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Threat Alert Prioritization Using Isolation Forest and Stacked Auto Encoder with Day-Forward-Chaining Analysis

Muhamad Erza Aminanto, Tao Ban, Ryoichi Isawa, Takeshi Takahashi, Daisuke Inoue
2020 IEEE Access  
ACKNOWLEDGMENT This research was partly conducted under a contract of "Research and development on IoT malware removal / make it non-functional technologies for effective use of the radio spectrum" among  ...  "Research and Development for Expansion of Radio Wave Resources(JPJ000254)", which was supported by the Ministry of Internal Affairs and Communications, Japan.  ...  METHODOLOGY This section presents the proposed method for automated and real-time alert prioritization using unsupervised isolation forest, SAE, and day-forward-chaining analysis.  ... 
doi:10.1109/access.2020.3041837 fatcat:j2gge7abtfb6pagdgfvddhx25m

Forecasting of COVID-19 cases using Deep learning models: Is it reliable and practically significant?

Jayanthi Devaraj, Rajvikram Madurai Elavarasan, Rishi Pugazhendhi, G.M. Shafiullah, Sumathi Ganesan, Ajay Kaarthic Jeysree, Irfan Ahmad Khan, Eklas Hossain
2021 Results in Physics  
Subsequently, the prediction of cumulative confirmed, death and recovered global cases are modelled with Auto-Regressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), Stacked Long Short-Term  ...  The spread of COVID-19 is increasing day by day, imposing human lives and economy at risk.  ...  The authors would also like to acknowledge the technical expertise provided by the Clean and Resilient Energy Systems (CARES) Laboratory, Texas A&M University,  ... 
doi:10.1016/j.rinp.2021.103817 pmid:33462560 pmcid:PMC7806459 fatcat:oyycklz67vgyncz5dsddqrpfzm

D2.1 5G Security: Current Status and Future Trends

Grant Millar, Anastasios Kafchitsas, Orestis Mavrooulos, Anastasios Kourtis, George Xilouris, Maria Christopoulou, Stavros Kolometsos, Edgardo Montes De Oca, Huu Nghia Nguyen, Antonio Pastor, Sonia Fernandez, Diego Lopez (+18 others)
2020 Zenodo  
It includes a summary of the 5G threat landscape, the 5G networks classification criteria and their threat taxonomy; a description of security requirements of 5G systems, divided into domain-specific use  ...  This deliverable aims to provide a basis for the identification of use cases and the development of 5G security enablers in INSPIRE-5Gplus.  ...  In [113] , an anomaly detection system is devised to spot cyberthreats in 5G networks based on deep learning techniques, particularly Deep Belief Networks (DBN), Stacked Auto-Encoders (SAE) and Long Short-Term  ... 
doi:10.5281/zenodo.3947893 fatcat:bg7jnn5ph5fv3gjp7pqacy3us4

D2.1 5G Security: Current Status and Future Trends

Grant Millar, Anastasios Kafchitsas, Orestis Mavrooulos, Anastasios Kourtis, George Xilouris, Maria Christopoulou, Stavros Kolometsos, Edgardo Montes De Oca, Huu Nghia Nguyen, Antonio Pastor, Sonia Fernandez, Diego Lopez (+18 others)
2020 Zenodo  
It includes a summary of the 5G threat landscape, the 5G networks classification criteria and their threat taxonomy; a description of security requirements of 5G systems, divided into domain-specific use  ...  This deliverable aims to provide a basis for the identification of use cases and the development of 5G security enablers in INSPIRE-5Gplus.  ...  In [113] , an anomaly detection system is devised to spot cyberthreats in 5G networks based on deep learning techniques, particularly Deep Belief Networks (DBN), Stacked Auto-Encoders (SAE) and Long Short-Term  ... 
doi:10.5281/zenodo.4569519 fatcat:7aersbhzyrccrn563shazvj4dq

NLP Methods in Host-based Intrusion Detection Systems: A Systematic Review and Future Directions [article]

