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Cyber-Attacks Risk Analysis Method for Different Levels of Automation of Mining Processes in Mines Based on Fuzzy Theory Use

Agnieszka A. Tubis, Sylwia Werbińska-Wojciechowska, Mateusz Góralczyk, Adam Wróblewski, Bartłomiej Ziętek
2020 Sensors  
As a result, this article focuses on developing a risk analysis method that integrates Kaplan's and Garrick's approach and fuzzy theory.  ...  The fuzzy theory is implemented in risk parameter estimation for cyber-attack scenario occurrence in the mining industry.  ...  As a result, the mine will be able to base its analyses on current data on direct impacts on its own network and not rely on general industry data.  ... 
doi:10.3390/s20247210 pmid:33339301 pmcid:PMC7766562 fatcat:y2c7fzgtlfgwtimkpo3rt4dl6u

Cyber Security Threat Intelligence using Data Mining Techniques and Artificial Intelligence

2019 International journal of recent technology and engineering  
In addition, various data mining approaches used in boosting threat truthfulness in cybersecurity data are also studied.  ...  Data analysis can be formulated to guide industries and Internet-connected systems such as smartphones or robotic factories on what to do in the appearance of an incident.  ...  (2018) Information Security Risk Assesment in Database Management Systems Using Artificial Intelligence techniques, a model based on Fuzzy logic was developed. 3.  ... 
doi:10.35940/ijrte.c5675.098319 fatcat:wt6pblccmnaexodby3qpydb7sa

Application of Data Mining Techniques for Information Security in a Cloud: A Survey

Preeti Aggarwal, M. M. Chaturvedi
2013 International Journal of Computer Applications  
Data Mining techniques and algorithms contribute tremendously to this task of assuring security of information on the cloud.  ...  In this paper, review of various data mining techniques and algorithms is presented which can help achieve security of information on cloud.  ...  Soft computing framework data mining is presented in paper [2] where soft computing approaches like fuzzy logic, neural network are discussed.  ... 
doi:10.5120/13920-1804 fatcat:efk3evo2yfb4piiaakxm45yney

A Survey : Data Mining and Machine Learning Methods for Cyber Security

Ashish Prajapati, Shital Gupta
2021 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
This survey paper describes the literature survey for cyber analytics in support of intrusion detection of machine learnings (ML) and data mining (DM) methods.  ...  Documents representing each method were categorized, read and summarized based on the number of citations and significance of an evolving method. Since data is so important.  ...  Google Scholar queries using "machine learning" and "cyber," and "data mining" and cyber were conducted.  ... 
doi:10.32628/cseit217212 fatcat:rz6kk2ywprbi3lf7gz7msm2zxa

Mining Employees Safety and the Application of Information Technology in Coal Mining: Review

Li Yang, Getnet Engeda Birhane, Junqi Zhu, Jichao Geng
2021 Frontiers in Public Health  
This paper aims to analyze in detail the causes of safety and environmental issues in the coal mining industry, as well as the impact of IoT on coal mining.Method: A systematic review was conducted.  ...  And the environmental impact of abandoned mining sites should be given due attention.  ...  Shahani et al. (19) Fuzzy logic Fuzzy logic data analysis The main causes of fatalities in coal mining were mine collapse (Pakistan) and blast, accumulation of gas, gas explosion, and falling stones Liu  ... 
doi:10.3389/fpubh.2021.709987 pmid:34485234 pmcid:PMC8416457 fatcat:lwcuufgng5bzhlg6niexkuovlq

Research Methodology on Web Mining for Malware Detection
English

Shaik. Irfan Babu, Dr. M.V.P. Chandra Sekhara Rao, G.Nagi Reddy
2014 International Journal of Computer Trends and Technology  
The proposed web mining methodology uses web structure mining, using graph mining for malware detection with a case study proposed on cloud mining.  ...  In this review paper we want to discuss Research Methodology on Web mining for Malware detection.  ...  Web mining is based on data mining technique by using data mining technique discover the hidden data in web log.  ... 
doi:10.14445/22312803/ijctt-v12p131 fatcat:tt4nfblmhfb43a5a5j7hrew2pm

Fraud Analytics Using Data Mining

2016 International Journal of Research Studies in Computer Science and Engineering  
The two main types of data mining methods i.e. supervised and unsupervised learning methods used in fraud analytics have been intensively reviewed with the help of existing literature.  ...  This paper deals with the data mining techniques used to combat fraud in different industries.  ...  Several innovative data visualization and data mining technologies are being deployed by security firms to help in identifying data patterns.  ... 
doi:10.20431/2349-4859.0304001 fatcat:nzq4rwmlyrelhmxwntxrb467g4

A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection

Anna L. Buczak, Erhan Guven
2016 IEEE Communications Surveys and Tutorials  
This survey paper describes a focused literature survey of machine learning (ML) and data mining (DM) methods for cyber analytics in support of intrusion detection.  ...  The complexity of ML/DM algorithms is addressed, discussion of challenges for using ML/DM for cyber security is presented, and some recommendations on when to use a given method are provided.  ...  Integrating fuzzy logic with frequency episodes was attempted by Luo and Bridges [39] to find the fuzzy frequency episodes that represent the frequent fuzzy sequences in the data.  ... 
doi:10.1109/comst.2015.2494502 fatcat:n6l5u4xgvbc7jgsy35mlmlpwp4

