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2019 2019 IEEE International Conference On Artificial Intelligence Testing (AITest)  
of Oviedo), Claudio De La Riva (University of Oviedo), and Javier Tuya (University of Oviedo) An Analytical Framework for Security-Tuning of Artificial Intelligence Applications Under Attack 111  ...  Session: Automated Testing and AI User-Assisted Log Analysis for Quality Control of Distributed Fintech Applications ATARI: Autonomous Testing and Real-Time Intelligence -A Framework for Autonomously Testing  ... 
doi:10.1109/aitest.2019.00004 fatcat:ijwo6plmzbf27hka4qiij3bygq

Big data analytics in Industry 4.0 ecosystems

Gagangeet Singh Aujla, Radu Prodan, Danda B. Rawat
2021 Software, Practice & Experience  
The first paper titled "An Efficient Scheme for Secure Feature Location using Data Fusion and Data Mining in IOT Environment" by Balaji et al. 1 proposes a secure feature location approach based on data  ...  The cutting-edge technologies (like, Internet of things, big data, artificial intelligence, drones, cyber-physical systems, and augmented reality, and computer vision) are key enablers of this industrial  ...  quality of the submitted papers.  ... 
doi:10.1002/spe.3008 fatcat:ybmfafgybvenjpgm3w6d7wcqhq

Big Data Analytics-as-a-Service: Bridging the gap between security experts and data scientists

Claudio A. Ardagna, Valerio Bellandi, Ernesto Damiani, Michele Bezzi, Cedric Hebert
2021 Computers & electrical engineering  
Fully exploiting data through advanced analytics, machine learning and artificial intelligence, becomes crucial for businesses, from micro to large enterprises, resulting in a key advantage (or shortcoming  ...  Our solution acts as a middleware allowing a security expert and a data scientist to collaborate to the deployment of an analytics addressing their needs.  ...  Acknowledgments This work was partly supported by the European Union's Horizon 2020 research and innovation programme under the CONCORDIA: Cyber security cOmpeteNce fOr Research anD Innovation project,  ... 
doi:10.1016/j.compeleceng.2021.107215 fatcat:3g46gzlyhnff7np4d7o2ypqgqu

Challenges of Information Security in the Contemporary Cyber Threat Perception

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
In other words, it encompasses security of both data at rest and data in transmission.  ...  Information security comprises advancements, methods and practices proposed to guarantee protection of system hubs, programs, information, data and system from hack assaults, modifications to data or unintended  ...  Kingshuk Srivastava, Assistant Professor (SG), School of Computer Science (SCS), University of Petroleum and Energy Studies (UPES), Dehradun for his assistance in writing this paper.  ... 
doi:10.35940/ijitee.j1060.08810s19 fatcat:e3x623gbxzhfba7w5p3vfjiuse

The Duo of Artificial Intelligence and Big Data for Industry 4.0: Review of Applications, Techniques, Challenges, and Future Research Directions [article]

Senthil Kumar Jagatheesaperumal, Mohamed Rahouti, Kashif Ahmad, Ala Al-Fuqaha, Mohsen Guizani
2021 arXiv   pre-print
The increasing need for economic, safe, and sustainable smart manufacturing combined with novel technological enablers, has paved the way for Artificial Intelligence (AI) and Big Data in support of smart  ...  , interpretability, communication, and different adversarial attacks and security issues.  ...  ACKNOWLEDGMENT The authors gratefully acknowledge the Management, and Faculty of Mepco Schlenk Engineering College, Sivakasi, India for their support and extending necessary facilities to carry out this  ... 
arXiv:2104.02425v2 fatcat:r25gug6wmrbyjnreiewprdvqpa

Application of distributed computing and machine learning technologies to cybersecurity

Hamza Attak, Marc Combalia, Georgios Gardikis, Bernat Gastón, Ludovic Jacquin, Dimitris Katsianis, Antonis Litke, Nikolaos Papadakis, Dimitris Papadopoulos, Antonio Pastor, Marc Roig, Olga Segou
2018 Zenodo  
The Data Analysis and Remediation Engine executes security analytics modules on top of monitoring data modules in order to detect threats.  ...  The security analytics heavily leverage Machine Learning algorithms for detecting anomalies and classifying threats.  ...  This paper focuses on the DARE, which couple Artificial Intelligence (AI) with security.  ... 
doi:10.5281/zenodo.3266038 fatcat:3hp3onsq2zemzckcegscpfipjq

Artificial Neural Network Model for Intrusion Detection System

Yusuf Musa Malgwi, Ibrahim Goni, Bamanga Mahmud Ahmad
2022 Mediterranean Journal of Basic and Applied Sciences  
Artificial Intelligence (AI) breakthroughs in the last few years have accelerated dramatically as a result of the industry's vast technological use.  ...  During the realization of this work Artificial Neural Network (ANN) were used to shape the proposed model using a realistic CICIDS2017 dataset retrieved from the Canadian Institute for Cyber-Security (  ...  The hyper-parameters evaluated for tuning are alpha, which can be a contrast of multiple regularization parameter values, and hidden layer sizes, which is an alternate parameter for tuning.  ... 
doi:10.46382/mjbas.2022.6103 fatcat:jodkp32a2fcd3jahs2reb2hkvi

The Next Generation Cognitive Security Operations Center: Adaptive Analytic Lambda Architecture for Efficient Defense against Adversarial Attacks