Zarrin Tasnim Sworna, Zahra Mousavi, Muhammad Ali Babar
2022 arXiv   pre-print
The Host-Based Intrusion Detection Systems (HIDS) are widely used for defending against cybersecurity attacks.  ...  and predict attacker's next steps.  ...  Filter+VAE (Variational Auto Encoder) avoiding any data pre-processing [S58] outperformed semantic ELM [S40] .  ... 
arXiv:2201.08066v1 fatcat:t6nsqoj5hnhnhcv4hsugsnau6m

An Empirical Study on System Level Aspects of Internet of Things (IoT)

Narasimha Swamy S, Kota Solomon Raju
2020 IEEE Access  
The authors would also like to thank the P C Panchariya, Director, CSIR-CEERI, Pilani, for his encouragement and constant support.  ...  Acknowledgment The authors would like to thank the Indian National Academy of Engineering (INAE), Gurgaon, and R V College of Engineering (RVCE), Bengaluru, for their financial support.  ...  [132] proposed Gaussian Bernoulli restricted Boltzmann Machine (GBRBM) based Deep Neural Network with auto Encoder (DAE).  ... 
doi:10.1109/access.2020.3029847 fatcat:5nprx4xtbjfnnkyibk6vbeg47m

Applications of Artificial Intelligence in Battling Against Covid-19: A Literature Review

Mohammad-H. Tayarani-N.
2020 Chaos, Solitons & Fractals  
We also tried to conclude the paper with ideas on how the problems can be tackled in a better way and provide some suggestions for future works.  ...  The rapid growth of the pandemic has wreaked havoc and prompted the need for immediate reactions to curb the effects.  ...  A Neural Network approach is presented in [391] which is a modified auto-encoder and is used to predict the epidemic curve of different regions in Italy.  ... 
doi:10.1016/j.chaos.2020.110338 pmid:33041533 pmcid:PMC7532790 fatcat:gl3i37hag5gflajsa7fh6khvva

International Journal of Computer Science July 2021

IJCSIS Editor
2021 Zenodo  
See authors guide for manuscript preparation and submission guidelines.  ...  , state of the art, research, standards, implementations, running experiments, applications, and industrial case studies.  ...  Stages for their activity based anomaly detection included Activity Recognition, Activity discovery and anomaly detection using isolation forest.  ... 
doi:10.5281/zenodo.5543977 fatcat:vxk2ynl3l5bbpcvpda2lt4qef4

Smart Grid: Cyber Attacks, Critical Defense Approaches, and Digital Twin [article]

Tianming Zheng, Ming Liu, Deepak Puthal, Ping Yi, Yue Wu, Xiangjian He
2022 arXiv   pre-print
cyber systems, which include device identification, vulnerability discovery, intrusion detection systems (IDSs), honeypots, attribution, and threat intelligence (TI); iv) reviews the relevant content  ...  In the end, the paper puts forward our security considerations on the future development of DT-based smart grid.  ...  ACKNOWLEDGMENT We appreciate the support of the National Key R&D Program of China under Grants No. 2020YFB1807500, No. 2020YFB1807504, and National Science Foundation of China Key Project under Grants  ... 
arXiv:2205.11783v1 fatcat:fz43u2e6g5gyfepqz44tezelba

D6.1 System Orchestration And Management Design And Implementation

Carlos Parada, Isabel Borges, Francisco Fontes, George Tsolis, Michael J. McGrath, Vincenzo Riccobene, John Thomson, Julian Chesterfield, Joel Atherley, Manos Ragiadakos, Luis Tomas Bolivar, Livnat Peer (+13 others)
2018 Zenodo  
It concludes all the efforts done at WP6, finalizing the control framework, the SLA-base deployment design, and completes the symbolic execution checking and anomaly detection tools implementation.  ...  [8] presents a stakeholder analysis, as well as a Strengths Weaknesses Opportunities Threats (SWOT) analysis.  ...  ; • Aligned with NFV; • Uses TOSCA; • Integration with other tools (ManageIQ); • Auto-healing and auto-scaling capabilities; Weakest Points: • Still immature and unstable; • VNFFG and NS only released  ... 
doi:10.5281/zenodo.1232116 fatcat:sdtzshzkljbennvyyi7qklryby

