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Improving Intrusion Detection Systems Using Artificial Neural Networks

Yaser AbdulAali JASIM
2018 Advances in Distributed Computing and Artificial Intelligence Journal  
Artificial Neural Networks; BP; Intrusion Detection System; MATLAB In this paper, some of the methods used in the intrusion detection system were described using the neural network as a tool in intrusion  ...  The results of these analyzes have been used to learn the neural network on the structure and pattern of standard and unusual packets.  ...  Jasim Improving Intrusion Detection Systems Using Artificial Neural Networks ADCAIJ: Advances in Distributed Computing and Artifical Intelligence Journal Regular Issue, Vol. 7 N. 1 (2018), 49-65 eISSN:  ... 
doi:10.14201/adcaij2018714965 fatcat:fkmykyda7ze4del3dscanb3ivy

Advanced Applications of Neural Networks and Artificial Intelligence: A Review

Koushal Kumar, Gour Sundar Mitra Thakur
2012 International Journal of Information Technology and Computer Science  
Artificial Neural Network is a branch of Artificial intelligence and has been accepted as a new computing technology in computer science fields.  ...  This paper reviews the field of Artificial intelligence and focusing on recent applications which uses Artificial Neural Networks (ANN"s) and Artificial Intelligence (AI).  ...  Neural Networks Strengthens Technology behind antivirus functioning: Artificial neural networks and artificial intelligence techniques have played increasingly important role in antivirus detection and  ... 
doi:10.5815/ijitcs.2012.06.08 fatcat:pjdstjcnuzhwlg4rex2uwfrexe

Research on Artificial Intelligence Frontier Recognition Based on LDA

Ting Xie, Ping Qin, Juehu Yan
2018 OALib  
the research frontier of artificial intelligence abroad is obtained, which includes three categories: computer vision research, application of artificial intelligence in various fields and data mining  ...  Based on LDA model, this paper uses Python language to carry out standardized processing, stop words removal, stem extraction and word shape restoration on foreign artificial intelligence data from 2013  ...  ), neural network learning algorithms (Topic 19), deep learning and Convolutional neural networks (Topic 30), neural network spatial learning models (Topic 33).  ... 
doi:10.4236/oalib.1105005 fatcat:rubbdo2n5jec5hi4wxee2urfju


A Review On Neural Networks, Joselin. J, Dinesh. T, Ashiq. M
2019 Zenodo  
Artificial Neural Networks is considered as major soft computing technology and have been widely studied and applied during the last two epochs.  ...  It also considers the incorporation of neural networks with other computing systems Such as vague logic to enhance the construal ability of data.  ...  ARTIFICIAL NEURAL NETWORKS IN COMPUTER GRAPHICS: s play an important role in graphics fields also.  ... 
doi:10.5281/zenodo.3587964 fatcat:gqoflvbhcna7lfr6gsjemywryu

Deep Learning and its applications today

Edgar Thiago De Oliveira Chagas
2019 Panorama brasileiro de tungstênio (w) entre os anos de 2008 e 2014  
Artificial intelligence is no longer a plot for fiction movies. Research in this field increases every day and provides new insights into Machine learning.  ...  Deep learning methods, also known as Deep Learning, are currently used on many fronts such as facial recognition in social networks, automated cars and even some diagnoses in the field of medicine.  ...  Dartmouth's summer research project on [13] Artificial Intelligence, in 1956, boosted neural networks, as well as artificial intelligence, encouraging research in this area in relation to neural processing  ... 
doi:10.32749/ fatcat:6nbopid6hjfcdflwpe5z64c57u

The Legal Regulation of Artificial Intelligence and Edge Computing Automation Decision-Making Risk in Wireless Network Communication

Junlei Sun, Rashid A Saeed
2022 Wireless Communications and Mobile Computing  
This paper proposes a deep learning system model in real-time artificial intelligence driven by edge computing.  ...  This article is aimed at studying the legal regulation of artificial intelligence and edge computing automated decision-making risks in wireless network communications.  ...  Edge Computing Drives the Deep Learning System Model in Real-Time Artificial Intelligence. learning has always been one of the mainstream technologies in the field of artificial intelligence.  ... 
doi:10.1155/2022/1303252 fatcat:vdtdanjfabgdpixgqftsrdi6sa

Computational Intelligence for Network Intrusion Detection: Recent Contributions [chapter]

Asim Karim
2005 Lecture Notes in Computer Science  
This paper reviews these contributions categorized in the sub-areas of soft computing, machine learning, artificial immune systems, and agentbased systems.  ...  These contributions present the success and potential of computational intelligence in network intrusion detection systems for tasks such as feature selection, signature generation, anomaly detection,  ...  This paper reviews recent computational intelligence contributions in the areas of soft computing (section 2), machine learning (section 3), artificial immune systems (section 4), and agent-based systems  ... 
doi:10.1007/11596448_25 fatcat:n6vcx2x5gbbk7dzqaf5bb5hoxq

Applications of Artificial Intelligence Techniques to Combating Cyber Crimes: A Review

