Secure and Privacy Enhanced Gait Authentication on Smart Phone

Smart environments established by the development of mobile technology have brought vast benefits to human being. However, authentication mechanisms on portable smart devices, particularly conventional biometric based approaches, still remain security and privacy concerns. These traditional systems are mostly based on pattern recognition and machine learning algorithms, wherein original biometric templates or extracted features are stored under unconcealed form for performing matching with a new biometric sample in the authentication phase. In this paper, we propose a novel gait based authentication using biometric cryptosystem to enhance the system security and user privacy on the smart phone. Extracted gait features are merely used to biometrically encrypt a cryptographic key which is acted as the authentication factor. Gait signals are acquired by using an inertial sensor named accelerometer in the mobile device and error correcting codes are adopted to deal with the natural variation of gait measurements. We evaluate our proposed system on a dataset consisting of gait samples of 34 volunteers. We achieved the lowest false acceptance rate (FAR) and false rejection rate (FRR) of 3.92% and 11.76%, respectively, in terms of key length of 50 bits

A Survey on Password Guessing

Text password has served as the most popular method for user authentication so far, and is not likely to be totally replaced in foreseeable future. Password authentication offers several desirable properties (e.g., low-cost, highly available, easy-to-implement, reusable). However, it suffers from a critical security issue mainly caused by the inability to memorize complicated strings of humans. Users tend to choose easy-to-remember passwords which are not uniformly distributed in the key space. Thus, user-selected passwords are susceptible to guessing attacks. In order to encourage and support users to use strong passwords, it is necessary to simulate automated password guessing methods to determine the passwords' strength and identify weak passwords. A large number of password guessing models have been proposed in the literature. However, little attention was paid to the task of providing a systematic survey which is necessary to review the state-of-the-art approaches, identify gaps, and avoid duplicate studies. Motivated by that, we conduct a comprehensive survey on all password guessing studies presented in the literature from 1979 to 2022. We propose a generic methodology map to present an overview of existing methods. Then, we explain each representative approach in detail. The experimental procedures and available datasets used to evaluate password guessing models are summarized, and the reported performances of representative studies are compared. Finally, the current limitations and the open problems as future research directions are discussed. We believe that this survey is helpful to both experts and newcomers who are interested in password securityComment: 35 pages, 5 figures, 5 table

Implementation and Performance Analysis of Mobile Handoff Process on OpenFlow-based Wi-Fi Network

Research in communication network has the limit due to its problem of the supply frequency and equipment. To overcome this problem, open source can be the solution to build a helpful test bed for the research or academic purpose. Open source network can be developed using Software Defined Network (SDN) which has been continuosly developed due enormous number of installed base equipment and protocols that are inflexible, predefined, and fixed since SDN offers a flexible, dynamic, and programmable functionality of network systems. By using OpenFlow as its protocol, we can program the network flow in a flow table on different switches and routers. This research approches an OpenFlow-based Wi-Fi environment using OpenFlow-based Access Point (OFAP) and OpenFlow controller. Each OFAP is deployed at two different rooms and performed several experiments to evaluate handoff delay. The result of this experiment show that OpenFlow-based network show more stable process than traditional network because of installed flows given to each packets however the discovered value needs to be examined further due to better mechanism towards installed flows. The handoff delay between OFAPs is 24% faster than handoff delay between traditional AP with average of 79.9 miliseconds. By use of this system, we believe it could deliver high performance network and increase reliability for the real-time traffic over WLAN, by reducing handoff delay compared to classical Wi-Fi environment

Exploring Significant Motion Sensor for Energy-efficient Continuous Motion and Location Sampling in Mobile Sensing Application

The significant motion sensor is a new sensor that promises motion detection at low power consumption. Despite that promise, no known research has explored the usage of this sensor, especially in mobile sensing research. In this study, we explore the utilization of this significant motion sensor for continuous motion and location sampling in a mobile sensing application. A location sensor is known for its expensive power consumption in retrieving the location data, and continuously sampling from it will quickly deplete a smartphone battery. We experiment with two sampling strategies that utilize this significant motion sensor to achieve low power consumption during continuous sampling. One strategy involves utilizing the sensor naively, while the other involves combining with the duty cycle. Both strategies achieve low energy consumption, but the one that combines with the duty cycle achieves lower energy consumption. By utilizing this sensor, mobile sensing research especially that samples data from location or motion sensors, will be able to achieve lower energy consumption

Why smartphone users accessing facebook through facebook mobile website?: Battery and privacy awareness

Facebook has grown tremendously and becomes one of the most popular social networks in the world. Along development of smartphone, Facebook also provides Facebook application in order that smartphone users can easily to access Facebook using their smartphone. However, some of smartphone users prefer to access Facebook through Facebook mobile website rather than Facebook application. In this research, we want to investigate "Why smartphone users accessing Facebook through Facebook mobile website?". In this study, we collected smartphone data of 46 participants and analyzed factors affecting smartphone users prefer to access Facebook through Facebook mobile website rather than Facebook application. The results showed that battery and privacy awareness significantly affected the decision of smartphone users to access Facebook whether through Facebook mobile website or Facebook application