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Perfect Digital Crime

Computer forensics discussion. Please ensure that your post is not better suited to one of the forums below (if it is, please post it there instead!)
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Perfect Digital Crime

Post Posted: Wed Mar 28, 2018 11:48 am

As a training excercise I got a task to solve: A suspect planning to commit crime builds in advance a perfect and hardened alibi based on all aspects of live. He does

#1 Doppelganger engagement
#2 Perfect digital selflogging for selfdefense
#3 Perfect Pre- and PostCrime Alibi 12 months each
#4 Perfect Normality Interspersal (Looks Like Normal LLN)

The question is how as LEO to find an Indicator of Illusion IoI? Where, how and why such IoIs are unavoidable? In short the Perfect Digital Crime PDC.

Two things to consider: The suspect plays fully in public and social live with all aspects, no hidding but actively building an illusion.

Where are the areas the plan cannot work or will for sure fail?

DFA! You can talk to me.  

RolfGutmann
Senior Member
 
 
  

Re: Perfect Digital Crime

Post Posted: Wed Mar 28, 2018 12:54 pm

- RolfGutmann
As a training excercise I got a task to solve: A suspect planning to commit crime builds in advance a perfect and hardened alibi based on all aspects of live. He does

#1 Doppelganger engagement
#2 Perfect digital selflogging for selfdefense
#3 Perfect Pre- and PostCrime Alibi 12 months each
#4 Perfect Normality Interspersal (Looks Like Normal LLN)

The question is how as LEO to find an Indicator of Illusion IoI? Where, how and why such IoIs are unavoidable? In short the Perfect Digital Crime PDC.

Two things to consider: The suspect plays fully in public and social live with all aspects, no hidding but actively building an illusion.

Where are the areas the plan cannot work or will for sure fail?

DFA! You can talk to me.


As per your statement above... you have just admitted to your attempt (inchoate) to commit a perfect digital crime by identifying steps to making innocent-looking (outward appearance) activity to hide a crime thus revealing your mens rea (mindset) and actus reus (physical activity). Thank you for that and the UK National Crime Agency (NCA) will be in-touch you shortly.
_________________
Institute for Digital Forensics (IDF) - www.linkedin.com/groups/2436720
Mobile Telephone Examination Board (MTEB) - www.linkedin.com/groups/141739
Universal Network Investigations - www.linkedin.com/groups/13536130
Mobile Telephone Evidence & Forensics trewmte.blogspot.com 

trewmte
Senior Member
 
 
  

Re: Perfect Digital Crime

Post Posted: Wed Mar 28, 2018 1:48 pm

- RolfGutmann
#3 Perfect Pre- and PostCrime Alibi 12 months each


You seemingly forgot DCA (During Crime Alibi).

IoI (Indicator of Illusion) should be written as IOI as in most non-serif fonts IoI can easily be confused with lol (laughing out loud), particularly in sentences like

- RolfGutmann

Where, how and why such IoIs are unavoidable?

Here lols are unavoidable:
www.reddit.com/r/Jokes...d_luggage/


SYLA/SYSC

jaclaz
_________________
- In theory there is no difference between theory and practice, but in practice there is. - 

jaclaz
Senior Member
 
 
  

Re: Perfect Digital Crime

Post Posted: Wed Mar 28, 2018 3:53 pm

Biometrics fooling is not so easy and starts with false intial biometrics authentication. So any registration process in the society will fail I first thought. But how about twins, they have good chance to fool such a process. Twins are kind of comparable to genuine and doppelganger but has to be registered as twins before. The subject is all about CCI Criminal Composability Imagination first but practical barriers in real world.

Would e.g. a public surveillance cam really find-out the twins difference? If no database entry resolving exist not possible just storing. New Facial Personality Analysis (faception IL) would bring-out both twins suspect or none of both.

Voice is another layer which fails between genuine and doppelganger, as no relation between DNA face characteristics and voice band.

I first was wondering about the LLN aspect. How is normal defined, based on which indicators normal is defined in a range? More stupid can be an IoI and less stupid can hint to preparation.

Further more a very consistent communications scheme must be in-use. Otherwise the two human comparison fails. Normally human fails in one way or another. Preparation is one thing but humans react differently in certain situations (Unknowns).

It would be interesting to first list all authentication processes during a year and after compare which are difficult to bypass.

But a PDC is for sure possible, as I hold otherwise a Perfect Crime for not possible. The element of digital as a technical layer should be possible to harden.  

RolfGutmann
Senior Member
 
 
  

Re: Perfect Digital Crime

Post Posted: Wed Mar 28, 2018 10:32 pm

By taking an ordinary day lets assume that S takes a public transport for going to work. Instead of him goes the Double D and needs a valid ticket, e.g. mobile digital ticket. Payment based on an Mobile Payment App like Apple Pay requests FaceID by an iPhone X the related credit card would be validated by Passport or ID at the application process. Would the background check work if both S and D have almost similar address credentials (ordinary spell check failure)?

The first question: How do credit card companies separate twins and indicate them in their systems?
Could be a form of discimination to flag them internally and if they would know they could go against it.

Today is a climate of all is allowed and diversity is a wish. Lets assume they solved the first discrimination. After the way would be free for them to continue.

As I said before the trend of non-binary persons will open the anti-discrimination domain. Is digital ordinary existing (no hidding) in the anti-discrimination domain the area to search for IoIs?

One could say S&D are open eye hidding, nobody realizes a IoI, but I should.

Is shadow hidding and distraction with LLN a digital domain to search for new IoIs?  

RolfGutmann
Senior Member
 
 
  

Re: Perfect Digital Crime

Post Posted: Thu Mar 29, 2018 1:44 am

- RolfGutmann

The first question: How do credit card companies separate twins and indicate them in their systems?


They mark them as PET (Possible Evil Twin) setting the appropriate flag as PET1, PET2, etc., of course, but anyway credit card companies are not particularly interested in the identification of the one that presents the credit card to the cashier (or ATM, or payment system) as long as the card is valid, and there is credit, and no report of the card as lost or stolen exists, what they are after is more about card twins (that they call "clones") that about their bearers.

jaclaz
_________________
- In theory there is no difference between theory and practice, but in practice there is. - 

jaclaz
Senior Member
 
 
  

Re: Perfect Digital Crime

Post Posted: Thu Mar 29, 2018 5:40 pm

So the PET1 and PET2 are flagged in the EMV and SWIFT systems. Would actual selfie pay of MasterCard fail by PETS attempts? Obivously any authentication process will compare actual with DB reference.

The Initial Criminal False-in ICF is crucial. All starts if the inital validation process will be consistent.

Are there based Criminal Composability Imagination CCI undiscovered technigques to establish ICF? Normally over time we discover year-over-year that suspects find new ways in the area of ICF. Simply as they think day-and-night around this single problem and cross-think all possibilities. I call this the Prisoners Genius Approach PGA.

Does LEO think all the time in the area of ICF based on the PGA? No, simply because no free brain-time. But prisoners have exactly this ressource. They have one huge problem and its worth to solve it.

My post about the lack of CCI within LEO had no response. For the goal of our job in LEOs we have to FOCUS on ICFs.

My boss said: No more hunting, we have to build traps. Evidence Proof Traps EPTs.
Actually we run in-lab several new tiny EPTs to change the game. We want to be

Ahead Of Crime AOC.

For this I want to think about Indicators of Illusion IoIs.  

RolfGutmann
Senior Member
 
 

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