Intelligent system for COVID-19 prognosis: a state-of-the-art survey

Janmenjoy Nayak, Bighnaraj Naik, Paidi Dinesh, Kanithi Vakula, B. Kameswara Rao, Weiping Ding, Danilo Pelusi
2021 Applied intelligence (Boston)  
To deal with the challenges of the medical field, a broad range of intelligent based methods, frameworks, and equipment have been recommended by Machine Learning (ML) and Deep Learning.  ...  the prognosis of COVID-19, (iii) the growth in the development of type of ML and advanced ML methods for COVID-19 prognosis,(iv) analyzing the impact of data types and the nature of data along with challenges  ...  It is observed that various methods such as CNN, RNN, and GAN, LSTM, Auto Encoder Decoder etc. have been mostly used and their usage levels statistics have been mentioned in Fig. 8 .  ... 
doi:10.1007/s10489-020-02102-7 pmid:34764577 pmcid:PMC7786871 fatcat:vgw3qgocvnhibd6uxexuciqanm

AI and ML – Enablers for Beyond 5G Networks

Alexandros Kaloxylos, Anastasius Gavras, Daniel Camps Mur, Mir Ghoraishi, Halid Hrasnica
2020 Zenodo  
In the sequel the white paper elaborates on use case and optimisation problems that are being tackled with AI/ML, partitioned in three major areas, namely: network planning, network diagnostics/insights  ...  Feed-forward neural networks, deep neural networks, recurrent neural networks, and convolutional neural networks belong to this family.  ...  Besides, it can also be used for threat comparison and analysis.  ... 
doi:10.5281/zenodo.4299895 fatcat:ngzbopfm6bb43lnrmep6nz5icm

Artificial Intellgence – Application in Life Sciences and Beyond. The Upper Rhine Artificial Intelligence Symposium UR-AI 2021 [article]

Karl-Herbert Schäfer
2021 arXiv   pre-print
) and the University of Applied Sciences and Arts Northwestern Switzerland.  ...  Topics of the conference are applications of Artificial Intellgence in life sciences, intelligent systems, industry 4.0, mobility and others.  ...  Wetzel and T. Iraki for helpful comments and discussion.  ... 
arXiv:2112.05657v1 fatcat:wdjgymicyrfybg5zth2dc2i3ni

The Vessel Schedule Recovery Problem (VSRP) – A MIP model for handling disruptions in liner shipping

Berit D. Brouer, Jakob Dirksen, David Pisinger, Christian E.M. Plum, Bo Vaaben
2013 European Journal of Operational Research  
We demonstrate our approach on the routing problem for unmanned air vehicles with minimization of distance traveled and minimization of radar detection threat objectives. , Gokcen Turkel Dynamic scheduling  ...  Also, these problems have been addressed in collaboration with industry, and have led to substantial economic savings. We analyze scheduling chains of divisible computations.  ...  Window analysis is used to discuss the efficiency change over time. Data were collected from auto and auto component industries in Taiwan.  ... 
doi:10.1016/j.ejor.2012.08.016 fatcat:c27kagfnxnhjfbil2rydhjhomm

Statistical shape modeling in virtual assembly using PCA-technique

Björn Lindau, Lars Lindkvist, Alf Andersson, Rikard Söderberg
2013 Journal of manufacturing systems  
Special thanks to Prof ElMaraghy W. for his invaluable support and supervision. Also, we would like to thank Dr ElGeddawy T. for sharing with us his expertise in manufacturing system co-evolution.  ...  Acknowledgements We thank the whole Geometry and Motion Planning Group for useful discussions and help in the implementation.  ...  Scope of the paper A generalized method using a straight forward Principal Component Analysis (PCA) technique is presented and discussed.  ... 
doi:10.1016/j.jmsy.2013.02.002 fatcat:eaucg4ewmre3lefsbiihax6tza
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