SMS Phishing and Mitigation Approaches

  title={SMS Phishing and Mitigation Approaches},
  author={Sandhya Mishra and Devpriya Soni},
  journal={2019 Twelfth International Conference on Contemporary Computing (IC3)},
  • Sandhya Mishra, Devpriya Soni
  • Published 1 August 2019
  • Computer Science
  • 2019 Twelfth International Conference on Contemporary Computing (IC3)
Smishing is an attack targeted to mobile devices in which the attacker sends text messages containing malicious links, phone numbers or E-Mail IDs to the victim and the attacker aims to steal sensitive user data like bank account details, passwords, user credentials, credit card details, etc through this message. Through this message, the attacker prompts the user to click on the link or contact the phone number or E-mail ID provided in the SMS. In this paper, we have discussed various mobile… 
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Mobile phishing attacks and defence mechanisms: State of art and open research challenges
A Content-Based Approach for Detecting Smishing in Mobile Environment
A novel method which will categorize the text message based on the SMS contents and URL behavior, using a machine learning algorithm to classify the message on basis of malicious keywords present in the message is proposed.
Mobile Phishing Attacks and Mitigation Techniques
This paper discusses various phishing attacks using mobile devices followed by some discussion on countermeasures to bring more awareness to emerging mobile device-based phishingattacks.
Feature Based Approach for Detection of Smishing Messages in the Mobile Environment
This article describes the proposed proposed Smishing Approaches approach as a "new feature-based approach" aimed at tackling the "smishing epidemic" in the mobile environment.
Smishing-Classifier: A Novel Framework for Detection of Smishing Attack in Mobile Environment
A novel framework for Smishing attack detection is proposed that uses Naive Bayesian classifier to filter text messages and analyses the content of the text message and extracts the words commonly used in Smishing messages.
A Practical Rule Based Technique by Splitting SMS Phishing from SMS Spam for Better Accuracy in Mobile Device
This study proposes a technique to split the class of SMS phishing from SMS spam and produce better accuracy using the Bayesian technique, and generated an improvement of SMS Phishing corpus which has been labelled in three different classes ie.
Security Considerations for Smart Phone Smishing Attacks
Recently, phishing, a new type of crime, has increased due to the expansion of the use of smart phones, and financial losses have been increasingly reported. As damage cases, which have become
S-Detector: an enhanced security model for detecting Smishing attack for mobile computing
An enhanced security model for detecting Smishing attack (the authors called “S-Detector”) is applied to a Naive Bayes classifier to improve the Smishingattack detection in smart devices and it is possible to analyze a text message and effectively detect SMS phishing.
Phishing detection taxonomy for mobile device
Phishing is one of the social engineering attacks and currently hit on mobile devices. Based on security report by Lookout [1], 30% of Lookout users clicking on an unsafe link per year by using