IEEE Access Special Section Editorial: Data Mining for Internet of Things

Chun-Wei Tsai, Mu-Yen Chen, Francesco Piccialli, Tie Qiu, Jason J. Jung, Patrick C. K. Hung, Sherali Zeadally
2021 IEEE Access  
., ''Research and application of element logging intelligent identification model based on data mining,'' by Liang et al., ''Cyber security threats detection in Internet of Things using deep learning approach  ...  algorithm,'' by Wang and Wang; ''Operating efficiency-based data mining on intensive land use in smart city,'' by Duan et al.; ''Simulation of vehicle network communication security based on random geometry  ... 
doi:10.1109/access.2021.3090137 fatcat:cnleukmukfgexmkwx7tino2k5y

From logs to stories: human-centred data mining for cyber threat intelligence

Neda AfzaliSeresht, Yuan Miao, Sandra Michalska, Qing Liu, Hua Wang
2020 IEEE Access  
The validation is performed on case study from Security Operations Centre (SOC) at educational institution.  ...  The solution caters for different levels of reader expertise and preference by providing adjustable templates, filled from both local and global knowledge base.  ...  allows to spot the potential logical links.  ... 
doi:10.1109/access.2020.2966760 fatcat:s4ul3sjw7ngtfcvu7piffxkf4e

A technology map to facilitate the process of mine modernization throughout the mining cycle

J. Jacobs
2017 Journal of the Southern African Institute of Mining and Metallurgy  
mining industry currently spends so little on innovation and business-improvement programmes.  ...  On a revenue-to-revenue basis, the industry spends 80% less on technology and innovation compared with the petroleum sector, for example.  ...  Examples include cloud computing, sensors, GPS systems, embedded logic, cyber-security, 'big data', 3D visualization, and simulation modelling (Deloitte, 2014) .  ... 
doi:10.17159/2411-9717/2017/v117n7a5 fatcat:bfweg5nu5vfrherdjdw54tw3ji

A systematic mapping study of process mining

Ana Rocío Cárdenas Maita, Lucas Corrêa Martins, Carlos Ramón López Paz, Laura Rafferty, Patrick C. K. Hung, Sarajane Marques Peres, Marcelo Fantinato
2017 Figshare  
The analysis of 705 papers evidenced 'discovery' (71%) as the main type of process mining addressed and 'categorical prediction' (25%) as the main mining task solved.  ...  The most applied traditional technique is the 'graph structure-based' ones (38%).  ...  Process Mining: Extending alpha-Algorithm to Mine Duplicate Tasks in Process Logs 2007 C Pacific-Asia Conf. on Advances in Knowledge Discovery and Data Mining (PAKDD) Mining high impact exceptional  ... 
doi:10.6084/m9.figshare.5619598 fatcat:bh4gcfst3rbdvaqvcipn5yrxga

A systematic mapping study of process mining

Ana Rocío Cárdenas Maita, Lucas Corrêa Martins, Carlos Ramón López Paz, Laura Rafferty, Patrick C. K. Hung, Sarajane Marques Peres, Marcelo Fantinato
2017 Figshare  
The analysis of 705 papers evidenced 'discovery (71%) as the main type of process mining addressed and 'categorical prediction (25%) as the main mining task solved.  ...  The most applied traditional technique is the 'graph structure-based ones (38%).  ...  Process Mining: Extending alpha-Algorithm to Mine Duplicate Tasks in Process Logs 2007 C Pacific-Asia Conf. on Advances in Knowledge Discovery and Data Mining (PAKDD) Mining high impact exceptional  ... 
doi:10.6084/m9.figshare.5619598.v1 fatcat:nvnam7nlgjabpl5kw3em4nyie4

Data Mining Algorithms for Smart Cities: A Bibliometric Analysis

Anestis Kousis, Christos Tjortjis
2021 Algorithms  
Smart cities connect people and places using innovative technologies such as Data Mining (DM), Machine Learning (ML), big data, and the Internet of Things (IoT).  ...  Scientists from all over the world show a great interest in researching and collaborating on this interdisciplinary scientific field.  ...  The digital and physical cities are linked by IoT, thereby forming an integrated cyber-physical space.  ... 
doi:10.3390/a14080242 fatcat:zalmt5lwhvaaflxhig44yfuw5i

Analysis of Machine Learning Algorithms to Protect from Phishing in Web Data Mining

N. Swapna
2017 International Journal of Computer Applications  
As the cyber security problems grows many types of phishing activities may arises bid data analytics is pretty helpful in identifying various phishing threats of suppliers by scanning various data roots  ...  The term Big data is a large data sets those outgrow the simple kind of database and data handling design.  ...  Data mining techniques like neural networks rule induction decision tree machine learning can be useful to the fuzzy logic model.  ... 
doi:10.5120/ijca2017912743 fatcat:nt4vh7gdazdqxa4r7u5ddqafa4
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