Perceptual Operating Systems for the Trade Associations of Cyber Criminals to Scrutinize Hazardous Content

Pub Date : 2024-05-06 DOI:10.4018/ijcwt.343314
Romil Rawat, Anand Rajavat
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Abstract

The limits of user visibility have been exceeded by the internet. The “Dark Web” or “Dark Net” refers to certain unknown portions of the internet that cannot be found using standard search methods. A number of computerised techniques are being explored to extract or crawl the concealed data. All users can freely interact on the surface web. Identity identities may be found on the deep web, and the dark web (DW), a hub for anonymous data, is a haven for terrorists and cybercriminals to promote their ideologies and illegal activities. Officials in clandestine surveillance and cyberpolicing are always trying to track down offenders' trails or hints. The search for DW offenders might take five to ten years.The proposed study provides data from a DW mining and online marketplaces situation from a few domains, as well as an overview for investigators to build an automated engine for scraping all dangerous information from related sites.
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网络罪犯行业协会审查危险内容的感知操作系统
互联网已经超越了用户可见度的极限。暗网 "或 "黑网 "指的是互联网上某些未知部分,用标准搜索方法无法找到。人们正在探索一些计算机技术,以提取或抓取隐藏的数据。所有用户都可以在表层网络上自由互动。身份标识可以在深网上找到,暗网(DW)是匿名数据的中心,是恐怖分子和网络罪犯宣传其意识形态和非法活动的天堂。从事秘密监视和网络警察工作的官员总是试图追踪罪犯的踪迹或蛛丝马迹。拟议的研究提供了几个域的 DW 挖掘和在线市场情况的数据,并为调查人员提供了一个概述,以便建立一个自动引擎,从相关网站上搜刮所有危险信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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