Sudqi Khater et al., 2019 - Google Patents
A lightweight perceptron-based intrusion detection system for fog computingSudqi Khater et al., 2019
View HTML- Document ID
- 14366689733528397724
- Author
- Sudqi Khater B
- Abdul Wahab A
- Idris M
- Abdulla Hussain M
- Ahmed Ibrahim A
- Publication year
- Publication venue
- applied sciences
External Links
Snippet
Fog computing is a paradigm that extends cloud computing and services to the edge of the network in order to address the inherent problems of the cloud, such as latency and lack of mobility support and location-awareness. The fog is a decentralized platform capable of …
- 238000001514 detection method 0 title abstract description 65
Classifications
-
- 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
- H04L63/1441—Countermeasures against malicious traffic
- H04L63/1458—Denial of Service
-
- 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
- H04L63/1441—Countermeasures against malicious traffic
- H04L63/145—Countermeasures against malicious traffic the attack involving the propagation of malware through the network, e.g. viruses, trojans or worms
-
- 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
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network-specific arrangements or communication protocols supporting networked applications
- H04L67/10—Network-specific arrangements or communication protocols supporting networked applications in which an application is distributed across nodes in the network
-
- 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
- H04L63/02—Network architectures or network communication protocols for network security for separating internal from external traffic, e.g. firewalls
- H04L63/0209—Architectural arrangements, e.g. perimeter networks or demilitarized zones
- H04L63/0218—Distributed architectures, e.g. distributed firewalls
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network-specific arrangements or communication protocols supporting networked applications
- H04L67/28—Network-specific arrangements or communication protocols supporting networked applications for the provision of proxy services, e.g. intermediate processing or storage in the network
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Sudqi Khater et al. | A lightweight perceptron-based intrusion detection system for fog computing | |
Ali et al. | Threat analysis and distributed denial of service (DDoS) attack recognition in the internet of things (IoT) | |
Abu Al-Haija et al. | ELBA-IoT: An ensemble learning model for botnet attack detection in IoT networks | |
Alzaqebah et al. | A modified grey wolf optimization algorithm for an intrusion detection system | |
Dhaliwal et al. | Effective intrusion detection system using XGBoost | |
Oliveira et al. | Intelligent cyber attack detection and classification for network-based intrusion detection systems | |
Alghazzawi et al. | Efficient detection of DDoS attacks using a hybrid deep learning model with improved feature selection | |
Albulayhi et al. | IoT intrusion detection taxonomy, reference architecture, and analyses | |
Zhong et al. | Sequential model based intrusion detection system for IoT servers using deep learning methods | |
Qaddoura et al. | A multi-layer classification approach for intrusion detection in iot networks based on deep learning | |
Qaddoura et al. | A multi-stage classification approach for iot intrusion detection based on clustering with oversampling | |
Chaganti et al. | A particle swarm optimization and deep learning approach for intrusion detection system in internet of medical things | |
Alkahtani et al. | Artificial intelligence algorithms for malware detection in android-operated mobile devices | |
Tareq et al. | Analysis of ton-iot, unw-nb15, and edge-iiot datasets using dl in cybersecurity for iot | |
Liu et al. | Adversarial samples on android malware detection systems for IoT systems | |
Rodríguez et al. | Transfer-learning-based intrusion detection framework in IoT networks | |
Ashraf et al. | A deep learning-based smart framework for cyber-physical and satellite system security threats detection | |
Javed et al. | An intelligent system to detect advanced persistent threats in industrial internet of things (I-IoT) | |
Alotaibi et al. | Ensemble-learning framework for intrusion detection to enhance internet of things’ devices security | |
Azeez et al. | Network intrusion detection with a hashing based apriori algorithm using Hadoop MapReduce | |
Khater et al. | Classifier performance evaluation for lightweight IDS using fog computing in IoT security | |
Musafer et al. | An enhanced design of sparse autoencoder for latent features extraction based on trigonometric simplexes for network intrusion detection systems | |
Ding et al. | A hybrid analysis-based approach to android malware family classification | |
Alosaimi et al. | An intrusion detection system using BoT-IoT | |
Alalhareth et al. | An improved mutual information feature selection technique for intrusion detection systems in the Internet of Medical Things |