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Application of deep learning to enhance the accuracy of intrusion detection in modern computer networks

Jafar Majidpour, Hiwa Hasanzadeh
2020 Bulletin of Electrical Engineering and Informatics  
Application of deep learning to enhance the accuracy of intrusion detection in modern computer networks were studied in this paper.  ...  Intrusion detection is not a proper title for intrusion detection systems, because these systems really detect infiltration.  ...  Network-based intrusion detection systems require a password for applications, salaries It is not related to the network operating system or system connections when running the software.  ... 
doi:10.11591/eei.v9i3.1724 fatcat:qyss2zyrijc6biebrp6dgy6lpy

Ten AI Stepping Stones for Cybersecurity [article]

Ricardo Morla
2019 arXiv   pre-print
This paper discusses ten issues in cybersecurity that hopefully will make it easier for practitioners to ask detailed questions about what they want from an AI system in their cybersecurity operations.  ...  We then discuss the use of AI by attackers on a level playing field including several issues in an AI battlefield, and an AI perspective on the old cat-and-mouse game including how the adversary may assess  ...  If you're looking for examples of adversarial attacks to deep learning intrusion detection systems and malware detection, start here: [27] assumes a continuous learning autoencoder-based intrusion detection  ... 
arXiv:1912.06817v1 fatcat:ujeitni5grcopbhl6dwenncjje

1D CNN Based Network Intrusion Detection with Normalization on Imbalanced Data [article]

Azizjon Meliboev, Jumabek Alikhanov, Wooseong Kim
2020 arXiv   pre-print
Intrusion detection system (IDS) plays an essential role in computer networks protecting computing resources and data from outside attacks.  ...  Deep neural network (DNN) is considered popularly for complex systems to abstract features and learn as a machine learning technique.  ...  INTRODUCTION Intrusion Detection System (IDS) is an essential tool for the cybersecurity to detect various security threatens in computer networks.  ... 
arXiv:2003.00476v2 fatcat:wayig6yihbbsjnd62shfyrn6ri

A survey of neural networks usage for intrusion detection systems

Anna Drewek-Ossowicka, Mariusz Pietrołaj, Jacek Rumiński
2020 Journal of Ambient Intelligence and Humanized Computing  
Intrusion detection system (IDS) presents one of the domains in which neural networks are widely tested for improving overall computer network security and data privacy.  ...  This article gives a thorough overview of recent literature regarding neural networks usage in intrusion detection system area, including surveys and new method proposals.  ...  Intrusion detection systems and machine learning Intrusion detection system Intrusion detection systems are entities for auditing systems and network operations against hostile actions and policy violations  ... 
doi:10.1007/s12652-020-02014-x fatcat:3caiis3mf5ejfgdzopsjxf57zq

Detection of Intruder in Cloud Computing Environment using Swarm Inspired based Neural Network

Nishika -, Kamna Solanki, Sandeep Dalal
2021 International Journal of Advanced Computer Science and Applications  
Keywords-Cloud computing; intrusion detection system; cuckoo search; feed forward back propagation neural network (FFBPNN)  ...  Therefore, it is necessary to design an accurate Intrusion Detection System (IDS) to identify the suspected node in the cloud computing environment.  ...  This is possible through the utilization of the Intrusion Detection System (IDS). A suspicious entry in the network is known as an intrusion [6] .  ... 
doi:10.14569/ijacsa.2021.0120952 fatcat:fovbioookvefxcsupefeofz2am

Network Intrusion Detection Using Neural Networks on FPGA SoCs

Lenos Ioannou, Suhaib A. Fahmy
2019 2019 29th International Conference on Field Programmable Logic and Applications (FPL)  
We present an approach for network intrusion detection using neural networks, implemented on FPGA SoC devices that can achieve the required performance on embedded devices.  ...  Network security is increasing in importance as systems become more interconnected.  ...  ACKNOWLEDGEMENT This work was supported in part by an IBM Faculty Award and the UK Engineering and Physical Sciences Research Council (EPSRC), grant EP/N509796/1.  ... 
doi:10.1109/fpl.2019.00043 dblp:conf/fpl/IoannouF19 fatcat:3ugthbp4fvduldxvnom3qshvxi

A chipset level network backdoor

Sherri Sparks, Shawn Embleton, Cliff C. Zou
2009 Proceedings of the 4th International Symposium on Information, Computer, and Communications Security - ASIACCS '09  
Because of its low-level position in a computer system, the backdoor is capable of bypassing virtually all commodity firewall and host-based intrusion detection software, including popular, widely deployed  ...  The network backdoor has the ability to both covertly send out packets and receive packets, without the need to disable security software installed in the compromised host in order to hide its presence  ...  Our data infiltration experiments test the ability to intercept network packets before they reach any software firewall or Intrusion Detection System (IDS).  ... 
doi:10.1145/1533057.1533076 dblp:conf/ccs/SparksEZ09 fatcat:w6m66pzn6ffs7nzlbpk27dchki

Forget the Myth of the Air Gap: Machine Learning for Reliable Intrusion Detection in SCADA Systems

Rocio Lopez Perez, Florian Adamsky, Ridha Soua, Thomas Engel
2018 EAI Endorsed Transactions on Security and Safety  
However, traditional Intrusion Detection Systems (IDSs) cannot detect attacks that are not already present in their databases.  ...  To this end, we assess in this paper Machine Learning (ML) techniques for anomaly detection in SCADA systems using a real data set collected from a gas pipeline system and provided by the Mississippi State  ...  We thank Dominic Dunlop for his review and comments that greatly improved the manuscript.  ... 
doi:10.4108/eai.25-1-2019.159348 fatcat:mgvwzwmny5cfxfguo5pkerujbi

