Avoiding the Phishing Bait: The Need for Conventional Countermeasures for Mobile Users

According to the international Anti-Phishing Work Group (APWG), phishing activities have significantly risen over the last few years, and users are becoming more susceptible to online and mobile fraud. Machine Learning (ML) techniques have the potential for building technical anti-phishing models, a majority of them have yet to be applied in a real-time environment. ML models also require domain experts to interpret the results. This gives conventional techniques a vital role as supportive tools for a wider audience, especially novice users, in order to reduce the rate of phishing attacks. Our paper aims at raising awareness and educating users on phishing in general and mobile phishing in particular from a conventional perspective, unlike existing reviews that are based on data mining and machine learning. This will equip individuals with knowledge and skills that may prevent phishing on a wider context within the mobile users' community.