Authentication of Students and Students’ Work in E-Learning : Report for the Development Bid of Academic Year 2010/11

Global e-learning market is projected to reach $107.3 billion by 2015 according to a new report by The Global Industry Analyst (Analyst 2010). The popularity and growth of the online programmes within the School of Computer Science obviously is in line with this projection. However, also on the rise are students’ dishonesty and cheating in the open and virtual environment of e-learning courses (Shepherd 2008). Institutions offering e-learning programmes are facing the challenges of deterring and detecting these misbehaviours by introducing security mechanisms to the current e-learning platforms. In particular, authenticating that a registered student indeed takes an online assessment, e.g., an exam or a coursework, is essential for the institutions to give the credit to the correct candidate. Authenticating a student is to ensure that a student is indeed who he says he is. Authenticating a student’s work goes one step further to ensure that an authenticated student indeed does the submitted work himself. This report is to investigate and compare current possible techniques and solutions for authenticating distance learning student and/or their work remotely for the elearning programmes. The report also aims to recommend some solutions that fit with UH StudyNet platform.Submitted Versio

ONLINE MONITORING USING KISMET

Colleges and universities currently use online exams for student evaluation. Stu- dents can take assigned exams using their laptop computers and email their results to their instructor; this process makes testing more efficient and convenient for both students and faculty. However, taking exams while connected to the Internet opens many opportunities for plagiarism and cheating. In this project, we design, implement, and test a tool that instructors can use to monitor the online activity of students during an in-class online examination. This tool uses a wireless sniffer, Kismet, to capture and classify packets in real time. If a student attempts to access a site that is not allowed, the instructor is notified via an Android application or via Internet. Identifying a student who is cheating is challenging since many applications send packets without user intervention. We provide experimental results from realistic test environments to illustrate the success of our proposed approach

A Classification of Threats to Remote Online Examinations

This document is the Accepted Manuscript version of the following paper: Abrar Ullah, Hannah Xiao, and Trevor Barker, ‘A Classification of Threats to Remote Online Examinations’, in Proceedings of the 2016 IEEE 7th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), 13-15 October 2016, Vancouver, Canada. Published by IEEE, available online via http://ieeexplore.ieee.org/document/7746085/ Copyright © 2016, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Summative online examinations is a high stake process which faces many security threats. The lack of face-toface interaction, monitoring or invigilation motivates many threats, which includes intrusion by hackers and collusion by students. This paper is based on a survey of literature to present a threat classification using security abuse case scenarios. Collusion is one of the challenging threats, when a student invites a third party collaborator to impersonate or aid a student to take an online test. While mitigation of all types of threats is important, the risk of collusion is increasingly challenging because it is difficult to detect such attacks.Final Accepted Versio

Cybersecurity of Online Proctoring Systems

The online proctored examinations are adopted exceedingly in all forms of academic education and professional training. AI with Machine Learning technology take the leading role in supporting authentication, authorization, and operational control of proctored online examination. The paper discusses how administrative, physical, and technical controls can help mitigate related cybersecurity vulnerabilities of online proctoring systems (OPS). The paper considers two classes of OPS: fully automated AI-enabled systems and hybrid systems (automated AI-enabled with an expert live proctor in control). Based on the review of 20 online proctoring systems, the paper discusses methods and techniques of multi-factor authentication and authorizations, including the use of challenge-response, biometrics (face and voice recognition), and blockchain technology. The discussion of operational controls includes the use of lockdown browsers, webcam detection of behavioral signs of fraud, endpoint security, VPN and VM, screen-sharing and keyboard listening programs, technical controls to mitigate the absence of spatial (physical area) controls, compliance with regulations (GDPR), etc. Other topics discussed include confidentiality of the exam content, logging of control data, video and sound recording for auditing, limitations of endpoint-based security protection and detection techniques of behavior-based cheating and the effect of new intrusive technology on students’ privacy. In conclusion, the paper lists advanced features of online proctoring systems

EyeSpot: leveraging gaze to protect private text content on mobile devices from shoulder surfing

