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Security Risks and Protection in Online
Learning: A Survey
n OnlineCourses
Yong Chen and Wu He
Old Dominion University, USA
Abstract
This paper describes a survey of online learning which attempts to determine online
learning providers’ awareness of potential security risks and the protection measures
that will diminish them. The authors use a combination of two methods: blog mining
and a traditional literature search. The findings indicate that, while scholars have
identified diverse security risks and have proposed solutions to mitigate the security
threats in online learning, bloggers have not discussed security in online learning with
great frequency. The differences shown in the survey results generated by the two
different methods confirm that online learning providers and practitioners have not
considered security as a top priority. The paper also discusses the next generation of
an online learning system: a safer personal learning environment which requires a
one-stop solution for authentication, assures the security of online assessments, and
balances security and usability.
Keywords: Online learning; security; risk; threat; protection; e-learning
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Introduction
Due to the development of the Internet, more and more people are taking online
courses. According to a recent SLOAN-C annual report (2011), a survey conducted in
2011 among 4,523 degree-granting institutions of higher education in the United States
reveals that over 6.1 million students were taking at least one online course during the
fall 2010 term and 31% of current higher education students have taken at least one
course online. Furthermore, 65% of higher education institutions now say that online
learning is a critical part of their long-term strategy (SLOAN-C, 2011; Floyd, Schultz, &
Fulton, 2012). Meanwhile, in the business world, numerous online courses for job and
skill training are offered, to allow professionals to increase their competency and to
upgrade their skills (Oncu & Cakir, 2011).
Online learning is “a type of delivery method used in distance education that allows
synchronous and asynchronous exchanges of resource over a communication network”
(Khan, 1998). It uses content repositories to store content and uses Web-based
technologies to help learners interact with instructors and with other learners
(Sasikumar, 2013). For example, a number of Web 2.0 tools such as blogs, podcasting,
and wikis have been widely used in online learning to facilitate learning, collaboration,
and knowledge sharing (Zuev, 2012). Newer web-based technologies such as social
media have inspired educators to think differently about the ways in which learning
occurs (Neville & Heavin, 2013) because the social media allow learners to create their
own content freely and to form learning communities as the media support
collaboration among learners and teachers (Redecker, Ala-Mutka, & Punie, 2010).
More recently, massive open online courses (MOOCs) have received a lot of attention
among institutions of higher education across the world (Meyer & Zhu, 2013); they are
expected to change the learning landscape of higher education during the next decade.
As an Internet-based learning method, online learning depends on the Internet for its
execution (Alwi & Fan, 2010). However, there are any number of illegal activities and
security threats taking place on the Internet. Consequently, the e-learning environment
is inevitably exposed to constant security threats, risks, and attacks. Unfortunately,
many educational institutions are rushing into adopting online learning management
systems without careful planning and without a thorough understanding of the security
aspects of online learning (Alwi & Fan, 2010). A recent survey conducted by Campus
Computing (campuscomputing.net) and WCET (wcet.info) found that almost 88% of
the surveyed institutions have adopted a learning management system (LMS) as their
medium for offering online courses.
In online learning, security means that “learning resources are available and
unimpaired to all authorized users when they are needed” (Adams & Blandford, 2003).
Since online learning takes place via the Internet, every element in an online learning
system can be a potential target of hacking or attacks. This may lead to unauthorized
modification and/or destruction of educational assets (Zuev, 2012). Online learning
must consider the inherent security risks on the Internet, such as identity theft,
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impersonation, and inadequate authentication (Ayodele, Shoniregun, & Akmayeva,
2011). Online learning systems have attracted the attention of cybercriminals who thrive
on their ability to hack into such systems. The risk is great; as the functionalities and
features of online learning systems become more complex, online learning is
increasingly exposed to security threats (Alwi & Fan, 2010).