Konstantinos Demertzis, Nikos Tziritas, Panayiotis Kikiras, Salvador Llopis Sanchez, Lazaros Iliadis
2019 Big Data and Cognitive Computing  
The proposed λ-Architecture Network Flow Forensics Framework (λ-ΝF3) is an efficient cybersecurity defense framework against adversarial attacks.  ...  A Security Operations Center (SOC) is a central technical level unit responsible for monitoring, analyzing, assessing, and defending an organization's security posture on an ongoing basis.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/bdcc3010006 fatcat:qskf3u5xkfephh5tcis3ibo35i

Davis Mirilla Dissertation on Impact Task Disengagement in Cyber Security.pdf

Davis Mirilla
2019 Figshare  
Cyber-attacks and breaches continue to rise even though cyber-security practitioners have continued to improve on Incidence Response, by investing heavily in prevention technologies.  ...  These developments, however, have created opportunities for hacktivists, cyber-criminals and nation-state inspired cyber-attacks that have resulted in high-profile data breaches in government and commercial  ...  very important group of friends.  ... 
doi:10.6084/m9.figshare.9785363.v1 fatcat:po66obagnjb6jgnqaso65hybw4

Guest Editorial Introduction to the Special Issue on Deep Learning Models for Safe and Secure Intelligent Transportation Systems

Alireza Jolfaei, Neeraj Kumar, Min Chen, Krishna Kant
2021 IEEE transactions on intelligent transportation systems (Print)  
He was a Research Professor with the Center for Secure Information Systems, George Mason University.  ...  He is currently a Professor with the Department of Computer and Information Science, Temple University, Philadelphia, PA, USA, where he directs the IUCRC Center on Intelligent Storage.  ...  of the algorithms can perturb the utility of real-time data analytics particularly for safety applications in ITS.  ... 
doi:10.1109/tits.2021.3090721 fatcat:c2o2vno6bjbnxdn6y4zm7ztmvq

Securing AI-based Healthcare Systems using Blockchain Technology: A State-of-the-Art Systematic Literature Review and Future Research Directions [article]

Rucha Shinde, Shruti Patil, Ketan Kotecha, Vidyasagar Potdar, Ganeshsree Selvachandran, Ajith Abraham
2022 arXiv   pre-print
Healthcare systems are increasingly incorporating Artificial Intelligence into their systems, but it is not a solution for all difficulties.  ...  As a result, we have synthesized a conceptual framework using Blockchain Technology for AI-based healthcare applications that considers the needs of each NLP, Computer Vision, and Acoustic AI application  ...  The Attack Surface of Artificial Intelligence Machine learning is a data processing technique that automates the development of analytical models.  ... 
arXiv:2206.04793v1 fatcat:v2wrluwugja65btmjct5wlrfm4

An Efficient Industrial Federated Learning Framework for AIoT: A Face Recognition Application [article]

Youlong Ding, Xueyang Wu, Zhitao Li, Zeheng Wu, Shengqi Tan, Qian Xu, Weike Pan, Qiang Yang
2022 arXiv   pre-print
Therefore, we propose an efficient industrial federated learning framework for AIoT in terms of a face recognition application.  ...  Recently, the artificial intelligence of things (AIoT) has been gaining increasing attention, with an intriguing vision of providing highly intelligent services through the network connection of things  ...  We demonstrate our framework in terms of a face recognition application while it paves the way for a broader scope of applications in this scenario.  ... 
arXiv:2206.13398v2 fatcat:pmhvnnv3irgutczwbpkeg6cljm

Contents

2018 2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC)  
Challenge: An Experimental Application of Artificial Intelligence Techniques to National Security Decision Support 104-109 2.7 1570415410 Movie Genre Preference Prediction Using Machine Learning  ...  for Detecting the Low-Rate Denial of Service Attacks 450-456 7.5 1570416232 Impact of Privacy Invasion in Social Network Sites 457-462 7.6 1570416296 Securing Data Forwarding against Blackhole  ... 
doi:10.1109/ccwc.2018.8301783 fatcat:qmdq273aojbarcn2gszmz6yyx4

Trustworthy Intrusion Detection in E-Healthcare Systems

Faiza Akram, Dongsheng Liu, Peibiao Zhao, Natalia Kryvinska, Sidra Abbas, Muhammad Rizwan
2021 Frontiers in Public Health  
The security of data servers in all sectors (mainly healthcare) has become one of the most crucial challenges for researchers.  ...  The practical implementation of the ANFIS model on the MATLAB framework with testing and training results compares the accuracy rate from the previous research in security.  ...  Towards secure big data analytic for cloud-enabled applications with fully homomorphic encryption.  ... 
doi:10.3389/fpubh.2021.788347 pmid:34926397 pmcid:PMC8678532 fatcat:4iso64ixvndtniok2igg5xapeq

DeepOSN: Bringing deep learning as malicious detection scheme in online social network

Putra Wanda, Marselina Endah Hiswati, Huang J. Jie
2020 IAES International Journal of Artificial Intelligence (IJ-AI)  
Notably, this article describes how deep learning makes the OSN security technique more intelligent for detecting malicious activity by establishing a classifier model.  ...  Manual analysis for malicious prediction in Online Social Networks (OSN) is time-consuming and costly. With growing users within the environment, it becomes one of the main obstacles.  ...  ACKNOWLEDGEMENTS This paper is conducted in the Institute of Research in Information Processing Laboratory, Harbin University of Science and Technology under CSC Scholarship.  ... 
doi:10.11591/ijai.v9.i1.pp146-154 fatcat:xeyelljk7bcmlolmr2h6foy2v4
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