Ouarda et al., 2023 - Google Patents
Towards a better similarity algorithm for host-based intrusion detection systemOuarda et al., 2023
View HTML- Document ID
- 16033973871764003863
- Author
- Ouarda L
- Malika B
- Brahim B
- Publication year
- Publication venue
- Journal of Intelligent Systems
External Links
Snippet
An intrusion detection system plays an essential role in system security by discovering and preventing malicious activities. Over the past few years, several research projects on host- based intrusion detection systems (HIDSs) have been carried out utilizing the Australian …
Classifications
-
- 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
- G06F21/563—Static detection by source code analysis
-
- 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
-
- 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
- G06F21/566—Dynamic detection, i.e. detection performed at run-time, e.g. emulation, suspicious activities
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Vinayakumar et al. | Evaluating deep learning approaches to characterize and classify malicious URL’s | |
| Hassen et al. | Scalable function call graph-based malware classification | |
| Vinayakumar et al. | Evaluating deep learning approaches to characterize and classify the DGAs at scale | |
| US8370278B2 (en) | Ontological categorization of question concepts from document summaries | |
| Zhong et al. | Graph embeddings on gene ontology annotations for protein–protein interaction prediction | |
| Ouarda et al. | Towards a better similarity algorithm for host-based intrusion detection system | |
| Palahan et al. | Extraction of statistically significant malware behaviors | |
| Canfora et al. | Metamorphic malware detection using code metrics | |
| Xu et al. | Protranslator: zero-shot protein function prediction using textual description | |
| Ashik et al. | Detection of malicious software by analyzing distinct artifacts using machine learning and deep learning algorithms | |
| Liu et al. | Multifamily classification of Android malware with a fuzzy strategy to resist polymorphic familial variants | |
| Pentel | Predicting user age by keystroke dynamics | |
| De Vine et al. | Analysis of word embeddings and sequence features for clinical information extraction | |
| Yan et al. | Automatic malware classification via PRICoLBP | |
| Yang et al. | Android malware detection method based on highly distinguishable static features and DenseNet | |
| Sutoyo et al. | Detecting documents plagiarism using winnowing algorithm and k-gram method | |
| Aljofey et al. | A supervised learning model for detecting Ponzi contracts in Ethereum Blockchain | |
| Wang et al. | Metmap: Metamorphic testing for detecting false vector matching problems in LLM augmented generation | |
| Domschot et al. | Improving automated labeling for att&ck tactics in malware threat reports | |
| Uhlig et al. | Combining AI and AM–Improving approximate matching through transformer networks | |
| Shin et al. | System API vectorization for malware detection | |
| Panda et al. | An ensemble approach for imbalanced multiclass malware classification using 1D-CNN | |
| Huang et al. | TagSeq: Malicious behavior discovery using dynamic analysis | |
| Bonifro et al. | Content-based textual file type detection at scale | |
| Hai et al. | An efficient classification of malware behavior using deep neural network |