In response to increasing threats, researchers have developed a number of
countermeasures and solutions to improve security in online learning. The purpose of
this paper is to synthesize the related discussions in the literature, to provide an in-
depth review of the security aspects of online learning, and to identify the future trends
and challenges to security in online learning. Currently, the discussion of security risks
of online learning is disparate, fragmented, and distributed among different outlets such
as academic articles, white papers, educational reports, and news articles. This paper
hopes to coordinate this information and to aid administrators and providers of online
learning and online learning systems to understand the state of the art in this fast-
moving field. This paper will offer necessary insights and tips so that online learning
providers can become proactive and knowledgeable as they mitigate the security risks
found in online learning.
Background
Security in online learning refers to protection from malicious or accidental misuse of
resources in online learning (Adams & Blandford, 2003; Neumann, 1994). Previous
literature indicates that security has three basic requirements: confidentiality, integrity,
and availability (Adams & Blandford, 2003; Serb, Defta, Iacob, & Apetrei, 2013; Weippl
& Ebner, 2008). Confidentiality refers to the protecting of sensitive information from
being accessed by unauthorized persons (Serb, Defta, Iacob, & Apetrei, 2013; Adams &
Blandford, 2003) and the absence of unauthorized disclosure of information (Weippl &
Ebner, 2008). Since there are a large number of users in any online learning
environment (among them students, visitors, instructors, tutors, and administrators),
both a login system and a strong delimitation marking registered users and user groups
are needed to safeguard the access to the appropriate user (Serb, Defta, Iacob, &
Apetrei, 2013). In order to protect personal information, security safeguards such as
authentication and encryption are usually implemented. Integrity, a critical element of
security, refers to “the protection of data from intentional or accidental unauthorized
changes” (Serb, Defta, Iacob, & Apetrei, 2013) and “the absence of improper system
alterations” (Weippl & Ebner, 2008). It assures that “information and data have not
been accidentally or maliciously modified or destroyed, and are in accurate, correct, and
complete original form” (Raitman, Ngo, Augar, & Zhou, 2005). Access control is the key
to maintaining integrity in the online learning environment (Serb, Defta, Iacob, &
Apetrei, 2013). Availability means the readiness for correct service (Weippl & Ebner,
2008). It connotes that an online learning system can be accessed by authorized users
whenever needed (Serb, Defta, Iacob, & Apetrei, 2013). And it assures that “information
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and communication resources are readily accessible and reliable in a timely manner by
authorized persons” (Raitman, Ngo, Augar, & Zhou, 2005). Availability can mainly be
damaged by denial of service and/or loss of data processing capabilities (Serb, Defta,
Iacob, & Apetrei, 2013).
According to Graf (2002), applications of information communication technology in
online learning can cause many security risks, such as loss of confidentiality and
availability, the exposure of critical data, and vandalism of public information services.
Usually, online learning security issues have been attributed to users’ poor knowledge of
security measures, improper behaviors, and lack of education, because security
protection mechanisms have been adopted in online learning programs. For example, in
almost all institutions, the main online learning providers have installed firewalls and
anti-virus software to protect their learning resources (Weippl & Ebner, 2008).
Furthermore, they continue to enhance the content and technology in their online
learning systems to secure online learning (Alwi & Fan, 2010; Srivastava & Sinha, 2013).
But in recent years, even though users’ security knowledge and skills have grown,
security issues such as information manipulation by outsiders and insiders (by students
or insiders) and loss of confidentiality still happen from time to time (Dietinger, 2003).
Security is essential as a means to retain users’ trust in the online learning environment
because any risk can dramatically affect students’ perceptions of a system’s reliability
and trustworthiness (Adams & Blandford, 2003). As a result, it is crucial to identify the
underlying factors that can cause security issues in online learning and to identify the
limitations of the current security protection methods. Then, counter-measures can be
developed to mitigate the security risks inherent in online learning.
Method
This study adopts two approaches to carrying out the review of security risks and
protection in online learning.
