A New Model for Simultaneous Detection of Phishing and Darknet Websites

Xu, Jie; Lan, Haoliang; Ju, Ao

doi:10.1109/iccc54389.2021.9674357

Cited by 4 publications

(3 citation statements)

References 10 publications

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“…The Darkweb is often associated with cybercrime, including phishing attacks. Recent studies have detected phishing and other malicious activity in the Darkweb [ 79 ]. For example, developing machine learning techniques and data analytics tools can help identify and track phishing campaigns and other forms of cybercrime [ 80 ].…”

Section: Discussionmentioning

confidence: 99%

Darkweb research: Past, present, and future trends and mapping to sustainable development goals

Raman,

Kumar Nair,

Nedungadi

et al. 2023

Heliyon

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Section: Discussionmentioning

confidence: 99%

Darkweb research: Past, present, and future trends and mapping to sustainable development goals

Raman,

Kumar Nair,

Nedungadi

et al. 2023

Heliyon

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“…(1) From the standpoint of professional engineering certification [6], it is essential to adhere to the paradigm and standards of the Sydney Agreement, to carry out professional construction for international certification, to implement result-oriented education, and to develop results-oriented curriculum systems. It is also necessary to carry out the full process, comprehensively evaluated professional courses in a scientific and reasonable https://doi.org/10.1051/shsconf/202316601037 SHS Web of Conferences 166, 01037 (2023) EIMM 2022 manner, and to enhance the professional connotation.…”

Section: Researches On Reforming Of Mould Coursesmentioning

confidence: 99%

Courses reform of mould courses based on field augmented reality facing engineering education certification

et al. 2023

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Mould courses are crucial components of the mechanical manufacturing course system, and their innovation and reform can inspire new approaches to college education reform, as for the engineering education certification process. The augmented reality mould disassembly and assembly teaching scheme that is proposed in this paper can help students master the structure and processing of complicated moulds, and thus make comprehensive use of the relating learning knowledge and skills. By understanding of the typical structural design and assembly of moulds, students can learn actively by interaction of the three teaching strands of instruction, case study, and assessment. This will raise the level of instruction throughout the courses as well as student participation and interest. The proposed AR auxiliary system is a new approach to essentially foster students’ capacity for independent learning, knowledge understanding, and innovation and production in the age of digital learning and engineering education certification.

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“…Fan et al [20] used a Fast Unfolding algorithm to cluster websites and extract URL features of illegal websites, and judged whether they were illegal websites by detecting the URL features of unknown websites. Xu et al [21] used a density clustering algorithm to cluster dark web sites, phishing sites, and normal websites, which proved the effectiveness of clustering on the classification of dark web sites and phishing sites. Li et al [22] proposed a gambling website detection method based on the PAM probabilistic topic model.…”

Section: Related Work 221 Detection Of Illegal Websitesmentioning

confidence: 99%

Multi-Modal Clustering Discovery Method for Illegal Websites Based on Network Surveying and Mapping Big Data

Wang,

Shi,

Zheng

2023

Applied Sciences

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With the development of internet technology, the number of illicit websites such as gambling and pornography has dramatically increased, posing serious threats to people’s physical and mental health, as well as their financial security. Currently, the governance of such illicit websites mainly focuses on limited-scale detection through manual annotation. However, the need for effective solutions to govern illicit websites is urgent, requiring the ability to rapidly acquire large volumes of existing website data from the internet. Web mapping engines can provide massive, near real-time web data, which plays a crucial role in batch detection of illicit websites. Therefore, in this paper, we propose a method that combines web mapping engine big data to perform unsupervised multimodal clustering (MDC) for illicit website discovery. By extracting features based on contrastive learning methods from webpage screenshots and OCR text, we conduct feature similarity clustering to identify illicit websites. Finally, our unsupervised clustering model achieved an overall accuracy of 84.1% on all confidence levels, and a 92.39% accuracy at a confidence level of 0.999 or higher. By applying the MDC model to 3.7 million real web mapping data, we obtained 397,275 illicit websites primarily focused on gambling and pornography, with 14 attributes. This dataset is made publicly.

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A New Model for Simultaneous Detection of Phishing and Darknet Websites

Cited by 4 publications

References 10 publications

Darkweb research: Past, present, and future trends and mapping to sustainable development goals

Darkweb research: Past, present, and future trends and mapping to sustainable development goals

Courses reform of mould courses based on field augmented reality facing engineering education certification

Multi-Modal Clustering Discovery Method for Illegal Websites Based on Network Surveying and Mapping Big Data

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