Biblio

The volume of SMS messages sent on a daily basis globally has continued to grow significantly over the past years. Hence, mobile phones are becoming increasingly vulnerable to SMS spam messages, thereby exposing users to the risk of fraud and theft of personal data. Filtering of messages to detect and eliminate SMS spam is now a critical functionality for which different types of machine learning approaches are still being explored. In this paper, we propose a system for detecting SMS spam using a semi-supervised novelty detection approach based on one class SVM classifier. The system is built as an anomaly detector that learns only from normal SMS messages thus enabling detection models to be implemented in the absence of labelled SMS spam training examples. We evaluated our proposed system using a benchmark dataset consisting of 747 SMS spam and 4827 non-spam messages. The results show that our proposed method out-performed the traditional supervised machine learning approaches based on binary, frequency or TF-IDF bag-of-words. The overall accuracy was 98% with 100% SMS spam detection rate and only around 3% false positive rate.

Security is a requirement in society, yet its wide implementation is held back because of high expenses, and barriers to the use of technology. Experimental implementation of security at low cost will only help in promoting the technology at more affordable prices. This paper describes the design of a security system of surveillance using Raspberry Pi and Arduino UNO. The design senses the presence of \$a\$ human in a surveillance area and immediately sets off the buzzer and simultaneously starts capturing video of the motion it had detected and stores it in a folder. When the design senses a motion, it immediately sends an SMS to the user. The user of this design can see the live video of the motion it detects using the internet connection from a remote area. Our objective of making a low-cost surveillance area security system has been mostly fulfilled. Although this is a low-cost project, features can be compared with existing commercially available systems.

SMS (Short Message Service)-based authentication is widely used as a simple and secure multi-factor authentication, where OTP (One Time Password) is sent to user’s mobile phone via SMS. However, SMS authentication is vulnerable to Password Reset Man in the Middle Attack (PRMitM). In this attack, the attacker makes a victim perform password reset OTP for sign-up verification OTP. If the victim enters OTP to a malicious man-in-the-middle site, the attacker can overtake the victim’s account.We find new smartphone useful functions may increase PR-MitM attack risks. SMS push notification informs us an arrival of message by showing only beginning of the message. Hence, those who received SMS OTP do not notice the cautionary notes and the name of the sender that are supposed to show below the code, which may lead to be compromised. Auto-fill function, which allow us to input authentication code with one touch, is also vulnerable for the same reason.In this study, we conduct a user study to investigate the effect of new smartphone functions incurring PRMitM attack.

Mobile Device Security is an important factor as all the user's sensitive information is stored on the mobile device. The problem of mobile devices getting lost or stolen has only been increasing. There are various systems which provide Online Mobile Device Security which require internet to perform their required functions. Our proposed system SMS Based Offline Mobile Device Security System provides mobile device users with a wide range of security features that help protect the mobile device from theft and also acts as an assistant that helps the users in any problems they may face in their day-to-day lives. The project aims to develop a mobile security system that will allow the user to manipulate his mobile device from any other device through SMS which can be used to get contact information from the user's mobile device remotely, help find the phone by maximizing the volume and playing a tone, trace the current location of the mobile device, get the IMEI No of the device, lock the device, send a message that will be converted to speech and played on the user's mobile device, call forwarding, message forwarding and various other features. It also has an additional security feature that will detect a sim card change and send the new SIM card mobile no to the recovery mobile numbers specified during initial setup automatically. Hence, the user will be able to manipulate his phone even after the SIM card has been changed. Therefore, the SMS-Based Offline Mobile Device Security System provides much more security for the mobile device than the existing online device security methods.

Attacks targeting several millions of non-internet based application users are on the rise. These applications such as SMS and USSD typically do not benefit from existing multi-factor authentication methods due to the nature of their interaction interfaces and mode of operations. To address this problem, we propose an approach that augments blockchain with multi-factor authentication based on evidence from blockchain transactions combined with risk analysis. A profile of how a user performs transactions is built overtime and is used to analyse the risk level of each new transaction. If a transaction is flagged as high risk, we generate n-factor layers of authentication using past endorsed blockchain transactions. A demonstration of how we used the proposed approach to authenticate critical financial transactions in a blockchain-based asset financing platform is also discussed.

This paper describes a system that comprises of control, safety and security subsystem for industries and homes. The entire system is based on the Bolt IoT platform. Using this system, the user can control the devices such as LEDs, speed of the fan or DC motor, monitor the temperature of the premises with an alert sub-system for critical temperatures through SMS and call, monitor the presence of anyone inside the premises with an alert sub-system about any intrusion through SMS and call. If the system is used specifically in any industry then instead of monitoring the temperature any other physical quantity, which is critical for that industry, can be monitored using suitable sensors. In addition, the cloud connectivity is provided to the system using the Bolt IoT module and temperature data is sent to the cloud where using machine-learning algorithm the future temperature is predicted to avoid any accidents in the future.

