Enhancing Email Security with AI: A Review of Machine Learning, Deep Learning and Fuzzy Logic Approaches

Email is the most common method of communication and work of confirmation during personal and business correspondence, but its increased use has made it vulnerable to cybersecurity threats such as phishing and Advanced Persistent Threats (APTs). Spammer mails not only compromise the machine security but as such, decrease the level of output in any workplace. Spam detection is therefore a very important part of cybersecurity as cybercriminals take advantage of the email vulnerabilities they create and attack everyone from individuals to enterprises. The static and rule-based filters that conventional spam filters function about is not much effective to combat the new strategies of spamming. The inability to accommodate new patterns yields bad accuracy, high false positive rates and false negatives. The development of advanced AI techniques and their applications to spam filter have introduced new opportunities to overcome the limitations of existing approaches by using various machine learning, deep learning and fuzzy logic methods that enhance the spam filter flexibility and accuracy. This study examines various types of spam filtering methods including Fuzzy Logic Systems, Support Vector Machines (SVM), Long Short-Term Memory (LSTM), and Bidirectional Encoder Representations from Transformers (BERT). Detection accuracy and level of adaptability are used to assess these models. Results from this study show that deep learning models perform better than fuzzy logic-based techniques, even if SVM and Random Forest, the traditional machine learning methods, seems to perform between 95% and 99%, however DNN methods such as LSTM and BERT provide superior performance, above 98% classification accuracy. These results illustrate that there is an acceptable performance gap between traditional machine learning algorithms and new advanced deep learning architectures for spam filtering problems, in turn shows that an intelligent ability and adaptive spam filtering should be the proposed solutions.