An Extensive Study and Review on Dark Web Threats and Detection Techniques

An Extensive Study and Review on Dark Web Threats and Detection Techniques

DOI: 10.4018/978-1-6684-8133-2.ch011
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Abstract

The Dark Web is a difficult and anonymous network used by cybercriminals, terrorists, and state-sponsored agents to carry out their illicit goals. Dark web cybercrime is very similar to offline crime. However, the vastness of the Dark Web, its unpredictable ecology, and the anonymity it provides are all obstacles that must be overcome in order to track down criminals. To reach the dark web, which is not indexed by search engines, you must use the anonymous Tor browser. The anonymity and covert nature of the network make it ideal for criminal activity and the launch of carefully orchestrated, malicious assaults. Online criminal activity is rampant and getting more intense, according to specialists in cyber security. This chapter has provided a thorough analysis of the various attacks and attack strategies utilized on the dark web. In addition, the authors examine the strengths and weaknesses of the various methods currently in use for threat detection, and how they apply to anonymity networks such as Tor, I2P, and Freenet.
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Introduction

There is an unprecedented quantity of digital data in the world wide web (WWW), a complicated system. Search engines like Google and Yahoo are used for reaching the common Internet that is used every day. Large portions of the Internet, however, are not indexed and are concealed from common search engines (Weimann, 2016a). The Deep Web, which accounts for about 96 percent of the World Wide Web, is this hidden area of the Internet. The DarkWeb, also known as the Dark Net, is a section of the Deep Web that is primarily used for illegal purposes (Anjum et al., 2021). According to a survey by the University of Surrey, there was roughly $1.5 trillion in revenue generated by cybercrimes in 2018 (Saleem et al., 2022), and these crimes are expected to grow in frequency and aggression over time(Attaallah et al., 2022; Husain, 2019, 2020; M. Z. Khan, Husain, et al., 2020; W. Khan & Haroon, 2022b; Sahu et al., 2020).

The TOR network, which allows users to secretly and anonymously share information via peer-to-peer connections rather than a centralised computer server, is the most well-known tool on the Dark Web (Masinde & Graffi, 2020). The U.S. Naval Research Laboratory created this service in 2002 with the goal of allowing users to access blocked content, get around censorship, and protect the privacy of confidential communications (Watson, 2012). Due to the TOR network's anonymous nature, it is very difficult to monitor the Dark Web. Due to its untraceable and challenging to close down infrastructure, criminals use the Onion Router (TOR) to access the Dark Web (Gehl, 2016). The intense strain placed on security organisations and law enforcement to track and monitor activity on the Dark Web is one of the reasons for this.

The majority of dark web sites are secured, which aids in protecting user anonymity and making their actions difficult to track. Overlay networks are the basis for anonymity tools that allow users to interact globally without disclosing their identities or locations (Vasserman et al., 2009). Researchers have applied overlay methods to a wide range of problems, including anonymous communication and polling; communication censorship; private information retrieval; taxonomy; traffic analysis; and more. Anonymizer.com and gotrusted.com are just two examples of the many businesses and individuals who supply privacy services; others include the open-source Tor Network, FreeNet, Subgraph Operating System, and the Invisible Internet Project (I2P) (Zhang & Zou, 2020) (Marcella, 2021; Quasim et al., 2023). Onion sites, also known as secret services, are a type of website found on the dark web that can only be accessed by using a special browser. Tor’s wide adoption can be attributed to the anonymity it affords users, making them less of a target for oppressive governments (Gallagher et al., 2017; Husain & Khan, 2019; M. Z. Khan, Mishra, et al., 2020; M. Z. Khan, Shoaib, et al., 2020).

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