Evaluating Passwords User Behavior and the Psychology of Password Management
Walid Ali Sulaiman Ali Alothman
Regardless of how complex an association's security framework is, it stays helpless because of the human factor. Content based passwords are usually utilized for verification in figuring condition. Despite the fact that passwords are considered as the underlying line of assurance for users, they stay simple to compromise. To improve the security of frameworks, different password synthesis policies are embraced. These strategies guarantee that users are made to pick solid passwords that assistance anticipate online ruptures and information spills. Be that as it may, it likewise make passwords hard to retain and review, diminishing the general ease of use. In this examination we researched the ease of use of password strategies and users' view of password security. We additionally reviewed and examined the patterns practiced by users while producing passwords (Crantor, Hong and Reiter, 2016).
Users are not as mindful of security prerequisites and practices as they think. By far most of users' passwords are breakable within days or shorter. Strikingly, we found that the utilization of numbers and uppercase letters is common among clients. Numbers are generally utilized toward the end of the passwords and uppercase letters are for the most part utilized toward the start of passwords. The presence of such patterns makes it simpler for attackers to create progressively compelling dictionaries. In light of the examination in this investigation, we make suggestions to the IT office to improve the password policy (Shen, 2016).
Classification of printed and handwritten text using hybrid techniques for gurumukhi script
Manpreet Kaur, Balwinder Singh
Text classification is a crucial step for optical character recognition. The output of the scanner is non- editable. Though one cannot make any change in scanned text image, if required. Thus, this provides the feed for the theory of optical character recognition. Optical Character Recognition (OCR) is the process of converting scanned images of machine printed or handwritten text into a computer readable format. The process of OCR involves several steps including pre-processing after image acquisition, segmentation, feature extraction, and classification. The incorrect classification is like a garbage in and garbage out. Existing methods focuses only upon the classification of unmixed characters in Arab, English, Latin, Farsi, Bangla, and Devnagari script. The Hybrid Techniques is solving the mixed (Machine printed and handwritten) character classification problem. Classification is carried out on different kind of daily use forms like as self declaration forms, admission forms, verification forms, university forms, certificates, banking forms, dairy forms, Punjab govt forms etc. The proposed technique is capable to classify the handwritten and machine printed text written in Gurumukhi script in mixed text. The proposed technique has been tested on 150 different kinds of forms in Gurumukhi and Roman scripts. The proposed techniques achieve 93% accuracy on mixed character form and 96% accuracy achieves on unmixed character forms. The overall accuracy of the proposed technique is 94.5%.