Cluster-Based Antiphishing (CAP) Model for Smart Phones

Mohammad Faisal,Sa’Ed Abed,Shah Nazir

doi:10.1155/2021/9957323

Mohammad Faisal, Sa’Ed Abed + Show 1 more

Open Access

https://doi.org/10.1155/2021/9957323

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Abstract

Different types of connectivity are available on smartphones such as WiFi, infrared, Bluetooth, GPRS, GPS, and GSM. The ubiquitous computing features of smartphones make them a vital part of our lives. The boom in smartphone technology has unfortunately attracted hackers and crackers as well. Smartphones have become the ideal hub for malware, gray ware, and spyware writers to exploit smartphone vulnerabilities and insecure communication channels. For every security service introduced, there is simultaneously a counterattack to breach the security and vice versa. Until a new mechanism is discovered, the diverse classifications of technology mean that one security contrivance cannot be a remedy for phishing attacks in all circumstances. Therefore, a novel architecture for antiphishing is mandatory that can compensate web page protection and authentication from falsified web pages on smartphones. In this paper, we developed a cluster-based antiphishing (CAP) model, which is a lightweight scheme specifically for smartphones to save energy in portable devices. The model is significant in identifying, clustering, and preventing phishing attacks on smartphone platforms. Our CAP model detects and prevents illegal access to smartphones based on clustering data to legitimate/normal and illegitimate/abnormal. First, we evaluated our scheme with mathematical and algorithmic methods. Next, we conducted a real test bed to identify and counter phishing attacks on smartphones which provided 90% accuracy in the detection system as true positives and less than 9% of the results as true negative.

Highlights

A phishing attack is used to obstruct and limit legitimate user access to resources of service providers on global networks
87.24 85.15 86.94 86.57 83.88 87.03 86.33 85.26 86.41 86.44 87.31 e cluster-based antiphishing (CAP) model produces more than 90% accuracy in its detection system, which has been classified as true positive
Fake commercial advertisements can play the role of honey pots for phishing attacks, as they behave like original finance and business sector advertisements

Summary

Introduction

A phishing attack is used to obstruct and limit legitimate user access to resources of service providers on global networks. Phishing attack focuses on a single system by using different launching pads [1] It is not mandatory for both standalone and distributed phishing attacks to harm the data permanently and directly, it is certain that they deliberately compromise all the resource availability for cornerstone security services. Among these attacks, a phishing attack is the worst as its damages smartphones compared to other attacks such as ransomware, backdoors, Denial of Service (DOS)/(DDOS), bot activity, and worm propagation. A phishing attack damages all the data content of the smartphones, while in passive attack scenarios, a phishing attack uses the smartphone as a launching pad against other systems after compromising the system.

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