Αποτελέσματα Αναζήτησης
10 Μαΐ 2022 · Hybrid is a technique that combines misuse-based and anomaly-based techniques [5]. The hybrid technique resolves the disadvantages of the two legacy IDSs. Research shows that hybrid detection systems have better performance compared to single IDS.
17 Ιαν 2020 · Single classifier IDSs are unable to achieve high accuracy and low false alarm rates due to polymorphic, metamorphic, and zero-day behaviors of malware. In this paper, a Hybrid IDS (HIDS) is proposed by combining the C5 decision tree classifier and One Class Support Vector Machine (OC-SVM).
1 Ιουλ 2019 · In this study, a hybrid and layered Intrusion Detection System (IDS) is proposed that uses a combination of different machine learning and feature selection techniques to provide high...
Intrusion detection systems (IDS) are designed to detect specific issues, and are categorized as signature-based (SIDS) or anomaly-based (AIDS). IDS can be software or hardware. How do SIDS and AIDS detect malicious activity? What is the difference between the two? What are the four IDS evasion techniques discussed, and how do they evade an IDS?
12 Ιαν 2024 · This paper proposes a model (known as “AS-IDS”) that combines these two approaches to detect known and unknown attacks in IoT networks. The proposed model has three phases: traffic...
4 Φεβ 2019 · In this study, a hybrid and layered Intrusion Detection System (IDS) is proposed that uses a combination of different machine learning and feature selection techniques to provide high performance intrusion detection in different attack types.
13 Μαρ 2021 · In this research, the Suricata IDS/IPS is deployed along with the NN model for the metaheuristic's manual detection of malicious traffic in the targeted network. For the metaheuristic-based...
