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  • Open Access

    ARTICLE

    Dark-Forest: Analysis on the Behavior of Dark Web Traffic via DeepForest and PSO Algorithm

    Xin Tong1, Changlin Zhang2,*, Jingya Wang1, Zhiyan Zhao1, Zhuoxian Liu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 561-581, 2023, DOI:10.32604/cmes.2022.022495

    Abstract The dark web is a shadow area hidden in the depths of the Internet, which is difficult to access through common search engines. Because of its anonymity, the dark web has gradually become a hotbed for a variety of cyber-crimes. Although some research based on machine learning or deep learning has been shown to be effective in the task of analyzing dark web traffic in recent years, there are still pain points such as low accuracy, insufficient real-time performance, and limited application scenarios. Aiming at the difficulties faced by the existing automated dark web traffic analysis methods, a novel method… More >

  • Open Access

    ARTICLE

    An Ensemble Approach to Identify Firearm Listing on Tor Hidden-Services

    Hashem Alyami1, Mohd Faizan2, Wael Alosaimi3, Abdullah Alharbi3, Abhishek Kumar Pandey2, Md Tarique Jamal Ansari4, Alka Agrawal2, Raees Ahmad Khan2,*

    Computer Systems Science and Engineering, Vol.38, No.2, pp. 141-149, 2021, DOI:10.32604/csse.2021.017039

    Abstract The ubiquitous nature of the internet has made it easier for criminals to carry out illegal activities online. The sale of illegal firearms and weaponry on dark web cryptomarkets is one such example of it. To aid the law enforcement agencies in curbing the illicit trade of firearms on cryptomarkets, this paper has proposed an automated technique employing ensemble machine learning models to detect the firearms listings on cryptomarkets. In this work, we have used part-of-speech (PoS) tagged features in conjunction with n-gram models to construct the feature set for the ensemble model. We studied the effectiveness of the proposed… More >

  • Open Access

    ARTICLE

    A Link Analysis Algorithm for Identification of Key Hidden Services

    Abdullah Alharbi1, Mohd Faizan2, Wael Alosaimi1, Hashem Alyami3, Mohd Nadeem2, Suhel Ahmad Khan4, Alka Agrawal2, Raees Ahmad Khan2,*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 877-886, 2021, DOI:10.32604/cmc.2021.016887

    Abstract The Tor dark web network has been reported to provide a breeding ground for criminals and fraudsters who are exploiting the vulnerabilities in the network to carry out illicit and unethical activities. The network has unfortunately become a means to perpetuate crimes like illegal drugs and firearm trafficking, violence and terrorist activities among others. The government and law enforcement agencies are working relentlessly to control the misuse of Tor network. This is a study in the similar league, with an attempt to suggest a link-based ranking technique to rank and identify the influential hidden services in the Tor dark web.… More >

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