[go: up one dir, main page]

Wanawe et al., 2014 - Google Patents

An efficient approach to detecting phishing a web using k-means and naïve-bayes algorithms

Wanawe et al., 2014

Document ID
10468305613874340095
Author
Wanawe K
Awasare S
Puri N
Publication year
Publication venue
International Journal of Research in Advent Technology

External Links

Continue reading at scholar.google.com (other versions)

Classifications

    • 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
    • H04L63/1441Countermeasures against malicious traffic
    • H04L63/1483Countermeasures against malicious traffic service impersonation, e.g. phishing, pharming or web spoofing
    • 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
    • H04L63/1441Countermeasures against malicious traffic
    • H04L63/1458Denial of Service
    • 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

Similar Documents

Publication Publication Date Title
Wang et al. Machine learning based cross-site scripting detection in online social network
Ranganayakulu et al. Detecting malicious urls in e-mail–an implementation
Sunil et al. A pagerank based detection technique for phishing web sites
Apte et al. Frauds in online social networks: A review
Barlow et al. A novel approach to detect phishing attacks using binary visualisation and machine learning
Madhubala et al. Survey on malicious URL detection techniques
Vanitha et al. Malicious-URL detection using logistic regression technique
Azeez et al. CyberProtector: identifying compromised URLs in electronic mails with Bayesian classification
Gu et al. An efficient approach to detecting phishing web
Aung et al. Url-based phishing detection using the entropy of non-alphanumeric characters
US20230164180A1 (en) Phishing detection methods and systems
P. Velayudhan et al. Compromised account detection in online social networks: A survey
Noh et al. Phishing website detection using random forest and support vector machine: A comparison
Wanawe et al. An efficient approach to detecting phishing a web using k-means and naïve-bayes algorithms
Jaiswal et al. Malicious address identifier (MAI): A browser extension to identify malicious URLs
Solanki et al. Website phishing detection using heuristic based approach
Khan et al. A dynamic method of detecting malicious scripts using classifiers
Bhavani et al. Detection of legitimate and phishing websites using machine learning
Dholakia et al. Review on phishing attack detection techniques
Jansi et al. An Effective Model of Terminating Phishing Websites and Detection Based On Logistic Regression
Khadir et al. Efforts and Methodologies used in Phishing Email Detection and Filtering: A Survey.
Radha Damodaram et al. Bacterial foraging optimization for fake website detection
Thirumaran et al. Phishing website detection using natural language processing and deep learning algorithm
Abdul Abiodun et al. Performance Assessment of some Phishing predictive models based on Minimal Feature corpus
Mishra et al. Prevention of phishing attack in internet-of-things based cyber-physical human system