First, an extensive literature search was conducted, via academic databases including
the Web of Knowledge, the ACM Digital Library, the AACE Digital Library, and a web
search engine (Google Scholar), using queries regarding security risks, threats, and
protection in online learning. Since security has been a hot topic in the domain of online
learning for some time, many articles were discovered. However, the discussions of
security in online learning are disparate and fragmented.
Second, blog mining, a novel research method, was employed in this study, in order to
further identify security risks and threats in online learning and to explore effective
security protection strategies available to online learning. Blogs allow self-motivated
bloggers to freely and easily post ideas, individual experiences, and opinions (Rubin,
Burkel, & Quan-Haase, 2011; Furukawa, Ishizuka, Matsuo, Ohmukai, & Uchiyama,
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2007). As blogs have a “high degree of exophoricity, quotation, brevity, and rapid of
content update” (Ulicny, Baclawski, & Magnus, 2007, p. 1), running a blog mining
analysis can improve the currency and relevance of this study (Chau & Xu, 2012).
However, blog posts can have an inherent bias. For example, the information on blogs is
not peer-reviewed; the authorship of some blog pages is either not clear or unknown;
and some blog information might be posted for commercial purposes. Therefore,
researchers need to be aware of these drawbacks as they carry out blog mining analysis.
Overall, this study combines blog mining with an extensive literature search to
overcome these shortcomings, in order to engender a comprehensive understanding of
the current state of security risks and protection in online learning.
Below is a description of how the blog mining was conducted.
Step one: Keywords, such as “online learning”, “ elearning”, “distance learning”,
“security”, and “risk”, were typed in the advanced search option of Google Blog Search
(http://www.google.com/blogsearch), a search tool specially designed to retrieve
content from blogs that are freely and publicly available on the Internet. To identify the
latest blog content discussing security risks and protection in online learning, the query
time period was set from January 01, 2010 to June 20, 2013. Next, the query was
performed. During this process, Google filtered similar blog posts first and then
returned 312 posts that were relevant to the keywords.
To track Internet users’ search interests regarding “online learning security” in recent
years, we applied Google Trends, a web-based search tool that provides the frequency of
some specific search terms or keywords queried over a specific period of time. The result
generated by Google Trends (see Figure 1) indicated that although the search frequency
of online learning security has fluctuated in a narrow range since 2010, the overall
attention paid to it has not changed much. This was consistent with the result we got via
a Google Blog search.
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Figure 1. Search frequency of “online learning security” shown by Google Trends.
Step two: The authors read through each page of the 312 blogs generated, removed 62
irrelevant and repetitive posts, and saved the content of the rest of the posts in a single
Word document as the sample data set. The sample data set provided a glimpse into the
ongoing concerns and discussion regarding security risks and protection in online
learning.
Step three: A concept analysis and mapping (CAAM) technique was applied to the data
by loading the data file into a special CAAM software tool called Leximancer
(http://www.leximancer.com), which extracted and classified the key concepts and
themes in the data, and further identified the patterns and the relationships between
concepts and themes. Leximancer has been adopted in quite a few studies in recent
years (Cretchley, Rooney, & Gallois, 2010; Smith & Humphreys, 2006; Watson, Smith,
& Watter, 2005). The Leximancer system is “a method for transforming lexical co-
occurrence information from natural language into semantic patterns in an
unsupervised manner” (Watson, Smith, & Watter, 2005). It uses word frequency and
co-occurrence data to identify which concepts (words that occur very frequently) exist in
a set of texts (Cretchley, Rooney, & Gallois, 2010). The technology behind the system is
based on Bayesian theory, which argues that fragmented information can be used to
predict what happens in a system (Watson, Smith, & Watter, 2005). Cretchley, Rooney,
and Gallois (2010) describe in detail the way in which Leximancer works:
The software includes an interactive concept-mapping
facility, which provides an overview of the conceptual
structure of the data set that assists the researcher in
interpretation. Concepts that co-occur often within the
same two-sentence coding block attract one another
strongly when the map is clustered, so that similar
concepts tend to settle together in close proximity.
