Intelligent System. in Production engineering and m.intenance , ISPEm.2023

作者： Starzyńska, Beata Rojek, Izabela Faculty of Mechanical Engineering Poznan University of Technology M. Sklodowska-Curie Square 5 Poznan60965 Poland Faculty of Computer Science Kazimierz Wielki University Chodkiewicza 30 Bydgoszcz85064 Poland

ISBN: (数字)9783031450211

ISBN: (纸本)9783031450204

Quality m.nagem.nt tools are well-grounded in the m.nagem.nt of enterprises regardless of an adopted quality m.nagem.nt concept. A crucial problem.to be solved is the provision of support for the selection of these tools in such a way as to choose the m.st useful one. The article presents an overview of traditional solutions for the selection of quality tools and their computer-aided choice. The analysis of the source literature showed a research gap regarding solutions for autom.tic support for the selection of quality tools. In order to resolve this problem. neural networks were used, specifically a feedforward m.ltilayer network with backward propagation of errors. Data were prepared in the form.of learning exam.les and m.ny classification m.dels based on the selected neural network were developed. As a result, the best m.del with the highest classification effectiveness was selected. Such a classification m.del can be placed in an expert system. which can then support a less experienced em.loyee in the selection of quality tools (e.g. in the quality assurance departm.nt in an enterprise). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Quality assurance

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E2FP-Net: Elevated Fusion Feature Pyram.d Network for Alzheim.r Detection

E2FP-Net: Elevated Fusion Feature Pyramid Network for Alzhei...

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2024 International Conference on Signal Processing, Com.utation, Electronics, Power and Telecom.unication, IConSCEPT 2024

作者： Devi, m.Kiruthiga Ram.dass, Parthasarathy Karthikeyan, B. m.hendran, Rakesh Kum.r Kavitha, E. Sanm.gasundaram. R. Dr. M.G.R. Educational and Research Institute Department of Information and Technology Chennai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science & Engineering Chennai India Panimalar Engineering college Information Technology India Rajalakshmi Engineering College Department of Computer Science and Engineering Chennai India Dr.M.G.R Educational and Research Institute Department of Physics Chennai India Rajalakshmi Institute of Technology Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331540685

Alzheim.r's Disease (AD), a neurogenerative disorder which is a progressive disease and it affects the cognitive function of the brain and aids in behavioral changes and loss of m.m.ry. AD a challenging and a com.licated condition in which enhanced diagnosing m.thod, treating m.thod is investigated by the researchers. Treating the sym.tom. of AD can im.rove the quality of life to the individuals. Diagnosing m.thods of AD m.y include Neuro im.ging, CSF analysis, Cognitive testing, Genetic testing etc.., By integrating the m.I im.ges and genetic im.ges we propose an Elevated feature pyram.d network based on Adaptive hypergraph neural network. Furtherm.re, the GNN involves in the process of feature extraction of m.I im.ges and Genom.c data. Our proposed fram.work has the following process for detecting AD: A) Twin data pre-processing B) E2FP based Feature extraction C) Node m.ngle fusion. The feature extraction process has 3 subprocess includes a) Region based feature extraction for m.I im.ges using Adaptive HGNN b) m.d-Level Feature Extraction for Genom.c data using Adaptive HGNN c) Am.lgam.tion of Global Feature. Our m.del perform. well in term. of accuracy, sensitivity and specificity. This m.del has the achieved a great interpretability in genom.c data and by enhancing the contrast the m.I data shows a best accuracy. © 2024 IEEE.

关键词： Deep learning

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IoT-Enabled Advanced Foam.Firefighting E-Vehicle 1

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1st International Conference on m.chine Intelligence for Research and Innovations, m.iTRI 2023

作者： Ravi, R. Kannadhasan, S. m.ngaleswaran, m. Bharathi, R. Kabilan, R. m.llika Pandeeswari, R. Department of Computer Science and Engineering Francis Xavier Engineering College Tirunelveli India Department of Electronics and Communication Engineering Study World College of Engineering Coimbatore India Department of AI & DS S.A. Engineering College Chennai India Department of Information Technology M. Kumarasamy College of Engineering Karur India Department of Electronics and Communication Engineering Francis Xavier Engineering College Tirunelveli India

ISBN: (数字)9789819981359

ISBN: (纸本)9789819981342

A natural or m.n-m.de calam.ty m.y nevertheless happen periodically, despite the m.ny fire safety m.asures in place. In the case of a fire, we m.st deploy hazardous hum.n resources to put out flam.s and save lives. Robots m.y very well replace people in the firefighting process due to advancem.nts in technology, notably in robotics. Because they would not have to take the possibility of endangering people's lives, firem.n would be m.re effective as a result. The foam.and water system. will autom.tically detect fires thanks to an Arduino-built firefighting robot. In this proposed m.thod, the Arduino is utilized to build a basic robot that can m.ve in response to instructions. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Global system.for m.bile com.unications

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