[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Tang et al., 2019 - Google Patents

Dynamic API call sequence visualisation for malware classification

Tang et al., 2019

View PDF @Full View
Document ID
16389589424625771060
Author
Tang M
Qian Q
Publication year
Publication venue
IET Information Security

External Links

Snippet

Due to the development of automated malware generation and obfuscation, traditional malware detection methods based on signature matching have limited effectiveness. Thus, a novel approach using visualisation and deep learning technology can play an important role …
Continue reading at ietresearch.onlinelibrary.wiley.com (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • G06K9/4652—Extraction of features or characteristics of the image related to colour
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/40—Analysis of texture
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30587—Details of specialised database models
    • G06F17/30595—Relational databases
    • G06F17/30598—Clustering or classification
    • G06F17/30601—Clustering or classification including cluster or class visualization or browsing

Similar Documents

Publication Publication Date Title
Tang et al. Dynamic API call sequence visualisation for malware classification
Nguyen et al. A novel graph-based approach for IoT botnet detection
Venkatraman et al. A hybrid deep learning image-based analysis for effective malware detection
Ahmed et al. A system call refinement-based enhanced Minimum Redundancy Maximum Relevance method for ransomware early detection
Venkatraman et al. Use of data visualisation for zero‐day malware detection
Singh et al. Malware classification using image representation
Charmet et al. Explainable artificial intelligence for cybersecurity: a literature survey
Pektaş et al. Malware classification based on API calls and behaviour analysis
Chumachenko Machine learning methods for malware detection and classification
Haddadpajouh et al. A multikernel and metaheuristic feature selection approach for IoT malware threat hunting in the edge layer
Gao et al. Malware classification for the cloud via semi-supervised transfer learning
Firdaus et al. Root exploit detection and features optimization: mobile device and blockchain based medical data management
Zhao et al. A review of computer vision methods in network security
Yan et al. A survey of adversarial attack and defense methods for malware classification in cyber security
Gao et al. Android malware detection via graphlet sampling
Du et al. Digital Forensics as Advanced Ransomware Pre‐Attack Detection Algorithm for Endpoint Data Protection
Ali et al. Deep learning methods for malware and intrusion detection: A systematic literature review
Gulmez et al. XRan: Explainable deep learning-based ransomware detection using dynamic analysis
Ravi et al. Attention‐based convolutional neural network deep learning approach for robust malware classification
Alazab et al. Detecting malicious behaviour using supervised learning algorithms of the function calls
Xue et al. Homology analysis of malware based on ensemble learning and multifeatures
Wei et al. Toward identifying APT malware through API system calls
Hwang et al. Semi-supervised based unknown attack detection in EDR environment
Liu et al. FewM-HGCL: Few-shot malware variants detection via heterogeneous graph contrastive learning
Li et al. Deep learning algorithms for cyber security applications: A survey