Clusters of concepts are grouped by theme circles to
summarize the main ideas in particular clusters. Each
theme is named after the most prominent concept in that
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group, which is also indicated by the largest dot in the
theme cluster. (p. 319)
Figure 2 is a screenshot of the interface of Leximancer 4.0. The map in the middle
indicates the importance of the concepts. Red is the most important, followed by orange
and so on, according to the color wheel.
Figure 2. A screenshot of the interface of Leximancer 4.0.
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Results
According to an extensive literature search via academic databases and Google Scholar,
online learning faces various security risks (shown in Table 1), which mainly come from
external intruders.
Table 1
Security Risks and Protection Measures in Online Learning
Security risks
Protection measures
• ARP cache poisoning and
MITM attack
• Brute force attack
• Cross-Site Request Forgery
(CSRF)
• Cross Site Scripting (XSS)
• Denial of Service (Dos)
• IP spoofing
• Masquerade
• Rootkits
• SQL Injection
• Session Hijacking
• Session Prediction
• Stack-smashing attacks
(Serb, Defta, Iacob, & Apetrei, 2013;
Costinela-Luminita & Nicoleta-
Magdalena, 2012; Barik & Karforma,
2012; Srivastava & Sinha, 2013)
• Installing firewalls and anti-
virus software (Weippl & Ebner,
2008)
• Implementing Security
Management (ISM)
(Adams & Blandford, 2003;
Alwi & Fan, 2010)
• Improving authentication,
authorization, confidentiality,
and accountability
(Cardenas & Sanchez, 2005;
Agulla, Rifon, Castro, & Mateo,
2008)
• Using digital right management
and cryptography
(Barik & Karforma, 2012)
• Training security professionals
(Srivastava & Sinha, 2013)
To mitigate these risks, scholars have offered quite a few protection proposals (shown in
Table 1). In contrast, in the concept map generated by Leximancer, neither the risks nor
the protection measures can be easily identified. Figure 3 shows the concept map that
Leximancer generated after the blog data was loaded. The large circles represent the
clusters of concepts and the dots represent the main concepts. Leximancer can generate
many concept terms using its text analytics algorithms. For our study, those clusters
and concepts that appear with the highest frequency are listed in Table 2. It should be
noted that compared with Table 1, Table 2 shows quite different content.
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Figure 3. An example of the concept map generated by Leximancer with the sample
data.
Table 2
Cluster of Concepts Associated with Security in Online Learning in Blog Posts
Cluster of concepts
Concept
Learning
learning, students, online, use, course, environment,
teaching, courses, used, classroom, social, important,
experience, knowledge, different, distance, example,
virtual
Technology
technology, support, system, development, access,
training, provide, research, resources, educational,
quality, skills, institutions, developed
Education
education, work, world, schools, community, higher,
better, program, become, life, group, programs, making
Information
information, management, mobile, systems, software,
data, design, based, web, include, applications,
performance, network, provides
Content
content, using, tools, available, process, technologies, e-
learning, digital, level, computer, communication, offer,
assessment
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Discussion
Based on our extensive literature search and blog mining, we would like to provide a
more detailed discussion on the causes of security threats, security protection measures,
and the status of existing security protection for online learning.
Causes of Security Threats
Security threats in online learning can be examined from two aspects: the user side and
the management side. As far as the user side is concerned, emerging ICT applications
and imprudent human behavior are the main causes that lead to security issues in
online learning. Besides, of the security risks inherent in the Internet, the development
of new learning technologies such as Web 2.0 and social media have allowed for many
new security breaches and a much larger security impact (Adams & Blandford, 2003;
He, 2012). The amount of malicious content and the number of cyber-attacks on these
new Web applications is rapidly increasing in both frequency and sophistication.
