Space Laboratories

Cohen, Marc

doi:10.4271/2001-01-2142

Cited by 7 publications

(1 citation statement)

References 34 publications

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“…This research intends to use the information of students in learning, such as portions where there are more pauses when viewing a textbook, the technical terms of a query, the question of a chat robot, and the download statistics of an online textbook (Cohen et al, 2001;Lim & Cho, 2006;Liao et al, 2011). This information is transmitted to the system for storage in real time; for future tracking analysis, the teacher can clearly understand the students' problems when they are recommending other related textbooks to help students solve their difficulties immediately, and even when giving feedback to teachers for consultations to adjust online textbooks (Bell et al, 2021;Homsi et al, 2008).…”

Section: Mobile Learningmentioning

confidence: 99%

Intelligent and Interactive Chatbot Based on the Recommendation Mechanism to Reach Personalized Learning

Yao

2022

International Journal of Information and Communication Technology Education

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With the impacts of Covid-19 epidemic, e-learning has become a popular research issue. Therefore, how to upgrade the interactivity of e-learning, and allow learners to quickly access personalized and popular learning information from huge digital materials, is very important. However, chatbots are mostly used in automation, as well as simple occasions of general standard question and answer. But to solve the different problems of e-learners in the learning process, chatbots are used to filter the blind spots of learners and to provide further relevant information, so that e-learning can improve in efficiency and interactivity. This study utilizes AI, two-stage Bayesian algorithm, and crawler technology to provide customized learning materials according to learner's current learning situation. The experimental results show that this research system can indeed correctly understand and judge the blind spots of digital learners, and effectively find the relevant e-learning and video information. The accuracy rate reaches nearly 90%.

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Section: Mobile Learningmentioning

confidence: 99%

Intelligent and Interactive Chatbot Based on the Recommendation Mechanism to Reach Personalized Learning

Yao

2022

International Journal of Information and Communication Technology Education

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Discovering Novel Attack Strategies from Infosec Alerts

Qin

Lee

Data Warehousing and Data Mining Techniques for Cyber Security

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Discovering Novel Attack Strategies from INFOSEC Alerts

Qin

Lee

2004

Computer Security – ESORICS 2004

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Correlating security alerts and discovering attack strategies are important and challenging tasks for security analysts. Recently, there have been several proposed techniques to analyze attack scenarios from security alerts. However, most of these approaches depend on a priori and hard-coded domain knowledge that lead to their limited capabilities of detecting new attack strategies. In this paper, we propose an approach to discover novel attack strategies. Our approach includes two complementary correlation mechanisms based on two hypotheses of attack step relationship. The first hypothesis is that attack steps are directly related because an earlier attack enables or positively affects the later one. For this type of attack relationship, we develop a Bayesian-based correlation engine to correlate attack steps based on security states of systems and networks. The second hypothesis is that for some related attack steps, even though they do not have obvious and direct relationship in terms of security and performance measures, they still have temporal and statistical patterns. For this category of relationship, we apply time series and statistical analysis to correlate attack steps. The security analysts are presented with aggregated information on attack strategies from these two correlation engines. We evaluate our approach using DARPA's Grand Challenge Problem (GCP) data sets. The results show that our approach can discover novel attack strategies and provide a quantitative analysis of attack scenarios.

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Space Laboratories

Cited by 7 publications

References 34 publications

Intelligent and Interactive Chatbot Based on the Recommendation Mechanism to Reach Personalized Learning

Intelligent and Interactive Chatbot Based on the Recommendation Mechanism to Reach Personalized Learning

Discovering Novel Attack Strategies from Infosec Alerts

Discovering Novel Attack Strategies from INFOSEC Alerts

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