Ann Nosseir

Question-based authentication using context data

In everyday life there are low risk situations where resources normally need to be protected and thus access to them controlled, but at the same time the implications of occasional unauthorized access are not severe. In these situations using an authentication technique that is expensive or requires significant effort from the user may not be justified. In this paper, we introduce a question-based authentication scheme appropriate for low risk situations. The scheme utilizes the context data already collected within a smart environment to generate the questions. Despite, the limited capabilities of the smart environment used in this experiment our preliminary study shows that using simple questions based on workplace events it is possible to discriminate between genuine users and impostors.

E-Learning and motivation effects on Egyptian higher education

The information technology educational programs at most universities in Egypt face many obstacles that can be overcome using technology enhanced learning. An open source Moodle eLearning platform has been implemented at many universities in Egypt, as an aid to deliver e-content and to provide the institution with various possibilities for implementing asynchronous e-learning web-based modules. This paper shows that the use of interactive features of e-learning increases the motivation of the undergraduate students for the learning process.

Question-based group authentication

There are various situations where a distinction needs to be made between group members and outsiders. For example, to protect students in chat groups from unpleasant incidents caused by intruders; or to provide access to common domains such as computer labs. In some of these situations the implications of unauthorized access are negligible. Thus, using an expensive authentication technique, in terms of equipment and maintenance, or requiring significant effort from the user, is wasteful and unjustified. Passwords are the cheapest access control mechanism but have memorability issues. As a result, various alternatives have been proposed. These solutions are often either insecure or expensive in terms of data collection and maintenance. In this paper we present a solution that is less costly since it is built on the data produced by user-system interactions. The mechanism relies on a dynamic (and unpredictable) shared secret. We report on our investigation into differentiating between group members and outsiders by means of their group characteristics. We also present an original analytical framework to facilitate the automatic generation of questions from group characteristics. Finally, we introduce a prototype of the mechanism.

Automatic Identification and Classifications for Fruits Using k-NN

Most fruit recognition techniques combine different analysis method like color-based, shaped-based, size-based and texture-based. This work classifies the fruits features based on the color RBG values and texture values of the first statistical order and second statistical of the Gray Level Co-occurrence Matrix (GLCM). It applies different classifies Fine K-NN, Medium K-NN, Coarse K-NN, Cosine K-NN, Cubic K-NN, Weighted K-NN. The accuracy of each classifier is 96.3%, 93.8%, 25%, 83.8%, 90%, and 95% respectively. The system is evaluated with 46 images by amateur photographers of seasonal fruits at the time namely, strawberry, apply and banana. 100% of these pictures were recognised correctly.

Extraction of Egyptian License Plate Numbers and Characters Using SURF and Cross Correlation

In Egypt, Traffic police or traffic officers usually write down the car license numbers and characters to enforce traffic rules. This is subject to errors of writing or reading the numbers and characters. The proposed work can utilise the advantage of widely spread of mobile phones. Officers can take pictures of car plate licenses and the system converts the pictures of car plate numbers and characters into digital numbers and letters. Arabic characters are challenging because some are very similar to each others unlike the English characters.. For example, feh (ف) and Qaaf (ق), noon (ن) and ba (ب) difference is minor. The challenge of this work is to extract the Arabic characters and numbers with high accuracy from pictures of new and old car plate design and pictures by regular people. The algorithm has five steps image acquisition, pre-processing, segmentation, feature extraction, and character recognition. To improve the performance time, in the pre-processing step, the developed system tests the cropped area, converts the picture into gray scale, reverses color, and converts it into binary image. Then, it uses morphological operations which is dilation. To improve the accuracy, in the feature extraction step it uses SURF (Speeded Up Robust Features) and cross correlation algorithms in the character recognition. The system is tested with 21 plate pictures and the accuracy is 95% and only one plate picture was missed.

Automatic Extraction of Arabic Number from Egyptian ID Cards

ID check is a vital process to verify people identify and to allow entry to different places like universities, check points or a banks. This process is usually done by just looking into the ID or writing it down. To improve the check process and make it quick and easy, our work develops a novel system that extracts the Arabic numbers from the ID picture. The proposed algorithm uses morphological operations more specifically dilation to maximally eliminate non Region Of Interest (ROI) and enhance the (ROI). Moreover, algorithm applies (Speeded Up Robust Features) SUFE algorithm to extract feature points of each image and the correlation based template matching technique to recognise characters. The approach has been evaluated with 17 ID cards pictures taken by amateur people with their mobile and other pictures from the internet. The images were too bright, dark, or from an angle. The algorithm is tested with these pictures and all ID numbers where identified correctly

Using handheld mobile system for teaching illiterates

Handheld device systems had been used as a tool for teaching special needs people because of the graphics and simplicity of the usage. Can a handheld device system, such as cellular phone, be used for teaching illiterates people? This paper explores and exploits the possibility of the development of a mobile system to help the illiterate people in Egypt.

Towards Authentication via Selected Extraction from Electronic Personal Histories

Authentication via selected extraction from electronic personal histories is a novel question-based authentication technique. This paper first presents a study using academic personal web site data that investigated the effect of using image-based authentication questions. By assessing the impact on both genuine users and attackers the study concluded that from an authentication point of view (a) an image-based representation of questions is beneficial; (b) a small increase in the number of distracters/options in closed questions is positive; and (c) the ability of attackers, close to genuine users, to answer correctly with high confidence, genuine users’ questions is limited. Second, the paper presents the development of a web-based prototype for automated generation of image-based authentication questions. The prototype makes clear that although possible to largely automate the generation of authentication questions, this requires significant engineering effort and further research. These results are encouraging for the feasibility of the technique.