He et al., 2022 - Google Patents
A bi-layer intrusion detection based on device behavior profiling for smart home iotHe et al., 2022
- Document ID
- 3043665203514229881
- Author
- He F
- Tong F
- Zhang Y
- Publication year
- Publication venue
- 2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems (MASS)
External Links
Snippet
The Internet of Things (IoT), which has played a significant role in various scenarios nowadays, is increasing in popularity and facilitating human life. However, IoT devices are vulnerable due to their inadequate security defense mechanisms and increasing security …
- 238000001514 detection method 0 title abstract description 52
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
- H04L63/1408—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic by monitoring network traffic
- H04L63/1425—Traffic logging, e.g. anomaly detection
-
- 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
- H04L63/1416—Event detection, e.g. attack signature detection
-
- 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
- G06F21/552—Detecting local intrusion or implementing counter-measures involving long-term monitoring or reporting
-
- 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
- G06F21/56—Computer malware detection or handling, e.g. anti-virus arrangements
- G06F21/562—Static detection
-
- 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
-
- 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
- G06F21/554—Detecting local intrusion or implementing counter-measures involving event detection and direct action
-
- 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
- H04L63/1433—Vulnerability analysis
-
- 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
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/02—Details
- H04L12/26—Monitoring arrangements; Testing arrangements
- H04L12/2602—Monitoring arrangements
-
- 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
- H04L63/0227—Filtering policies
-
- 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
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Desai et al. | A feature-ranking framework for IoT device classification | |
Pektaş et al. | Botnet detection based on network flow summary and deep learning | |
Miah et al. | Improving detection accuracy for imbalanced network intrusion classification using cluster-based under-sampling with random forests | |
Procopiou et al. | ForChaos: Real time application DDoS detection using forecasting and chaos theory in smart home IoT network | |
Chen et al. | An efficient network intrusion detection | |
Alsajri et al. | Intrusion detection system based on machine learning algorithms:(SVM and genetic algorithm) | |
Cid-Fuentes et al. | An adaptive framework for the detection of novel botnets | |
Duan et al. | A novel and highly efficient botnet detection algorithm based on network traffic analysis of smart systems | |
Khoei et al. | Boosting-based models with tree-structured parzen estimator optimization to detect intrusion attacks on smart grid | |
Wang et al. | Attack detection analysis in software-defined networks using various machine learning method | |
Razdan et al. | Performance analysis of network intrusion detection systems using j48 and naive bayes algorithms | |
Dubey et al. | A novel approach to intrusion detection system using rough set theory and incremental SVM | |
Soewu et al. | Analysis of Data Mining-Based Approach for Intrusion Detection System | |
Almomani et al. | Reconnaissance attack detection via boosting machine learning classifiers | |
Yu Beng et al. | A survey of intrusion alert correlation and its design considerations | |
Ahanger et al. | Intrusion detection system for iot environment using ensemble approaches | |
Aleroud et al. | Context infusion in semantic link networks to detect cyber-attacks: a flow-based detection approach | |
Rudro et al. | Enhancing ddos attack detection using machine learning: A framework with feature selection and comparative analysis of algorithms | |
Su et al. | False alert buster: An adaptive approach for NIDS false alert filtering | |
Thamaraimanalan et al. | ANFIS-based multilayered algorithm for botnet detection | |
He et al. | A bi-layer intrusion detection based on device behavior profiling for smart home iot | |
Farid et al. | Learning intrusion detection based on adaptive bayesian algorithm | |
Amin et al. | Ensemble based effective intrusion detection system for cloud environment over UNSW-NB15 dataset | |
Yange et al. | A data analytics system for network intrusion detection using decision tree | |
Sharma et al. | Comparative Analysis of Machine Learning Models for Intrusion Detection Systems |