Law enforcement agencies have faced a tough time in dealing with cybercrime on the dark web.
Over the past couple of years, the dark web has become a haven for criminals.
These criminals range from drug dealers, vendors of stolen data and hackers who mainly target financial institutions.
The dark web enables them to remain anonymous, thus concealing their non-pseudonymous identities from law enforcement agencies.
However, as tough as it for them, law enforcement has remained adamant in trying to arrest crime perpetrators on the dark web with some success.
European and American countries have seen the heaviest effects of criminal dealings in the dark web. Law enforcement agencies in these countries have also vowed not to relent in their efforts to curb the vices.
Here are a few techniques that are being used by law enforcement agencies to identify and arrest dark web criminals.
Data Mining and Machine Learning
Data mining is a computing practice that discovers patterns in large sets of data. Machine learning involves settings up intelligent computer systems that can react accordingly in different situations.
Data mining is enabled by machine learning; the patterns discovered in data mining are used to make predictions within the scope where that data was mined through machine learning. This practice is deployed both on the surface web and dark web to collect data and analyze it.
For Instance, law enforcement officers could collect a set of data that has millions of IP addresses. The intelligent machines could pick out each IP address used to make a post on various platforms with content related to the dark web. The intelligent machines can also pick out which posts suggest an engagement with illicit activities on the dark web.
This technique has does not necessarily reveal the identities of dark web criminals, but it gives law enforcement officers insights into current trends in the dark web. Large volumes of data are involved and they give the officers patterns which could give them a base from which to start their investigation.
For example, from the analogy used above, an officer could realize that a large number of IP addresses picked as having a possible interaction with the dark web are from a particular location. That’s a pattern from which law enforcement officers could start associated investigations.
Real Life Observation
This is usually done when the police have narrowed down a possible suspect, but they can’t arrest them since they have nothing on them. So, why would the police conduct a physical observation of a suspect whose possible crimes are done online?
You’ll be surprised to learn that our pattern of online engagement has a strong correspondence with what we do in real life. For instance, the time we get online is determined by our offline schedule, or what we have been doing on that given day.
Once the police have narrowed down a possible suspect, they will track their real-life activities very closely. A good reference is Ross Ulbricht, founder of Silk Road. He has since been arrested and sentenced to life in prison.
Silk Road was also taken down. Ross was tracked by the police in real life, and among the reasons for his capture was the coinciding times of him getting into a coffee shop to access Wi-Fi and that of the administrator of Silk Road coming online, thus allowing law enforcement to verifiably connect the dots.
A large part of a crime that takes place on the dark web involves the drug trade. Most of the drugs bought are delivered by mail or parcel delivery companies.
Law enforcement agencies work closely with these companies to monitor the parcels that pass through them. Any parcel that is found to be suspicious is carefully inspected.
If any contraband is found, the officers will normally allow the delivery to continue so that they can arrest the receiver one the parcel is in their hands.
This technique normally leads them to the buyers and not the sellers, who are bigger targets for the police. At times, the parcels will have a return address that the police could use to try and track the source of the parcel.
This technique does not yield a lot of results for the law enforcement agencies, though, as the criminals always have ingenious ways of disguising the drug packages. The agencies are not willing to leave any area to chance, so they still keep a keen eye on parcels.
This is law enforcement’s most effective and favorite method of engaging the dark web. The officers join the dark web and pose as buyers or sellers and try to communicate with the criminals.
These communications give them clues on how to move ahead and possibly get the identity of these criminals. This also helps them when they have narrowed down a suspect.
For instance, in the same case of Ross, once the police resolved to arrest him, one undercover officer on the dark web continued to engage him in conversation so that he wouldn’t move while the other officers were closing in on him.
The officers also wished to get the conversation history so that they could prove beyond reasonable doubt that they had the correct person in custody.
Other undercover operations involve tracking payments, though this has been made incredibly difficult due to the use of Bitcoin.
Bitcoin payments are extremely difficult to trace, and digital wallets are not connected to any personal details. The police normally concentrate on platforms where Bitcoin is exchanged for cash.
Financial institutions that carry out these processes work with relevant agencies to provide them with information on any transaction that might seem suspicious under AML and KYC laws and policies.
The dark web offers high levels of anonymity that makes it exceptionally difficult for law enforcement agencies to track the persons involved.
The highlighted techniques are but the icing on the cake regarding the lengths law enforcement agencies go to so that they can uncover the identities of various criminal characters on the dark web.
The agencies prefer to keep most of their processes and information secret, understandably so as they wouldn’t be effective if everyone knew what they were doing.
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