Monitoring the behaviours of pet cat based on YOLO model and raspberry Pi

Rung-Ching Chen, Vani Suthamathi Saravanarajan, Hsiu-Te Hung
2021 International Journal of Applied Science and Engineering  
partially sponsored by Chaoyang University of Technology (CYUT) and Higher Education Sprout Project, Ministry of Education (MOE), Taiwan, under the project name: "The R&D and the cultivation of talent for  ...  Deep Learning Deep learning is a new field developed from artificial neural networks in machine learning.  ...  In terms of home, (Nadafa et al., 2020) proposed a smart mirror with a home intrusion detection system, using Raspberry Pi as a model and using (Viola and Jones, 2001) classifier to detect faces and  ... 
doi:10.6703/ijase.202109_18(5).016 fatcat:5kypuawl5vewhhbv3inwd2ny6e

Smart attendance system using Convolution Neural Network and Image Processing

Senigala Kuruba ChayaDevi, Vamsi Agnihotram
2020 European Journal of Engineering Research and Science  
Image recognition is playing an important role in the modern living like driver assistance systems, medical imaging system, quality control system to name a few.  ...  been proposed in this paper to overcome the disadvantages of the previous algorithms.  ...  B.V Doraswamy, scientist 'F', DMRL, DRDO for assistance in Convolution neural networks, and my family for support. With pleasure, we record our sincere gratitude to our Head of the Department Dr. K.  ... 
doi:10.24018/ejers.2020.5.5.1865 fatcat:rjbafqapgjhzhlbq76qznnibvy

Smart attendance system using Convolution Neural Network and Image Processing

Senigala Kuruba ChayaDevi, Vamsi Agnihotram
2020 European Journal of Engineering and Technology Research  
Image recognition is playing an important role in the modern living like driver assistance systems, medical imaging system, quality control system to name a few.  ...  been proposed in this paper to overcome the disadvantages of the previous algorithms.  ...  cats in other images.  ... 
doi:10.24018/ejeng.2020.5.5.1865 fatcat:mvde5a4xvrbqldlufwfwu2awiu

Unknown Security Attack Detection Using Shallow and Deep ANN Classifiers

Malek Al-Zewairi, Sufyan Almajali, Moussa Ayyash
2020 Electronics  
using two well-known benchmark datasets for network intrusion detection.  ...  The researchers conducted several experiments and evaluated modern intrusion detection systems based on shallow and deep artificial neural network models and their ability to detect Type-A and Type-B attacks  ...  Conclusions An intrusion detection system is an effective tool for detecting potential security threats and violations.  ... 
doi:10.3390/electronics9122006 fatcat:2tmztjx7ljanbcc7hcmx2xhv5i

Towards Detecting and Classifying Network Intrusion Traffic Using Deep Learning Frameworks

Ram B. Basnet, Riad Shash, Clayton Johnson, Lucas Walgren, Tenzin Doleck
2019 Journal of Internet Services and Information Security  
We apply and compare various state-of-the-art deep learning frameworks (e.g., Keras, TensorFlow, Theano, fast.ai, and PyTorch) in detecting network intrusion traffic and also in classifying common network  ...  Our results provide evidence of the utility of various deep learning frameworks detecting network intrusion traffic.  ...  Acknowledgment This research project was supported by the state of Colorado through funds appropriated for cybersecurity law dubbed "Cyber Coding Cryptology for State Records."  ... 
doi:10.22667/jisis.2019.11.30.001 dblp:journals/jisis/BasnetSJWD19 fatcat:xzzxwqpzjzhiffdsxi6237n3qi

Development of the ECAT Preprocessor with the Trust Communication Approach

Kevser Ovaz Akpinar, Ibrahim Ozcelik
2018 Security and Communication Networks  
To prevent, detect, and reduce attacks over the EtherCAT-based critical systems, first, we improved the open-source Snort intrusion detection/prevention system (IDS/IPS) to support packets that are not  ...  The most common objectives of these types of attacks are controlling/monitoring the physical process, manipulating programmable controllers, or affecting the integrity of software and networking equipment  ...  Snort IDS/IPS on Industrial Automation Systems Snort, commonly accepted as an IDS/IPS system, is opensource software used for detecting or preventing anomalies within the network.  ... 
doi:10.1155/2018/2639750 fatcat:2onppwanq5h6rafp2hdhv5me6a

SafeSearch: Obfuscated VPN Server using Raspberry Pi for Secure Network

Mohd Faris Mohd Fuzi, Mohamad Ridzuan Mohd Alias, Naginder Kaur, Iman Hazwam Abd Halim
2021 Journal of Computing Research and Innovation  
In this study, open VPN protocol was used to create the VPN server on a microcomputer called Raspberry Pi. The software used was mostly open-source except for the VPN client.  ...  Nowadays, users can either pay a premium price for a good VPN service or risk their privacy using free browser-based VPN. Thus, SafeSearch is developed to address these issues in mind.  ...  also developed an integrated tool that implemented OpenVPN protocol, DNS blocker and Intrusion Detection System (IDS) known as NetGuard. The researchers used Raspberry Pi to develop the system.  ... 
doi:10.24191/jcrinn.v6i4.230 fatcat:7ccoxv5aj5hejldaiud36mbjje
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