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

Javeed et al., 2021 - Google Patents

SDN-enabled hybrid DL-driven framework for the detection of emerging cyber threats in IoT

Javeed et al., 2021

View HTML
Document ID
13893039663040911202
Author
Javeed D
Gao T
Khan M
Publication year
Publication venue
Electronics

External Links

Snippet

The Internet of Things (IoT) has proven to be a billion-dollar industry. Despite offering numerous benefits, the prevalent nature of IoT makes it vulnerable and a possible target for the development of cyber-attacks. The diversity of the IoT, on the one hand, leads to the …
Continue reading at www.mdpi.com (HTML) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/01—Social networking
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/50—Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
    • G06F21/55—Detecting local intrusion or implementing counter-measures
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
    • H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/10—Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/10—Services
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F15/00—Digital computers in general; Data processing equipment in general
    • G06F15/16—Combinations of two or more digital computers each having at least an arithmetic unit, a programme unit and a register, e.g. for a simultaneous processing of several programmes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints

Similar Documents

Publication Publication Date Title
Javeed et al. SDN-enabled hybrid DL-driven framework for the detection of emerging cyber threats in IoT
Awajan A novel deep learning-based intrusion detection system for IOT networks
Vaccari et al. MQTTset, a new dataset for machine learning techniques on MQTT
Rashid et al. Cyberattacks detection in iot-based smart city applications using machine learning techniques
Dey et al. Effects of machine learning approach in flow-based anomaly detection on software-defined networking
Ali et al. Threat analysis and distributed denial of service (DDoS) attack recognition in the internet of things (IoT)
Tuan et al. A DDoS attack mitigation scheme in ISP networks using machine learning based on SDN
Kim et al. Intelligent detection of iot botnets using machine learning and deep learning
Chaganti et al. A particle swarm optimization and deep learning approach for intrusion detection system in internet of medical things
Soe et al. Towards a lightweight detection system for cyber attacks in the IoT environment using corresponding features
Fotiadou et al. Network traffic anomaly detection via deep learning
Abbas et al. Safety, security and privacy in machine learning based internet of things
Pinto et al. Survey on intrusion detection systems based on machine learning techniques for the protection of critical infrastructure
Javed et al. An intelligent system to detect advanced persistent threats in industrial internet of things (I-IoT)
Taheri et al. Leveraging image representation of network traffic data and transfer learning in botnet detection
Nikoloudakis et al. Towards a machine learning based situational awareness framework for cybersecurity: an SDN implementation
Ali et al. Low rate DDoS detection using weighted federated learning in SDN control plane in IoT network
Bahaa et al. Monitoring real time security attacks for IoT systems using DevSecOps: a systematic literature review
Elubeyd et al. Hybrid deep learning approach for automatic DoS/DDoS attacks detection in software-defined networks
de Caldas Filho et al. Botnet detection and mitigation model for IoT networks using federated learning
Yaser et al. Improved DDoS detection utilizing deep neural networks and feedforward neural networks as autoencoder
Li et al. Investigating the influence of special on–off attacks on challenge-based collaborative intrusion detection networks
Alabsi et al. Conditional tabular generative adversarial based intrusion detection system for detecting ddos and dos attacks on the internet of things networks
Liu et al. Real-time anomaly detection of network traffic based on CNN
Jove et al. Intelligent one-class classifiers for the development of an intrusion detection system: the mqtt case study