Detecting Phishing SMS Based on Multiple Correlation Algorithms
- PDF / 907,553 Bytes
- 9 Pages / 595.276 x 790.866 pts Page_size
- 3 Downloads / 242 Views
ORIGINAL RESEARCH
Detecting Phishing SMS Based on Multiple Correlation Algorithms Gunikhan Sonowal1 Received: 20 May 2020 / Accepted: 16 October 2020 © Springer Nature Singapore Pte Ltd 2020
Abstract The SMS phishing is another method where the phisher operates the SMS as a medium to communicate with the victims and this method is identified as smishing (SMS + phishing). Researchers promoted several anti-phishing methods where the correlation algorithm is applied to explore the relevancy of the features since there are numerous features in the features corpus. The correlation algorithm assesses the rank of the features that is the highest rank leads to the more relevant to the appropriate assignment. Therefore, this paper analyses four rank correlation algorithms particularly Pearson rank correlation, Spearman’s rank correlation, Kendall rank correlation, and Point biserial rank correlation with a machine-learning algorithm to determine the best features set for detecting Smishing messages. The result of the investigation reveals that the AdaBoost classifier offered better accuracy. Further analysis shows that the classifier with the ranking algorithm that is Kendall rank correlation appeared superior accuracy than the other correlation algorithms. The inferred of this experiment confirms that the ranking algorithm was able to reduce the dimension of features with 61.53% and presented an accuracy of 98.40%. Keywords Phishing · Smishing · Correlation Algorithm · Machine Learning Algorithm
Introduction Phishing is an entirely crucial attack these days where attackers snitch the credentials from the users using social engineering with technologies [44, 46]. Social engineering is the practice of influence and persuasion to deceive victims for acquiring information or performing some operation [16, 38]. The United Nations reports 350% rise in phishing websites during the COVID-19 pandemic [48]. Currently, phishing is expanding rapidly and according to the report concerning the Anti-Phishing Working Group(APWG) [4], the number of unique phishing websites detected in JanuaryJune 2020 is shown in Fig. 1. Nowadays, attackers employ numerous communication mediums to communicate with the victims such as email, text message( SMS), telephone, and others [5]. However, SMS is one of the feasible mechanisms to effectively communicate with others through mobile phones without the internet. It is generally accepted that every person possesses
* Gunikhan Sonowal [email protected] 1
Department of Computer Science, Pondicherry University, Pondicherry, India
mobile phones and the number of mobile phone users was estimated at 5.15 billion in 2020 [14]. According to the CallHub, the response rate of 98% SMS messages is 45% in comparison to the email is 28-33% which indicates that the email is 6% lower response rate than SMS [7, 10]. Attackers exploit this service and sending the phishing SMS to the users which are similar to the legitimate SMS to steal the credentials [23, 37, 52]. According to [33], smishing is a vari
Data Loading...
