[go: up one dir, main page]

Barbhuiya et al., 2021 - Google Patents

Linear Regression Based DDoS Attack Detection

Barbhuiya et al., 2021

Document ID
9247625329381466471
Author
Barbhuiya S
Kilpatrick P
S. Nikolopoulos D
Publication year
Publication venue
Proceedings of the 2021 13th International Conference on Machine Learning and Computing

External Links

Snippet

DDoS attacks are increasing alongside the growth of web-based services. Existing research proposes a number of anomaly-based techniques which analyse network traffic to detect such attacks. However, these techniques typically raise a number of false positives …
Continue reading at dl.acm.org (other versions)

Classifications

    • 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
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00Data switching networks
    • H04L12/02Details
    • H04L12/26Monitoring arrangements; Testing arrangements
    • H04L12/2602Monitoring arrangements
    • 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
    • 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
    • H04L63/1458Denial of Service
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00Arrangements for maintenance or administration or management of packet switching networks
    • H04L41/14Arrangements for maintenance or administration or management of packet switching networks involving network analysis or design, e.g. simulation, network model or planning
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00Arrangements for monitoring or testing packet switching networks
    • H04L43/08Monitoring based on specific metrics
    • 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
    • H04L43/00Arrangements for monitoring or testing packet switching networks
    • H04L43/02Arrangements for monitoring or testing packet switching networks involving a reduction of monitoring data

Similar Documents

Publication Publication Date Title
CN106341414B (en) A multi-step attack security situation assessment method based on Bayesian network
Lazarevic et al. A comparative study of anomaly detection schemes in network intrusion detection
Joshi et al. A review of network traffic analysis and prediction techniques
US8418247B2 (en) Intrusion detection method and system
Palmieri et al. A distributed approach to network anomaly detection based on independent component analysis
Wang A multinomial logistic regression modeling approach for anomaly intrusion detection
US20090245109A1 (en) Methods, systems and computer program products for detecting flow-level network traffic anomalies via abstraction levels
Aborujilah et al. Cloud‐Based DDoS HTTP Attack Detection Using Covariance Matrix Approach
Kato et al. An intelligent ddos attack detection system using packet analysis and support vector machine
Soleimani et al. Multi-layer episode filtering for the multi-step attack detection
Dhakar et al. A novel data mining based hybrid intrusion detection framework
Niknami et al. Entropy-kl-ml: Enhancing the entropy-kl-based anomaly detection on software-defined networks
Kornyo et al. Botnet attacks classification in AMI networks with recursive feature elimination (RFE) and machine learning algorithms
Angelini et al. An attack graph-based on-line multi-step attack detector
Brandao et al. Log Files Analysis For Network Intrusion Detection
Alhaidari et al. Network traffic anomaly detection based on Viterbi algorithm using SNMP MIB data
Li et al. Distributed threat intelligence sharing system: a new sight of P2P botnet detection
Sait et al. Multi-level anomaly detection: Relevance of big data analytics in networks
Barbhuiya et al. Linear Regression Based DDoS Attack Detection
Chakir et al. An efficient method for evaluating alerts of Intrusion Detection Systems
Maharaj et al. A comparative analysis of different classification techniques for intrusion detection system
Nehinbe Log Analyzer for Network Forensics and Incident Reporting
Farid et al. Learning intrusion detection based on adaptive bayesian algorithm
Rastogi et al. Network anomalies detection using statistical technique: a chi-square approach
Kumar et al. Intrusion detection system using stream data mining and drift detection method