Unveiling Challenges and Solutions with Intelligence in the Dark and Deep Web

Document Type

Conference Proceeding

Source of Publication

Lecture Notes in Networks and Systems

Publication Date

1-1-2024

Abstract

This study delves into the obscured realms of the internet, namely the Deep Web and the Dark Web, which piqued public curiosity following the Silk Road takedown. Despite this interest, widespread misunderstanding persists regarding these clandestine domains. The Deep Web constitutes a vast repository of hidden information, encompassing personal files, academic research, and sensitive databases like email and online banking records. Conversely, the Dark Web represents a minute fraction of this hidden space, notorious for facilitating illegal activities such as trading illicit goods, sharing stolen data, and orchestrating cyberattacks. Operated through specialized networks and leveraging cryptocurrencies like Bitcoin for transactions, the Dark Web poses significant challenges for law enforcement due to its anonymity and encrypted nature. Specific hurdles include hidden payment pages and untraceable money transfers, which render it a haven for cybercriminals. The paper offers an overview of both the Deep and Dark Web, underscoring the critical role of proactive monitoring tools in mitigating associated threats. These intelligent solutions leverage technologies such as data analytics and machine learning to preemptively detect and halt potential dangers, offering early threat detection and prediction capabilities. Moreover, they aid law enforcement by providing crucial evidence against cybercriminals and safeguarding private information. Recognizing the importance of understanding and combating cybercrime, collaborative efforts among cybersecurity experts, law enforcement agencies, and technology innovators are advocated to create a safer online environment for all stakeholders.

ISBN

[9783031700170]

ISSN

2367-3370

Publisher

Springer Nature Switzerland

Volume

1088 LNNS

First Page

372

Last Page

380

Disciplines

Computer Sciences

Keywords

Anonymity, Cybersecurity, Dark Web, Deep Web, Hidden Web, Onion Routing, Proactive Monitoring Solutions, Tor Network

Scopus ID

85203581633

Indexed in Scopus

yes

Open Access

no

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