With the rapid growth of Internet services, virtual world has witnessed an increasingly large number of online users who have a variety of needs such as accessing various websites to gather information, easing busines...
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With the rapid growth of Internet services, virtual world has witnessed an increasingly large number of online users who have a variety of needs such as accessing various websites to gather information, easing business transactions, and sharing updates. As a result, information security has become a major concern among online users, and the verification of access codes is now the main practice used to keep information systems safe. However, some issues arise as the result of coding and managing behavior, and this research seeks to address these issues. After following the Focus Group method and interviewing 13 college students, this research finds that forgetting the access code is one of the biggest challenges to most online users simply because of the longer duration and the time when the users have a need to access the websites again, their memory will eclipse. In addition, online users usually develop self-constructed rules to cope with elusive code. These rules include: creating some sets of code that may not be meaningful to outsiders;taking different degrees of complex measures to register authentication codes, dependent upon the importance of the websites to the online users;writing the authentication codes on a scratch-pad and sticking it on the computer screen;and keeping the codes in a notebook or computer file. The above practices nevertheless run the risk of being usurped by hackers, and it is found that hacking frequently takes place among closest friends, as they are quite familiar with the coding behavior of the victims. While assisting coding management does not help in this regard, as it is generally too expensive, online users troubled by the forgetting of access codes often end up with re-applying for a new set of authentication codes after unsuccessfully trying to login. All these self-constructed rules, nevertheless, constitute threat to information security. The research, in conclusion, calls for an education campaign to promote healthy coding
Secure coding is a mission that cannot be neglected as computing devices continue increasing. Every year, thousands of new software vulnerabilities are identified. Education is a crucial factor and a significant chall...
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ISBN:
(纸本)9781450371056
Secure coding is a mission that cannot be neglected as computing devices continue increasing. Every year, thousands of new software vulnerabilities are identified. Education is a crucial factor and a significant challenge to counter cyber threats. But gaining insight into how people learn has always been challenging. There is a considerable need for improved methodologies with active hands-on educational techniques for programmers to learn practical strategies to mitigate software vulnerabilities;to protect private data;and ultimately to write secure code in the first place. To the best of our knowledge, this is the first usage of eye tracking technologies to understand secure coding practices and to improve education. We focused on exploring the ways that students comprehended and learned to develop secure software. We recorded their eye gaze movements while they studied our hands-on learning module and mitigated the weaknesses within the source code. Our study involved 29 students mitigating software vulnerabilities via manual analysis of the source code. The eye tracking data allows us to objectively study and gain insight in order to understand and improve students learning behavior. Our analysis indicates that there is a distinction in the learning phase for students that answered correctly compared to students that did not provide the correct mitigation strategy. Specifically, our research indicates the most effective and efficient way to learn secure coding is to fully understand coding errors before working on the source code. Our findings also suggest that we can use reading patterns to understand student behaviors in order to be capable of developing improved hands-on learning material.
Protean malware mutations and premeditated cyber attacks are threatening security of information systems world-wide. There is an urgent need for effective methods to trace the source of code. In this paper, through st...
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ISBN:
(纸本)9781538655009
Protean malware mutations and premeditated cyber attacks are threatening security of information systems world-wide. There is an urgent need for effective methods to trace the source of code. In this paper, through study of coding behavior, which is a social characteristic of code, we trace the source of code preliminarily. Based on function-calling relation graph, three function-calling features of code are proposed to distinguish different coding patterns of programmers: relative edit distance shows the orderliness of code, semivariogram reveals programmers coding logic (Breadth First coding or Depth First coding) and ODD value suggests different function arrangement styles. Tested in experiments, these features are able to trace the coding behavior patterns of programmers, providing assistance with source tracing as expected.
Students working on their own, or in small groups, on tasks given to them by the teacher is a typical element of programming lessons. The task, if suitably complex, is meant to go beyond merely applying learned progra...
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ISBN:
(纸本)9798400710056
Students working on their own, or in small groups, on tasks given to them by the teacher is a typical element of programming lessons. The task, if suitably complex, is meant to go beyond merely applying learned programming concepts to (computational) problem solving. There have been some attempts to classify problem solving processes and to identify how students can succeed or fail in such a scenario, however, comparatively little is known on this part of programming education when compared to other research on programming. This article presents the results of an exploratory, observational study of students in grade 7 (N = 28) that work on a task. The behavior was recorded and qualitatively coded using the CCPS model of Chevalier et al. [6] as a deductive starting point. During coding we inductively refined this model to better explain what happens during that time students spend coding. The newly introduced subcategories were then used to help explain whether students successfully solved the task. The results show that out of a number of variables, the distinction between a more arbitrary and a more purposeful behavior when interacting with the programming environment was the only significant predictor and the different groups are also picked up in a clustering of the various approaches of students.
Programming assignment source code plagiarism detection is one of the important challenges in intelligent education. This paper provides an overview of program detection techniques in this field, reviews the related l...
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