Research Article
Hybrid Rule-Based Solution for Phishing URL Detection Using Convolutional Neural Network
Table 3
Comparison of advantages and disadvantages of different phishing detection techniques.
| Methods | Advantages | Disadvantages |
| Blacklist | Does not require high resources to use it Fast Excellent when minimal FP (false positive) required | Not trusted Not always updated | Lexical and host | Provides a sort of lexical profile for such URL Can prevent and not only detect | Should always be updated Needs human intervention sometimes | Content | Trusted Detect hidden content like iframes | Cannot detect obfuscation Should be maintained | Identity | Offers an owner profile | Not trusted | Visual similarity | Effective Mitigate zero-hour attack | Higher FP rate High computational cost | Behavioral | Detects hidden anomalies Reveals novel abnormal behaviors | Very high computational cost Needs human intervention Should be maintained | Machine learning | Can prevent and not only detect Mitigate zero-day attack Construct its own models | Time-consuming Needs maintenance Works through several rules | Deep learning | Can prevent and not only detect Mitigate zero-day attack Constructs its own models Becomes more effective with data increase | Time-consuming Should be maintained A vast number of rules Massive number of parameters to handle |
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