Nowadays, many instructors are using social media sites such as Tumblr, Facebook,
Wikis, online forums, and Twitter to support collaborative learning in their online
courses (He, 2011; Camarero, Rodríguez, & José, 2012; Patel et al., 2012). However, for
unwary instructors and students, these social media sites pose a variety of serious
security risks and threats. For example, as a collaborative learning environment, a wiki
also becomes a ripe environment for hacking, deception, abuse, and misuse (Patel et al.,
2012). Personal data posted on social media sites can be misused in many ways (e.g., for
virtual insult or, worse, for financial gain). Furthermore, recent studies show that social
media sites are more likely to be used for delivering malware than were previously
popular methods of email delivery (Kaspersky, 2009; He, 2013).
Other scholars analyze security issues from the standpoint of the user. For example,
Adams and Blandford (2003) argue that threats to online learning security are caused
by two main reasons: 1) The security mechanisms used in online learning programs lack
usability; and/or 2) security discipline is not user-centered and therefore can lead the
user to overlook serious security risks. They point out that the need-to-know principle
(restricting information only to those who need to know) coupled with the unwillingness
of security departments to know their users can cause a low usability of security
mechanisms. Due to the lack of usability, many online learning systems do not provide
users with adequate feedback or with the control rights that would allow them to protect
their data (Adams & Blandford, 2003). Furthermore, poor user-centered design of
security mechanisms and policy can contribute to insecurity and to users’ low
motivation to seek security (Adams & Sasse, 1999).
From the perspective of management, online learning providers have made some
mistakes. In the domain of online learning, threats not only come from outsiders, but
also from insiders (Alwi & Fan, 2010). Many scholars argue that security risks are
caused by online learning providers’ underdeveloped security policies and immature
security measures. For instance, Serb, Defta, Iacob, and Apetrei (2013) note that
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although more people are currently taking online courses, the security risks inherent in
online learning have not been seriously taken into account in the actual educational
context. Alwi and Fan (2010) point out that many online learning providers rush into
adopting information communication technology without fully understanding the
related security concerns. Yao and Ji (2011) note that online learning system designers
consider the quality of online course content a considerably bigger issue than the
security of their online systems. Furthermore, Weippl and Ebner (2008) indicate that
even though almost all institutions have firewalls and anti-virus software to protect their
campus resources, they often fail to perform adequate information system security
management. Unfortunately, content and technology are still the focuses of online
learning (Srivastava & Sinha, 2013). We feel that more attention should be put on the
security aspect of online learning. In fact, security is very important for online learning
because lacking security in online learning will cause a number of serious problems. For
example, as Adams and Blandford (2003) point out, any security risk in online learning
can dramatically affect students’ perception of reliability and trustworthiness about
learning via the Internet. As such, online learning will be less attractive and the
development of online learning will be hindered. In addition, ICT applications make
user authentication a big challenge for student assessment in online learning. When
assessing students’ asignments, as Alwi and Fan (2010) argue, it is very hard to verify
whether an assignment is completed and/or submited by a valid student. If student
assessment is not conducted correctly, the quality of online learning will be harmed
greatly.
Security Protection Measures
Scholars have discussed security protection from the user side and management side as
well. From the user side, protection motivation theory (PMT), a theory originally from
social psychology, is introduced into the field of information system security. Based on
this theory, information is perceived and evaluated, and then provides supports for
users to take actions (Crossler, 2010). This theory explains the cognitive mediating
process and coping modes when users encounter information sources. The PMT theory
is helpful for understanding security protection measures adopted by online learning
users.
From the management side, general deterrence theory (GDT), a theory from criminal
justice, is adopted by information system security scholars to explain how security
countermeasures can increase the perceptions of members in an organization regarding
the severity and certainty of punishment for any misuse of information (Straub, 1990).
Security policies and mechanisms in online learning must support authentication,
authorization, confidentiality, and accountability (Cardenas & Sanchez, 2005; Agulla,
Rifon, Castro, & Mateo, 2008). Authentication refers to the validation of a person’s
identity before the access is assigned. Authorization defines what rights and services a
person can access after the authentication process is passed. Confidentiality means that
some specific information or data cannot be disclosed to anyone who is not authorized.
