[go: up one dir, main page]

Smith et al., 2023 - Google Patents

Supervised feature selection to improve the accuracy for malware detection

Smith et al., 2023

Document ID
17411400159865529905
Author
Smith D
Khorsandroo S
Roy K
Publication year

External Links

Snippet

Malware is becoming increasingly sophisticated and difficult to detect with traditional monitoring tools and antivirus software. As a result, machine learning has become a popular approach for classifying and detecting malware-related data. In this study, two distinct …
Continue reading at www.researchsquare.com (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30861Retrieval from the Internet, e.g. browsers
    • G06F17/30864Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems
    • G06F17/30867Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems with filtering and personalisation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/3061Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F17/30705Clustering or classification
    • G06F17/30707Clustering or classification into predefined classes
    • 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
    • G06F21/56Computer malware detection or handling, e.g. anti-virus arrangements
    • G06F21/562Static detection
    • 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
    • G06F21/57Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
    • G06F21/577Assessing vulnerabilities and evaluating computer system security
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • 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
    • 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • 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
    • H04L63/1433Vulnerability analysis

Similar Documents

Publication Publication Date Title
Patil et al. Malicious URLs detection using decision tree classifiers and majority voting technique
Daoudi et al. A deep dive inside drebin: An explorative analysis beyond android malware detection scores
Li et al. Live-streaming fraud detection: A heterogeneous graph neural network approach
Ye et al. Hierarchical associative classifier (HAC) for malware detection from the large and imbalanced gray list
Pitolli et al. MalFamAware: automatic family identification and malware classification through online clustering
Ujah-Ogbuagu et al. A hybrid deep learning technique for spoofing website URL detection in real-time applications
Deore et al. Intrusion detection system based on RNN classifier for feature reduction
Adnan et al. Beyond Beall's blacklist: automatic detection of open access predatory research journals
Kasim Automatic detection of phishing pages with event-based request processing, deep-hybrid feature extraction and light gradient boosted machine model
Cohen et al. Website categorization via design attribute learning
CN117574374A (en) Malicious access identification methods, equipment, storage media and devices
Sarasjati et al. Comparative study of classification algorithms for website phishing detection on multiple datasets
Smith et al. Supervised feature selection to improve the accuracy for malware detection
Carragher et al. Detection and discovery of misinformation sources using attributed webgraphs
Wen et al. An imbalanced learning method based on graph tran-smote for fraud detection
Newaz et al. A sophisticated framework for the accurate detection of phishing websites
Smith et al. Leveraging feature selection to improve the accuracy for malware detection
Krishnaveni et al. Phishing Attack Prediction using Several Machine Learning Techniques
Wang et al. Identification of phishing websites through hyperlink analysis and rule extraction
Abdolrazzagh-Nezhad et al. Phishing Detection Techniques: A review
Khan et al. An Enhanced Anti-Phishing Technique for Social Media Users: A Multilayer Q-Learning Approach.
Sharma et al. Improving the classification of phishing websites using a hybrid algorithm
Chauhan et al. Hybrid Sampling Technique for Imbalanced Android Malware Family Classification
Mahmoud et al. A machine learning model for malware detection using recursive feature elimination (RFE) for feature selection and ensemble technique
Ponni et al. Randomized active learning to identify phishing URL