A Review on Image Spam Detection Techniques using Some Machine Learning Algorithms
Keywords:
Image Spam, Detection Techniques, Machine Learning, Algorithms, ReviewAbstract
The most convenient and time efficient method of online communication is through email despite the emergence of alternative forms of online communication which include social networking, sending and receiving. The increase in online transactions via email has led to a significant increase in the global number of email spam which has relatively become a critical problem in the area of computing. There have been numerous techniques of machine learning for identifying unsolicited email spam. Despite the significant improvements made in the number of existing literatures reviewed, there exist no classification technique that has achieve 100% accuracy, each algorithm employs a limited number of features. As a result, determining the most appropriate technique is a critical task because their effectiveness needs to be weighed relative to their drawbacks. To improve on the existing spam detection techniques, we develop a multi-modal architecture capable of detecting image spam, train the model and then, provide an experimental result which indicates that the resultant model performs efficiently.