[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Halbouni et al., 2022 - Google Patents

Machine learning and deep learning approaches for cybersecurity: A review

Halbouni et al., 2022

View PDF
Document ID
11011357619382488733
Author
Halbouni A
Gunawan T
Habaebi M
Halbouni M
Kartiwi M
Ahmad R
Publication year
Publication venue
IEEE Access

External Links

Snippet

The rapid evolution and growth of the internet through the last decades led to more concern about cyber-attacks that are continuously increasing and changing. As a result, an effective intrusion detection system was required to protect data, and the discovery of artificial …
Continue reading at ieeexplore.ieee.org (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F21/00Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/50Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
    • G06F21/55Detecting local intrusion or implementing counter-measures
    • G06F21/56Computer malware detection or handling, e.g. anti-virus arrangements
    • G06F21/562Static detection
    • G06F21/563Static detection by source code analysis
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/14Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1408Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
    • H04L63/1425Traffic logging, e.g. anomaly detection
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/14Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1408Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
    • H04L63/1416Event detection, e.g. attack signature detection
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F21/00Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/50Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
    • G06F21/55Detecting local intrusion or implementing counter-measures
    • G06F21/552Detecting local intrusion or implementing counter-measures involving long-term monitoring or reporting
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F21/00Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/50Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
    • G06F21/55Detecting local intrusion or implementing counter-measures
    • G06F21/554Detecting local intrusion or implementing counter-measures involving event detection and direct action
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/14Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1441Countermeasures against malicious traffic
    • H04L63/145Countermeasures against malicious traffic the attack involving the propagation of malware through the network, e.g. viruses, trojans or worms
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F21/00Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/50Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
    • G06F21/57Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
    • G06F21/577Assessing vulnerabilities and evaluating computer system security
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/14Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1433Vulnerability analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/02Knowledge representation
    • G06N5/022Knowledge engineering, knowledge acquisition
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00Network architectures or network communication protocols for network security
    • H04L63/20Network architectures or network communication protocols for network security for managing network security; network security policies in general
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00Computer systems based on specific mathematical models
    • G06N7/005Probabilistic networks
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F2221/00Indexing scheme relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity

Similar Documents

Publication Publication Date Title
Halbouni et al. Machine learning and deep learning approaches for cybersecurity: A review
Khraisat et al. A critical review of intrusion detection systems in the internet of things: techniques, deployment strategy, validation strategy, attacks, public datasets and challenges
Khraisat et al. Survey of intrusion detection systems: techniques, datasets and challenges
Ravi et al. Recurrent deep learning-based feature fusion ensemble meta-classifier approach for intelligent network intrusion detection system
Khammassi et al. A GA-LR wrapper approach for feature selection in network intrusion detection
Bharadiya Machine learning in cybersecurity: Techniques and challenges
Subbiah et al. Intrusion detection technique in wireless sensor network using grid search random forest with Boruta feature selection algorithm
Khanday et al. Implementation of intrusion detection model for DDoS attacks in Lightweight IoT Networks
Ahmetoglu et al. A comprehensive review on detection of cyber-attacks: Data sets, methods, challenges, and future research directions
Fraihat et al. Intrusion detection system for large-scale IoT NetFlow networks using machine learning with modified Arithmetic Optimization Algorithm
Moghanian et al. GOAMLP: Network intrusion detection with multilayer perceptron and grasshopper optimization algorithm
Kilincer et al. A comprehensive intrusion detection framework using boosting algorithms
Hammad et al. T‐SNERF: A novel high accuracy machine learning approach for Intrusion Detection Systems
Saheed et al. A voting gray wolf optimizer-based ensemble learning models for intrusion detection in the Internet of Things
Dixit et al. Comparing and analyzing applications of intelligent techniques in cyberattack detection
Shahin et al. Advancing network security in industrial IoT: a deep dive into AI-enabled intrusion detection systems
Bhati et al. A survey on hybrid intrusion detection techniques
Monshizadeh et al. Security related data mining
Rajasekaran et al. Malicious attacks detection using GRU-BWFA classifier in pervasive computing
Selim et al. DAE-BILSTM: A Fog-Based Intrusion Detection Model Using Deep Learning for IoT
Almomani et al. Reconnaissance attack detection via boosting machine learning classifiers
Parhizkari Anomaly detection in intrusion detection systems
Rafsanjani et al. Intrusion detection by data mining algorithms: a review
Al-Fawa'reh et al. Detecting malicious dns queries over encrypted tunnels using statistical analysis and bi-directional recurrent neural networks
Rani et al. Analysis of machine learning and deep learning intrusion detection system in Internet of Things network