As mobile devices allow access to an increasing amount of private data, using them in public can potentially leak sensitive information through shoulder surfing. This includes personal private data (e.g., in chat conversations) and business-related content (e.g., in emails). Leaking the former might infringe on users’ privacy, while leaking the latter is considered a breach of the EU’s General Data Protection Regulation as of May 2018. This creates a need for systems that protect sensitive data in public. We introduce EyeSpot, a technique that displays content through a spot that follows the user’s gaze while hiding the rest of the screen from an observer’s view through overlaid masks. We explore different configurations for EyeSpot in a user study in terms of users’ reading speed, text comprehension, and perceived workload. While our system is a proof of concept, we identify crystallized masks as a promising design candidate for further evaluation with regard to the security of the system in a shoulder surfing scenario

The design and implementation of an in-application automated testing and evaluation system for computer literacy skills based on the European and international computer driving licence (ECDL/ICDL)

models which, in turn, contributed to the development of the corresponding assessment tools and systems. With the ECDL at the forefront of the international computer literacy skills market and with its important role in the specification of digital literacy agenda, it becomes vitally important to ensure that assessment systems leading to this qualification are of the highest technical and pedagogical quality. This paper presents the experiences gained from the design, testing and implementation of such an assessment system and its deployment in a big-bang approach on a national basis in Cyprus. It explains the system’s technical architecture and components, its functionalities and services and discusses the pedagogical and educational aspects embedded in the design and highlights the pitfalls and lessons learned in the areas of team building and project

Fostering Innovation and Methodology through Experiential Learning for Data Structures

For real-life work environment, developing employability skills by the students’ community is indispensable and need of the hour. Laboratories associated with courses cultivate the ability of students to think independently and promote employability skills through experiential learning. Data structures are one such predominant course in IT/CSE domain to enhance the skill set of students for Placements/Higher studies. It provides opportunity for students to devise algorithms efficiently in an optimal manner by solving challenging problems easily thereby gaining confidence for attending placements. The purpose of this paper is to foster innovation by exploration in data structures course through experiential learning by providing coding based challenging questions as tutorials, assignment presentations and as activities during laboratory sessions and online classes are to be conducted as an essential one in the future learning perspective. Findings conclude that the experiential learning foster student’s abilities in solving the problem and thereby gaining confidence during e-learning and placement activities and the grading process are to be updated through centralized servers to the maximum extend and accuracy are to be maintained

Wireless Security

This Grants Collection for Wireless Security was created under a Round Eight ALG Textbook Transformation Grant. Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process. Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials: Linked Syllabus Initial Proposal Final Reporthttps://oer.galileo.usg.edu/compsci-collections/1010/thumbnail.jp

Towards sustainable e-learning platforms in the context of cybersecurity: A TAM-driven approach

The rapid growth of electronic learning (e-learning) platforms has raised concerns about cybersecurity risks. The vulnerability of university students to cyberattacks and privacy concerns within e-learning platforms presents a pressing issue. Students’ frequent and intense internet presence, coupled with their extensive computer usage, puts them at higher risk of being a potential victim of cyberattacks. This problem necessitates a deeper understanding in order to enhance cybersecurity measures and safeguard students’ privacy and intellectual property in educational environments. This dissertation work addresses the following research questions: (a) To what extent do cybersecurity perspectives affect student’s intention to use e-learning platforms? (b) To what extent do students’ privacy concerns affect their intention to use e-learning platforms? (c) To what extent does students’ cybersecurity awareness affect their intention to use e-learning platforms? (d) To what extent do academic integrity concerns affect their intention to use e-learning platforms? and (e) To what extent does students’ computer self-efficacy affect their intention to use e-learning platforms? This study was conducted using an enhanced version of the technology acceptance model (TAM3) to examine the factors influencing students’ intention to use e-learning platforms. The study involved undergraduate and graduate students at Eastern Michigan University, and data were collected through a web-based questionnaire. The questionnaire was developed using the Qualtrics tool and included validated measures and scales with close-ended questions. The collected data were analyzed using SPSS 28, and the significance level for hypothesis testing was set at 0.05. Out of 6,800 distributed surveys, 590 responses were received, and after data cleaning, 582 responses were included in the final sample. The findings revealed that cybersecurity perspectives, cybersecurity awareness, academic integrity concerns, and computer self-efficacy significantly influenced students’ intention to use e-learning platforms. The study has implications for practitioners, educators, and researchers involved in designing secure e-learning platforms, emphasizing the importance of cybersecurity and recommending effective cybersecurity training programs to enhance user engagement. Overall, the study highlights the role of cybersecurity in promoting the adoption and usage of e-learning platforms, providing valuable insights for developers and educators to create secure e-learning environments and benefiting stakeholders in the e-learning industry