Smishing is a type of cyberattack that includes delivering a fake messages to normal users in order to get their personal information. Cybersecurity experts are now concerned about this sort of assault because, both the individuals and companies are loosing their money by this attack. This article presents a machine learning base comparison approach using different text analysis features (i.e., Discourse, Linguistic, Psycholinguistic, Persuasion Principle and Statistics based features). Here, different Machine Learning classifiers (i.e., Logistic Regression, Naive Bayes, K-Nearest Neighbors, Random Forest, Support Vector Machine and XGBoost) have been used for smishing detection. The evaluation was performed on a prepared dataset. The dataset includes both smishing and normal messages. According to the comparative experimental results from the implemented classification algorithms, Random Forest classifier gives the best performance with the 99% accuracy.

Security on sensitive data of the patients is essential in e-medical system where, sensors and the servers use the insecure channels like ZigBee and Internet to exchange their information. An adversary may hamper the communications by mounting various attacks as well as he/she may try to get the sensitive data. Therefore, security system is needed so that it can protect the security attacks. This paper provides a new security protocol, referred as SecHealth when the healthcare sensors transmit their data to a local server known as fog server. In this case, after verifying each other (i.e., sensor and fog server), then only the sensors are able to transmit their data to the local fog server. However, security analysis of the proposed protocol states that it can overcome all the possible known attacks.

Abstract At the present time, application of online communication systems are rapidly increasing and most of the clients depend on a set of servers to fulfill their daily needs. In order to access these servers, a client (user) needs to register to each server with different login credentials. To circumvent this situation, the concept of multi‐server authentication has been adopted, where a user can access all the servers using a single login credential. In this paper, a two‐factor multi‐server authentication protocol, which is proposed by Leu and Hsieh, is analyzed and observed that the forgery attack and the off‐line password‐guessing attack can be made on it. Further, the off‐line password‐guessing attack and other security threats are found in similar kind of multi‐server authentication protocol, which is designed by Li et al. This paper mainly focuses on enhancing the securities of the previously mentioned protocols and thus proposed a new protocol. We have employed formal and informal security analysis to analyze the proposed protocol. The performance of our protocol is also compared with the related protocols. It can also be noted that the designed protocol accomplishes mutual authentication, session key verification, and identity and password change phases. Copyright © 2016 John Wiley & Sons, Ltd.

Abstract Client‐server‐based communications provide a facility by which users can get several services from home via the Internet. As the Internet is an insecure channel, it is needed to protect information of communicators. An authentication scheme can fulfill the aforementioned requirements. Recently, Huang et al. presented an elliptic curve cryptosystem‐based password authentication scheme. This work has demonstrated that the scheme of Huang et al. has security weakness against the forgery attack. In addition, this paper also presented that the scheme of Huang et al. has some design drawbacks. Therefore, this paper has focused on excluding the security vulnerabilities of the scheme of Huang et al. by proposing an elliptic curve cryptosystem‐based password authentication scheme using smart card. The security of our scheme is based on the hardness assumption of the one‐way hash functions and elliptic curve discrete logarithm problem. Furthermore, we have demonstrated that our scheme is secured against known attacks. The performance of our scheme is also nearly equal when compared to related competing schemes. Copyright © 2016 John Wiley & Sons, Ltd.