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Accountability refers to the methodology by which users’ resource consumption
information is collected for billing, auditing, and capacity-planning purposes (Song,
Lee, & Nam, 2013).
To mitigate security threats and risks in online learning, researchers have proposed
many remedies from a variety of points of view. For example, Alwi and Fan (2010)
propose information security management (ISM) for online learning providers, in order
to build an effective security architecture that can fight existing and emerging
information security threats. They argue that ISM should include policies, process,
procedures, organizational structures, and software and hardware functions, in order to
enhance the execution of security measures. Furnell and Karweni (2001) depict a
framework that includes five aspects: 1) authentication and accountability; 2) access
control; 3) protection of communications; 4) non-repudiation issues; 5) learning
resource provider server protection. Srivastava and Sinha (2013) highly recommend
that information security professionals improve their security knowledge and skills by
using the Virtual Training Environment (VTE), a web-based knowledge library launched
by the Carnegie Mellon Software Engineering Institute.
Security Protection Status
By comparing the results from the two research methods (Table 1 and Table 2), it is
obvious that security is not a prime focus of blog posts discussing online learning, even
though the topic has attracted much attention in the academic domain. Given the
analysis of the causes of security risks in online learning, security is not at the top of the
priority list in distance learning providers’ hands. As long as a decade ago, Furnell and
Karweni (2001) noted, “Security represents an aspect that may not suggest itself as a
high priority in an education environment.” The differences between the results
generated by the two research methods confirm the scholars’ conclusions, as mentioned
above: The security risks inherent in online learning have not been seriously taken into
account in an educational context. It may be that security issues have not caused as
much damage in the realm of distance learning as they have in the business world. Since
nothing serious about security has yet happened in the realm of online learning, not
much attention has been paid to it in blog posts so far.
Research Trends
During the past decade, online learning has quickly grown. It has grown, perhaps, too
quickly – too little attention has been paid to its security. Online learning will become
more user-centered and more secure with the help of new technologies.
1. Personal Learning Environment and Biometric Authentication
Authentication has been widely adopted in online learning as a tool to improve
confidentiality. Generally speaking, there are three ways to authenticate a user: 1)
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knowledge-based authentication that requires that users provide something that only
they know (e.g., type in a password, answer a secret question, or submit a personal
identification number); 2) token-based authentication that requires that users show
something that only they own (e.g., a key card, a mobile device, or a security token); 3)
biometrics that require that users provide something for measurement (e.g., a
fingerprint, a palm print, a retinal image, or a face gesture) (Garfinkel & Spfford, 1996;
Alotaibi & Argles, 2011). Among these authentication methods, passwords and personal
identification numbers (PINs) are most widely used (Adams & Blandford, 2003). As
Raitman, Ngo, Augar, and Zhou (2005) note, user logins are the simplest means for
providing identity and access services.
The next generation of online learning system is a personal learning environment (PLE),
“a learning environment where the student is able to customize his/her learning
environment based on pedagogical and personal choices” (Kolas & Staupe, 2007). As a
new way of using the web or Web 2.0 for learning, the PLE focuses on the individual and
“presents learners with learning resources based on individual interests, education level,
attitude and cultural, social and other factors” (Li & Gu, 2009). It is a framework that
integrates Web 2.0 and social tools, such as blogs, wikis, Facebook, podcasting, and
videocasting, according to the choice of learners (Alotaibi & Argles, 2011; Kompen,
Edirisingha, & Mobbs, 2008). As Alotaibi and Argles (2011) point out, the widespread
authentication mechanism of username and password is out of date for use in the PLE,
because learners have to sign on to multiple systems, each of which may involve a
different username and password. As intruders and hackers become smarter and more
technologically savvy (Science News, 2002), easy passwords make intrusion very
achievable for malicious users, even as long and complex passwords are impractical for
learners to remember (Gligor, 1993). According to a survey carried out in Alotaibi and
Argles (2011), the average internet user has to remember 15 access control passwords.
