De La Torre-Abaitua et al., 2020 - Google Patents
On the application of compression-based metrics to identifying anomalous behaviour in web trafficDe La Torre-Abaitua et al., 2020
- Document ID
- 8937475364175768609
- Author
- De La Torre-Abaitua G
- Lago-Fernández L
- Arroyo D
- Publication year
- Publication venue
- Logic Journal of the IGPL
External Links
Snippet
In cybersecurity, there is a call for adaptive, accurate and efficient procedures to identifying performance shortcomings and security breaches. The increasing complexity of both Internet services and traffic determines a scenario that in many cases impedes the proper …
- 238000007906 compression 0 title abstract description 11
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
-
- 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
-
- 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
- H04L63/1491—Countermeasures against malicious traffic using deception as countermeasure, e.g. honeypots, honeynets, decoys or entrapment
-
- 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
- H04L63/30—Network architectures or network communication protocols for network security for supporting lawful interception, monitoring or retaining of communications or communication related information
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US10909241B2 (en) | Event anomaly analysis and prediction | |
Moh et al. | Detecting web attacks using multi-stage log analysis | |
US9900332B2 (en) | Network security system with real-time and batch paths | |
Jerlin et al. | A new malware detection system using machine learning techniques for API call sequences | |
Aminanto et al. | Threat alert prioritization using isolation forest and stacked auto encoder with day-forward-chaining analysis | |
Tran et al. | An approach for host-based intrusion detection system design using convolutional neural network | |
De La Torre-Abaitua et al. | On the application of compression-based metrics to identifying anomalous behaviour in web traffic | |
Liu et al. | A statistical pattern based feature extraction method on system call traces for anomaly detection | |
EP4254198A2 (en) | Event data processing | |
US11601339B2 (en) | Methods and systems for creating multi-dimensional baselines from network conversations using sequence prediction models | |
Morichetta et al. | Clue: Clustering for mining web urls | |
Yang et al. | DEV-ETA: An interpretable detection framework for encrypted malicious traffic | |
EP4254239A1 (en) | Event data processing | |
Kaushik et al. | Network Security with Network Intrusion Detection System using Machine Learning Deployed in a Cloud Infrastructure | |
WO2023192051A1 (en) | System and method for predicting investigation queries based on prior investigations | |
WO2023192037A1 (en) | Event data processing | |
Prasse et al. | Learning explainable representations of malware behavior | |
de la Torre-Abaitua et al. | A parameter-free method for the detection of web attacks | |
Skopik et al. | Detecting unknown cyber security attacks through system behavior analysis | |
US11973775B1 (en) | Monitoring client networks for security threats using recognized machine operations and machine activities | |
US12063224B1 (en) | Network data interpretation pipeline for recognizing machine operations and activities from network sensor data | |
Rihan | Detection of Anomalous Activity Profiles on Windows Machines Utilizing Fuzzy Hashing and Machine Learning | |
Botana et al. | Explanation Method for Anomaly Detection on Mixed Numerical and Categorical Spaces | |
Wang et al. | Design and Implementation of Cyber Space Threat Detection System Based on User Behavioral Logs | |
WO2024025669A1 (en) | Increasing security of a computer program using unstructured text |