Software security is an important aspect that needs to be considered during the entire software development life cycle (SDLC). Integrating software security at each phase of SDLC has become an urgent need. To address software security, various approaches, techniques, methods, practices, and models have been proposed and developed. However, recent research shows that many software development methodologies do not explicitly include methods for incorporating software security during the development of software as it evolves from requirements engineering to its final disposal. The primary objective of this research is to study the state-of-the-art of security in the context of SDLC by following systematic mapping study (SMS). In the second phase, we will identify, through systematic literature review (SLR) and empirical study in the industry, the software security contributions, security challenges and their practices for global software development (GSD) vendors. The ultimate aim is to develop a Software Security Assurance Model (SSAM) to assist GSD vendor organisations in measuring their readiness towards the development of secure software.

Short Message Service is now-days the most used way of communication in the electronic world. While many researches exist on the email spam detection, we haven't had the insight knowledge about the spam done within the SMS's. This might be because the frequency of spam in these short messages is quite low than the emails. This paper presents different ways of analyzing spam for SMS and a new pre-processing way to get the actual dataset of spam messages. This dataset was then used on different algorithm techniques to find the best working algorithm in terms of both accuracy and recall. Random Forest algorithm was then implemented in a real world application library written in C\# for cross platform .Net development. This library is capable of using a prebuild model for classifying a new dataset for spam and ham.

For mobile phone users, short message service (SMS) is the most commonly used text-based communication type on mobile devices. Users can interact with other users and services via SMS. For example, users can send private messages, use information services, apply for a job advertisement, conduct bank transactions, and so on. Users should be very careful when using SMS. During the sending of SMS, the message content should be aware that it can be captured and act accordingly. Based on these findings, the elderly, called as “Silent Generation” which represents 70 years or older adults, are text messaging much more than they did in the past. Therefore, they need solutions which are both simple and secure enough if there is a need to send sensitive information via SMS. In this study, we propose and develop an android application to secure text messages. The application has a simple and easy-to-use graphical user interface but provides significant security.

Text messaging is used by more people around the world than any other communications technology. As such, it presents a desirable medium for spammers. While this problem has been studied by many researchers over the years, the recent increase in legitimate bulk traffic (e.g., account verification, 2FA, etc.) has dramatically changed the mix of traffic seen in this space, reducing the effectiveness of previous spam classification efforts. This paper demonstrates the performance degradation of those detectors when used on a large-scale corpus of text messages containing both bulk and spam messages. Against our labeled dataset of text messages collected over 14 months, the precision and recall of past classifiers fall to 23.8% and 61.3% respectively. However, using our classification techniques and labeled clusters, precision and recall rise to 100% and 96.8%. We not only show that our collected dataset helps to correct many of the overtraining errors seen in previous studies, but also present insights into a number of current SMS spam campaigns.

SMS (Short Messaging Service) is a text messaging service for mobile users to exchange short text messages. It is also widely used to provide SMS-powered services (e.g., mobile banking). With the rapid deployment of all-IP 4G mobile networks, the underlying technology of SMS evolves from the legacy circuit-switched network to the IMS (IP Multimedia Subsystem) system over packet-switched network. In this work, we study the insecurity of the IMS-based SMS. We uncover its security vulnerabilities and exploit them to devise four SMS attacks: silent SMS abuse, SMS spoofing, SMS client DoS, and SMS spamming. We further discover that those SMS threats can propagate towards SMS-powered services, thereby leading to three malicious attacks: social network account hijacking, unauthorized donation, and unauthorized subscription. Our analysis reveals that the problems stem from the loose security regulations among mobile phones, carrier networks, and SMS-powered services. We finally propose remedies to the identified security issues.

Today in the world of globalization mobile communication is one of the fastest growing medium though which one sender can interact with other in short time. During the transmission of data from sender to receiver, size of data is important, since more data takes more time. But one of the limitations of sending data through mobile devices is limited use of bandwidth and number of packets transmitted. Also the security of these data is important. Hence various protocols are implemented which not only provides security to the data but also utilizes bandwidth. Here we proposed an efficient technique of sending SMS text using combination of compression and encryption. The data to be send is first encrypted using Elliptic curve Cryptographic technique, but encryption increases the size of the text data, hence compression is applied to this encrypted data so the data gets compressed and is send in short time. The Compression technique implemented here is an efficient one since it includes an algorithm which compresses the text by 99.9%, hence a great amount of bandwidth gets saved.The hybrid technique of Compression-Encryption of SMS text message is implemented for Android Operating Systems.