Journal ArticleDOI
Application Model of Modern Artificial Neural Network Methods for the Analysis of Information Systems Security
Reads0
Chats0
TLDR
In this work, the representation of security violation as a property of the system described by a complex function is proposed, in which the method of finding violations is described in the form of approximation of that function and the calculation of its values for specific systems.Abstract:
In this work considered the problem of safety analysis of control mechanisms in modern information systems, including control software systems of cyberphysical and industrial facilities, digital control systems for distributed cyber environments VANET, FANET, MARINET, industrial Internet of things and sensor networks. The representation of security violation as a property of the system described by a complex function is proposed, in which the method of finding violations is described in the form of approximation of that function and the calculation of its values for specific systems. Various approaches to the interpolation of such function are considered in the work, it is shown that the most promising option is the use of deep neural networks.read more
Citations
More filters
Proceedings ArticleDOI
Detection of information security breaches in distributed control systems based on values prediction of multidimensional time series
TL;DR: An approach for information security breaches detection in distributed control systems based on prediction of multidimensional time series formed of sensor and actuator data is proposed.
Journal ArticleDOI
Using artificial neural networks when integrating the requirements of standards for management systems in QMS
Journal ArticleDOI
A Review of Artificial Intelligence to Enhance the Security of Big Data Systems: State-of-Art, Methodologies, Applications, and Challenges
Duan Dai,Sahar Boroomand +1 more
TL;DR: This study evaluates the security issues faced by Big data systems using AI techniques focusing on different attacks, defense strategies, and security evaluation models divided into eight categories: reinforcement learning, swarm intelligence, deep learning, multi-agent, game theory, ML, and ANN.
Proceedings ArticleDOI
AI-based Security for the Smart Networks
TL;DR: This study sets a comprehensive approach that aggregates the artificial intelligence (AI) based protection erecting a multimodal intrusion prevention approach that has shown the higher effectiveness than a traditional technique of the intensive data processing.
Proceedings ArticleDOI
A Comprehensive Study on Review of AI Techniques to Provide Security in the Digital World
TL;DR: The paper gives a brief overview of techniques implemented for the security using the fields if Artificial Intelligence (AI), to cover the wide range of algorithms to solve the problem of security theft.
References
More filters
Proceedings ArticleDOI
Going deeper with convolutions
Christian Szegedy,Wei Liu,Yangqing Jia,Pierre Sermanet,Scott Reed,Dragomir Anguelov,Dumitru Erhan,Vincent Vanhoucke,Andrew Rabinovich +8 more
TL;DR: Inception as mentioned in this paper is a deep convolutional neural network architecture that achieves the new state of the art for classification and detection in the ImageNet Large-Scale Visual Recognition Challenge 2014 (ILSVRC14).
Journal Article
Dropout: a simple way to prevent neural networks from overfitting
TL;DR: It is shown that dropout improves the performance of neural networks on supervised learning tasks in vision, speech recognition, document classification and computational biology, obtaining state-of-the-art results on many benchmark data sets.
Journal ArticleDOI
Learning representations by back-propagating errors
TL;DR: Back-propagation repeatedly adjusts the weights of the connections in the network so as to minimize a measure of the difference between the actual output vector of the net and the desired output vector, which helps to represent important features of the task domain.
Journal ArticleDOI
Multilayer feedforward networks are universal approximators
TL;DR: It is rigorously established that standard multilayer feedforward networks with as few as one hidden layer using arbitrary squashing functions are capable of approximating any Borel measurable function from one finite dimensional space to another to any desired degree of accuracy, provided sufficiently many hidden units are available.
Journal ArticleDOI
Multilayer feedforward networks are universal approximators
HornikK.,StinchcombeM.,WhiteH. +2 more