IEEE 2017-2018 Project Titles on Authentication & Security

Abstract:

Advancement in payment technologies has an important impact on one's quality of life. Emerging payment technologies create both opportunities and challenges for the future. Being a quick and convenient process, contactless payment gained momentum, especially with merchants, with throughput being the main parameter. However, it poses risks to issuers, as no robust customer verification method is available. Thus, efforts have been underway to evolve and sustain a well-organized, efficient, reliable, and secure unified payment system, which may contribute to the smooth functioning of the market by eliminating obstacles in business.

Abstract:

Recently vehicle tracking system is getting vast popularity because of the rising number of the stolen vehicles. Vehicle theft is happening on parking and sometimes driving in unsecured places. This research work explores how to avoid this kind of stealing and provides more security to the vehicles. The implemented system contains single-board embedded system which is equipped with global system for mobile (GSM) and global positioning system (GPS) along with a microcontroller installed in the vehicle. The use of GSM and GPS technologies allows the system to track the object and provides the most up-to-date information about on-going trips. Moreover, fingerprint verification is done in the implemented system to ensure the driving of correct person. The implemented system is very simple with greater security for vehicle anti-theft protection and low cost technique compared to others.

Abstract:

In the developing countries many crimes are happening at the highways and bridges. In this paper we have introduced a security feature which can resist the occurrence of those crimes. However, this system is based on RFID (Radio Frequency Identification) technology which replaces the traditional manual tolling system. In the existing automated tolling system RFID reader only detects the RFID card to deduct the toll amount according to the vehicle types. In our integrated system if the authority wants to block a certain type of vehicle or a specific vehicle, it can be done at the toll booth area. For this, a simple code text is sent to the system using GSM module and then the vehicle is blocked by not lifting the barrier even after deduction of the toll amount from the vehicle owner's prepaid based account. In addition, this can also be done to block all the vehicles at the toll booth area in the bridges in case of emergency.

Abstract:

This paper explains various security issues in the existing home automation systems and proposes the use of logic-based security algorithms to improve home security. This paper classifies natural access points to a home as primary and secondary access points depending on their use. Logic-based sensing is implemented by identifying normal user behavior at these access points and requesting user verification when necessary. User position is also considered when various access points changed states. Moreover, the algorithm also verifies the legitimacy of a fire alarm by measuring the change in temperature, humidity, and carbon monoxide levels, thus defending against manipulative attackers. The experiment conducted in this paper used a combination of sensors, microcontrollers, Raspberry Pi and ZigBee communication to identify user behavior at various access points and implement the logical sensing algorithm. In the experiment, the proposed logical sensing algorithm was successfully implemented for a month in a studio apartment. During the course of the experiment, the algorithm was able to detect all the state changes of the primary and secondary access points and also successfully verified user identity 55 times generating 14 warnings and 5 alarms.

Abstract:

Indoor navigation in physical retail type spaces aids the navigation of users to find physical items at known destinations. WiFi Fingerprinting using a mobile phone is perhaps the most widely used method. However, this is power-hungry, and its typical positioning accuracy (2.0 to 3.0 meters) is not enough to differentiate between adjacent narrow aisles to locate items. In this paper, we present a novel (Bluetooth Low Energy) BLE Received Signal Strength Indication (RSSI) ranking based fingerprinting method that uses Kendall Tau Correlation Coefficient (KTCC) to correlate a new signal position with the signal strength ranking of multiple low-power iBeacon devices situated in a retail space. This offers a higher positioning accuracy and is supported in recent smartphones. An important source of error is the RSSI, which varies depending on the model and orientation of the phone. We present a novel way to mitigate this. We validated our method in a retail-like indoor space of Queen Mary Library. We achieved an average positioning error of 0.87 meters which was sufficient to differentiate between physical space aisles.

Abstract:

Indoor positioning systems have become widely available due to the increased number of wireless technologies available today. A type of wireless device that has become very popular in the past years has been the Bluetooth Low Energy (BLE) beacon. This compact, battery-powered device can enable location-based and proximity services across in-door spaces. Several indoor positioning techniques have been explored to achieve indoor localization using these wireless devices. One of these techniques is the fingerprinting technique, which requires careful collection of training data at known locations. We developed an app to facilitate and expedite the process of collecting training data with iOS devices. The training data is collected by our app and saved in the cloud for future retrieval. We collected training data from different floor maps, performed initial analysis on this data, and tested a fingerprinting algorithm in order to provide indoor localization. We developed several tools to evaluate and visualize the training data and tested our indoor localization algorithm in a real-time scenario.