Thus, a one-stop solution that is not dependent on a series of characters but on a
technology, which is unique and can only be possessed by a specific individual, is
needed for PLE. As such, Alotaibi and Argles (2011) have proposed a biometric
authentication system, FingerID, which requires a fingerprint scan and human
interaction to utilize a service. Meanwhile, Song, Lee, and Nam (2013) have proposed
another method that uses brain wave and eye movement to authenticate users of online
learning systems. Biometrics refers to the use of identification mechanisms, such as a
fingerprint and retina scan, to certify that a person in front of a computer is indeed the
intended person (Sasikumar, 2013). Biometric authentication seems to be the option for
the next generation of authentication (Wang, Ge, Zhang, Chen, Xin, & Li, 2013).
2. Security for Online Assessments
As a major component in online learning, online assessments are important, both to
ascertain students’ progress and because they can be carried out flexibly in different
locations and at different times (Reeves, 2000; Meyer & Zhu, 2013). According to a
study carried out by King, Guyette, and Piotrowski (2009), 73.6% of students think that
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it is easier to cheat in an online environment than in a conventional one. Methods of
cheating on online assessments include online communication, telecommunication,
internet surfing (Rogers, 2006), copying and pasting from online sources (Underwood
& Szabo, 2003), obtaining answer keys in an illegitimate way, taking the same
assessment several times, and getting unauthorized help (Rowe, 2004).
Other means of cheating on online tests include someone other than the actual student
taking the online test and the copying of answers from elsewhere (Sasikumar, 2013).
Ndume, Tilya, and Twaakyondo (2008) argue that preventing cheating in online course
assessments is much harder than in traditional classrooms and that secure assessment
of online courses requires the improvement of system security, the registration of
learners with unique identification, and the overall administration of the online
assessment. Therefore, improving the security of online learning will improve the
security of online assessments, and this should not be neglected. The one-stop security
solution for the next generation of online learning needs to assure the security of online
assessment, as well.
3. The Goal of Security for Online Learning
Online learning is built on trust, information exchange, and discussion. However, a
secure environment can rely on distrust, restricted information flow, and autocratic
rules (Adams & Blandford, 2003). These attributes can make online learning and
security mutually exclusive concepts. In addition, Weippl and Ebner (2008) indicate
that no system can ever be totally secure while still remaining usable. What level of
security does online learning need? Needless to say, the goal of security in online
learning is definitely not to limit its usability. However, currently, online learning
providers are facing a difficult balance, as they try to provide sufficient security to
protect online learning resources while not inhibiting the appropriate use of these
resources. Maintaining such a balance is challenging due to diversity – the diversity of
computers and devices as well as a large number of diverse users (Pendegraft, Rounds,
& Stone, 2010). Although this study shows that security is not a top priority for many
online learning providers right now, serious efforts are needed to improve the security
in online learning. The goal of security for online learning is to maintain the
confidentiality, integrity, and availability of the resources in online learning at a certain
level while keeping their usability acceptable for learners.
Conclusion
The growing availability of the Internet and the number of diverse end user devices
facilitate the demands of online learning. The application of Web 2.0 and MOOCs are
heralding a new era in education. Online learning brings with it all of the security risks
inherent to the use of the Internet. However, although more people are taking online
courses, online learning providers have not been seriously taking security risks into
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account. Many of them rush into adopting information communication technologies
without fully understanding the related security concerns. Scholars have identified
diverse security risks and have proposed solutions to mitigate the security threats in
online learning. To our surprise, our study found that security is not a hot topic among
blog posts which discuss online learning. So far, online learning providers and
practitioners have not considered security as a top priority, possibly because few serious
security incidents have happened in the realm of online learning. As more and more
people are studying online, more attention and efforts are needed from online learning
providers and practitioners to prevent possible security breaches in online learning
before it is too late.
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