Artificial intelligence shows promise for monitoring dark web activity but also raises privacy concerns. Researchers have developed AI crawlers that can effectively gather information from dark web forums in multiple languages. An Australian police officer aims to create an AI crawler to detect illegal activity and alert authorities, with the goals of integrating it with a database and allowing it to automatically group websites. However, privacy advocates argue this could undermine privacy and political freedom, as the dark web also enables whistleblowing and circumventing censorship. There are opportunities for AI to help address crime, but the line between surveillance and overreach requires careful consideration.

1. Artificial Intelligence On The Dark Web
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AI is seen to be the ideal tool for fixing the crime-riddled dark web. Unfortunately, the issue of
online privacy presents itself dauntingly.
The internet has registered exceptional growth over the years. This trend has given rise to
the dark web, a somewhat troublemaking facet of the internet that has supported the
proliferation of various social ills.
Nonetheless, the entire dark web should not be criminalized. While there are particular
positive attributes of the hidden web , the dark web has been notorious for harboring
cybercrime, extreme behavior and the drug trade.
This issue has prompted law enforcement agencies to develop innovative strategies to arrest
dark web masterminds that have been blamed for the widespread erosion of societies' moral
fiber.
This aspect, therefore, has presented an urgent need for the application of mechanisms used
to monitor and analyze dark web activity by observing trends characterizing darknet forums.
Quite unfortunately, it has been evident that the employment of conventional web crawling
methods has been ineffective for collecting dark web content.
It is this need that has prompted experts to employ artificial intelligence (AI) techniques in
monitoring dark web activity.
Various scientific research papers have sought to explicate the practicality of applying AI as
the ultimate dark web cop in combating online crime.
Fundamentally, the Tor network has been extensively studied with the intention of manually
labeling crawled sites that have been grouped categorically. Such labelling has been closely
associated with the existence of automated crawls.
This perspective has been known to be efficient in creating definite taxonomies that advise
on issues surrounding dark web activity.
However, some limitations have been established within the context of specialized law
enforcement. Experts have endeavored to monitor illegal activity on the dark web by
concentrating on particular forms of crime, such as fraud.
Hitherto, a significant gap exists between taxonomies that explicate dark web activity and
those able to provide detailed information on dark web crime.

2. This challenge has formed the basis of various research questions that seek to streamline
law enforcement within the confines of the hidden web.
AI and Dark Web Monitoring
Artificial intelligence has swept the doyens of computer technology off their feet. But what
exactly is the significance of artificial intelligence in dark web activity?
This question is, undoubtedly, critical and can be approached by understanding the research
milestones made concerning the involvement of AI in controlling the hidden web.
A 2010 scientific paper, A Focused Crawler for Dark Web Forums by Abbasi et al., provided
a proposition for the creation of a crawling mechanism that would work to collect content from
darknet forums.
The outcomes of the study were very interesting. The researchers were successful in
creating a specialized crawler for gathering information from dark web forums.
They employed an accessibility technique that registered monumental levels of success that
were recorded at over 90 percent.
The crawler utilized a mechanism that was not tied down by language restrictions. This
ranged from URL tokens to anchor text. According to the researchers, this aspect was
fundamental in ensuring the gathering of content across the multilingual divide.
The crawler also used particular strategies that would allow it to sustain incremental crawling.
Furthermore, the incremental crawling method was combined with a recall improvement
technique that would typically re-spider uncollected content.
The paper's discussion intimated that the study managed to obtain latest information from
109 dark web forums. This success occurred despite the reality of multiple languages spoken
in the forum.
Specifically, the forums were grouped into three—American, Middle Eastern and Latin.
Moreover, the researchers provided a case study that vindicated the practicality of the
collections in analyzing dark web content.
The case study centered on the particular discussion topics that rule the dark web, and the
associated interaction patterns that characterize the respective forums.
In conclusion, the researchers affirmed the premise that a forum crawling system would go a
long way in providing an entry into the world of darknet forums with the intention of

3. understanding these covert groups.
In the same sphere, a member of the Australian Federal Police (AFP) intends to invent a
crawler that operates on artificial intelligence.
Janis Dalins, the AFP officer, believes that the crawler would be instrumental in the
monitoring of dark web activity with the aim of detecting illegal action and alerting law
enforcement of the same.
The internet has registered exceptional growth over the years.
Dalins intimates that the crawler will contribute to a database maintained by police officers
who will monitor dark web activity regularly.
Currently, the dark web is mainly accessed through Tor, a highly encrypted network that
promises its users the benefit of anonymity as they engage in various online activities.
According to Dalins, this aspect has fueled the proliferation of criminal elements on the dark
web.
The dark web supports the trade of goods ranging from drugs to stolen records and
identities.
To solve this problem, Dalins merged efforts with his Ph.D supervisor to provide the ultimate
solution to law enforcement issues within the dark web context. To Dark Net Market , their
work was published in the Digital Investigation journal.
According to the paper, the researchers operated under permission from Australian
authorities. This detail concerned their intentions to carry out an open crawl of Tor for the
sole purpose of the study.
This provision also included the go-ahead to analyze illicit content like child exploitation
material, which is a rampant form of crime on the dark web.
Just like the previously mentioned scientific paper, Dalins' work produced intriguing
outcomes. darknet markets managed to collect several hundred thousands of pages from
more than 7,000 dark web domains.
This allowed the team to amass information ranging from a broad sphere that heavily leaned
on illegal online activity.
The study applied a Tor-use Motivation Model (TMM) to test its hypotheses. TMM is a
classification technique that has been specially tailored for police work.
According to https://en.wikipedia.org/wiki/Evolution_(marketplace) , the manual labeling of

4. thousands of unique Tor pages was undertaken, and this unraveled mysteries surrounding
the possible applications of AI in curbing dark web crime. The technique exposed networks of
money laundering and illegal trade.
The study also discredited the traditional means used by law enforcement in monitoring illicit
dark web activity. Concerning this, conventional models proved to be vague within the terms
of law enforcement.
Dalins is hopeful that the project will advance as planned. Funding for the second phase will
enable the integration of his database with an AI program.
The AI tool will then stalk the dark web and group websites automatically. It would have the
ability to alert the AFP whenever it encounters any illegal activity on the dark web.
The Flip Side
Following the above analysis, it would be easy to regard AI as a welcome idea for restoring
stability on the dark web.
While this premise might be correct, the application of police-supported AI crawlers on dark
web activity may rub many people the wrong way. Notably, this development raises serious
privacy concerns.
Privacy advocates would easily dub it as a witch hunt for people out to exercise their
freedoms of thought and speech.

5. While criminals have primarily misused the dark web, a significant portion of the hidden web
has been instrumental in circumventing government-funded media censorship and being a
space where whistleblowers can expose corruption anonymously. This is just but one
positive attribute borne in the dark web that is often undermined.
Allowing the police to advance their surveillance methods on the dark web will heighten
issues surrounding political oppression. In the subject of child exploitation, such a move may
be justified.
However, see this and security of individuals using the dark web for legitimate reasons will
become primarily compromised.
Darknet Market Guides has always been important for people to have complete control over
their online privacy, with an emphasis on the prevention of government spying on their online
lives—privacy is a human right.
Conclusion
The application of AI on monitoring dark web activity has both academic and scientific value.
The reflection of collected data on security informatics would go a long way to combat dark
web crime.
However, there are serious privacy concerns attached to the application of AI in checking
dark web sites.
As a bona fide citizenry, it would be prudent for people to draw the line between constructive
dark web surveillance and unwarranted government interference on activities of the great
hidden web.”