Boero et al., 2017 - Google Patents
Statistical fingerprint‐based intrusion detection system (SF‐IDS)Boero et al., 2017
View PDF- Document ID
- 7236139412543119055
- Author
- Boero L
- Cello M
- Marchese M
- Mariconti E
- Naqash T
- Zappatore S
- Publication year
- Publication venue
- International Journal of Communication Systems
External Links
Snippet
Intrusion detection systems (IDS) are systems aimed at analyzing and detecting security problems. The IDS may be structured into misuse and anomaly detection. The former are often signature/rule IDS that detect malicious software by inspecting the content of packets …
- 238000001514 detection method 0 title abstract description 45
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Khraisat et al. | A critical review of intrusion detection systems in the internet of things: techniques, deployment strategy, validation strategy, attacks, public datasets and challenges | |
Ozkan-Okay et al. | A comprehensive systematic literature review on intrusion detection systems | |
Santhosh Kumar et al. | A Comprehensive Survey on Machine Learning‐Based Intrusion Detection Systems for Secure Communication in Internet of Things | |
US20220224716A1 (en) | User agent inference and active endpoint fingerprinting for encrypted connections | |
Oprea et al. | Made: Security analytics for enterprise threat detection | |
Idhammad et al. | Detection system of HTTP DDoS attacks in a cloud environment based on information theoretic entropy and random forest | |
Hajj et al. | Anomaly‐based intrusion detection systems: The requirements, methods, measurements, and datasets | |
García et al. | Survey on network‐based botnet detection methods | |
Bijone | A survey on secure network: intrusion detection & prevention approaches | |
US11457031B1 (en) | Apparatus having engine using artificial intelligence for detecting bot anomalies in a computer network | |
Boero et al. | Statistical fingerprint‐based intrusion detection system (SF‐IDS) | |
Moustafa | Designing an online and reliable statistical anomaly detection framework for dealing with large high-speed network traffic | |
Stevanovic et al. | Machine learning for identifying botnet network traffic | |
Lawal et al. | Security analysis of network anomalies mitigation schemes in IoT networks | |
Kumar et al. | Intrusion detection systems: a review | |
Deka et al. | Network defense: Approaches, methods and techniques | |
Rizvi et al. | Application of artificial intelligence to network forensics: Survey, challenges and future directions | |
Nazir et al. | Network intrusion detection: Taxonomy and machine learning applications | |
Verma et al. | A detailed survey of denial of service for IoT and multimedia systems: Past, present and futuristic development | |
Le et al. | Unsupervised monitoring of network and service behaviour using self organizing maps | |
Hagar et al. | Big Data Analytic Using Machine Learning Algorithms For Intrusion Detection System: A Survey | |
Hamzenejadi et al. | Mobile botnet detection: a comprehensive survey | |
Rimmer et al. | Open-world network intrusion detection | |
Beg et al. | Feasibility of intrusion detection system with high performance computing: A survey | |
Alauthman | An efficient approach to online bot detection based on a reinforcement learning technique |