Selma Dilek, Hüseyin Cakır, Mustafa Aydın
2015 International Journal of Artificial Intelligence & Applications  
Numerous bio-inspired computing methods of Artificial Intelligence have been increasingly playing an important role in cyber crime detection and prevention.  ...  , adaptable and robust, and able to detect a wide variety of threats and make intelligent real-time decisions.  ...  Numerous nature-inspired computing methods of AI (such as Computational Intelligence, Neural Networks, Intelligent Agents, Artificial Immune Systems, Machine Learning, Data Mining, Pattern Recognition,  ... 
doi:10.5121/ijaia.2015.6102 fatcat:r6cycqel5rcxpizuvejrllqxjq

Short time prediction of cloud server round-trip time using a hybrid neuro-fuzzy network

Robertas Damaševičius, Department of Software Engineering, Kaunas University of Technology, Kaunas, Lithuania, Tatjana Sidekerskienė, Department of Software Engineering, Kaunas University of Technology, Kaunas, Lithuania
2020 Journal of Artificial Intelligence and Systems  
The approach could be useful for increasing the efficiency of client-cloud systems, for example, when taking effective decisions for computational offloading, and contribute to the development of smart  ...  We predict the Round-Trip Time (RTT), i.e., the time for a network packet to travel from a client to a server and back.  ...  The method uses Journal of Artificial Intelligence and Systems historical network traffic delay data to train an artificial neural network to predict the network delay (RTT) in the future.  ... 
doi:10.33969/ais.2020.21009 fatcat:z3yxpcloene57a42mb374je6v4

Computer Network Fault Diagnosis Based On Neural Network

Wang Qian
2015 International Journal of Future Generation Communication and Networking  
With the development of artificial intelligence, using the neural network technology into the network fault diagnosis area can play an important role to the advantages of neural network in fault diagnosis  ...  Using computer network fault diagnosis as a practical example for the computer simulation and analysis developes a set of computer network diagnosis system can provide reference and assistance for the  ...  There is a certain sense diagnosis showed by example. ② Distributed Artificial Intelligence (DAI) and multi-agent systems (MAS). ③ Machine learning and data mining. ④ Research neural networks and genetic  ... 
doi:10.14257/ijfgcn.2015.8.5.04 fatcat:k5bpkzupznbx3pexlz2fjmdhse

Overview on intelligent comprehensive evaluation methods

Yong Yang, Chenxia Suo, Weijie Hao, Zhihui Zhang
2018 Review of Computer Engineer Studies  
As the computer technology develops, intelligent methods play an increasingly wider role in social life.  ...  This paper sorts out the important theories and methods for intelligent evaluation, analyzes and defines the basic principles and models involved, and forecasts the application of intelligent methods in  ...  Artificial neural network evaluation method The artificial neural network (ANN) is an artificial system that employs computer science and engineering technology methods to simulate the neural network structure  ... 
doi:10.18280/rces.050401 fatcat:42swrd7i5zawvaux3yiweajejq

Combined Computational Systems Biology and Computational Neuroscience Approaches Help Develop of Future "Cognitive Developmental Robotics"

Faramarz Faghihi, Ahmed A. Moustafa
2017 Frontiers in Neurorobotics  
AUTHOR CONTRIBUTIONS All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.  ...  One of the examples of incorporating molecular information in artificial systems is modeling of associative learning in artificial neural networks (Smith et al., 2008) .  ...  There are many challenges to implement natural intelligence in artificial neural systems including CDR (Xu et al., 2014) .  ... 
doi:10.3389/fnbot.2017.00063 pmid:29276486 pmcid:PMC5727420 fatcat:52cgr2h4w5gfze4vdz3p7scdvq

DGCC: data-driven granular cognitive computing

Guoyin Wang
2017 Granular Computing  
of machine learning systems which is "from finer to coarser", in a multiple granularity space.  ...  Three main schools of artificial intelligence are formed, that is, symbolism, connectionism and behaviorism. Artificial intelligence is intelligence exhibited by machines.  ...  under Grants 61572091 and 61533020.  ... 
doi:10.1007/s41066-017-0048-3 fatcat:st3kfbsdyzfltoolgmzbazkody

[ICSESS 2019 Front Matter]

2019 2019 IEEE 10th International Conference on Software Engineering and Service Science (ICSESS)  
Computing and Mobile Computing Data Mining & Knowledge Discovery Semantic web and intelligent web RFID System and Application Cloud Computing Machine Learning and Neural Network z Software Engineering  ...  Machine Learning, Decision Support System Neural Networks z Blockchain Technology and Systems Blockchain network and Architecture design Distributed database and ledger design and performance  ... 
doi:10.1109/icsess47205.2019.9040813 fatcat:b7ss6ntz4rfbhmcl3lrzopnrwm

Page 425 of Psychological Abstracts Vol. 83, Issue 1 [page]

1996 Psychological Abstracts  
, self-or- ganization, and cooperativity « Dynamic systems and optimiz- ation « Cooperative phenomena « Self-organization in neural networks e Learning in artificial neural networks « Learning in artificial  ...  neural networks, deterministic « Learning in artificial neural networks, statistical e Computability and complexity « Ap- plications and implementations « Control theory and robotics « Applications of  ... 
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