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A Blockchain-enabled Multi-domain DDoS Collaborative Defense Mechanism

  • Huifen Feng;Ying Liu;Xincheng Yan;Na Zhou;Zhihong Jiang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.3
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    • pp.916-937
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    • 2023
  • Most of the existing Distributed Denial-of-Service mitigation schemes in Software-Defined Networking are only implemented in the network domain managed by a single controller. In fact, the zombies for attackers to launch large-scale DDoS attacks are actually not in the same network domain. Therefore, abnormal traffic of DDoS attack will affect multiple paths and network domains. A single defense method is difficult to deal with large-scale DDoS attacks. The cooperative defense of multiple domains becomes an important means to effectively solve cross-domain DDoS attacks. We propose an efficient multi-domain DDoS cooperative defense mechanism by integrating blockchain and SDN architecture. It includes attack traceability, inter-domain information sharing and attack mitigation. In order to reduce the length of the marking path and shorten the traceability time, we propose an AS-level packet traceability method called ASPM. We propose an information sharing method across multiple domains based on blockchain and smart contract. It effectively solves the impact of DDoS illegal traffic on multiple domains. According to the traceability results, we designed a DDoS attack mitigation method by replacing the ACL list with the IP address black/gray list. The experimental results show that our ASPM traceability method requires less data packets, high traceability precision and low overhead. And blockchain-based inter-domain sharing scheme has low cost, high scalability and high security. Attack mitigation measures can prevent illegal data flow in a timely and efficient manner.

What Is a Monster Narrative? Seven Fragments on the Relationship between a Monster Narrative and a Catastrophic Narrative (괴물서사란 무엇인가? - 괴물서사에서 파국서사로 나아가기 위한 일곱 개의 단편 -)

  • Moon, Hyong-jun
    • Cross-Cultural Studies
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    • v.50
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    • pp.31-51
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    • 2018
  • The concept of 'monsters' have become popular, again, in recent times. A number of 'monster narratives' that discuss monsters such as zombies, humanoids, viruses, extraterrestrials, and serial killers have been made and re-made in popular media. Noting such an interesting cultural context, this article attempts, first, to find out some essential prototypical elements of a monster narrative and, second, to relate it with a catastrophic narrative. Correspondingly, the word 'monster' has been used as a conceptual prototype category that denies universal and clear definition, which makes it as one of the most widely used and familiar subjects of the use of metaphor. The prototypical meanings of various monster figures can be converged on a certain creature of being in this way held out as bizarre, curious, and abnormal. The monster figure that surpasses existing normality is also connected to 'abjection,' such as something that is cast aside from the body such as the bodily functions seen in its associated blood, tears, vomit, excrement, or semen, and so on. Nevertheless, both the monster figure and abjection produce disgust and horror in the minds of ordinary spectators or readers of media using this metaphor to heighten excitement for the viewers. The abject characteristic of the monster figure also has something in common with the posthuman figure, meaning to apply to a category of inhuman others who are held outside of the normal category of human beings. In the similar vein, it is natural that the most typical monster figures in our times are posthuman creatures embodied in such forms as seen with zombies, humanoids, cyborgs, robots, and so on. In short, the monster figure includes all of the creatures and beings that disarray normalized humanist categories and values. The monster narrative, in the same sense, is a type of story that tells about others outside modern, anthropocentric, male-centered, and Westernized categories of thought. It can be argued that a catastrophic narrative, a literary genre which depicts the world where a series of catastrophic events demolish the existing human civilization, ought to be seen as a typical modern-day monster narrative, because it also discounts and criticizes normalized humanist categories and values as is the result of the monster narrative. Going beyond the prevailing humanist realist narrative that are so familiar with existing values, the catastrophic narrative is not only a monster narrative per se, but also a monstrous narrative which disrupts and reinvents currently mainstream narratives and ways of thinking.

Topic Modeling Insomnia Social Media Corpus using BERTopic and Building Automatic Deep Learning Classification Model (BERTopic을 활용한 불면증 소셜 데이터 토픽 모델링 및 불면증 경향 문헌 딥러닝 자동분류 모델 구축)

  • Ko, Young Soo;Lee, Soobin;Cha, Minjung;Kim, Seongdeok;Lee, Juhee;Han, Ji Yeong;Song, Min
    • Journal of the Korean Society for information Management
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    • v.39 no.2
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    • pp.111-129
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    • 2022
  • Insomnia is a chronic disease in modern society, with the number of new patients increasing by more than 20% in the last 5 years. Insomnia is a serious disease that requires diagnosis and treatment because the individual and social problems that occur when there is a lack of sleep are serious and the triggers of insomnia are complex. This study collected 5,699 data from 'insomnia', a community on 'Reddit', a social media that freely expresses opinions. Based on the International Classification of Sleep Disorders ICSD-3 standard and the guidelines with the help of experts, the insomnia corpus was constructed by tagging them as insomnia tendency documents and non-insomnia tendency documents. Five deep learning language models (BERT, RoBERTa, ALBERT, ELECTRA, XLNet) were trained using the constructed insomnia corpus as training data. As a result of performance evaluation, RoBERTa showed the highest performance with an accuracy of 81.33%. In order to in-depth analysis of insomnia social data, topic modeling was performed using the newly emerged BERTopic method by supplementing the weaknesses of LDA, which is widely used in the past. As a result of the analysis, 8 subject groups ('Negative emotions', 'Advice and help and gratitude', 'Insomnia-related diseases', 'Sleeping pills', 'Exercise and eating habits', 'Physical characteristics', 'Activity characteristics', 'Environmental characteristics') could be confirmed. Users expressed negative emotions and sought help and advice from the Reddit insomnia community. In addition, they mentioned diseases related to insomnia, shared discourse on the use of sleeping pills, and expressed interest in exercise and eating habits. As insomnia-related characteristics, we found physical characteristics such as breathing, pregnancy, and heart, active characteristics such as zombies, hypnic jerk, and groggy, and environmental characteristics such as sunlight, blankets, temperature, and naps.