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adversarial search state-of-the-art #2547
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Real world $2.44 million fraud with Amazon reviews/votes, thnx @pimveldhuisen |
Most of these were quite useful for gaining some understanding on this topic, thanks @synctext and @pimveldhuisen. I am currently looking into It currently seems that lots of partial 'solutions' wrt adversarial search exist and have been researched, but most often they heavily depend on some form of centralisation or have another major drawback. |
Also, regarding an often-used WoT based system: |
@wordempire A lot of abuse, fraud and spam examples can be found in social media and e-commerce. So that is nice stuff to write about. but most often they heavily depend on some form of centralisation or have another major drawback. That is a perfect storyline! Anything more for self-organising systems or P2P? Stuff like, http://www.ece.umd.edu/~goergen/docs/sec-nwatch.pdf .. Web-of-trust mechanisms can be a minority part of your report, halve, or the majority. Whatever makes the most interesting story. A list of partial, flawed, and fantasy WoT solutions would be ideal. |
Fraud with search results with direct financial gain. |
lee2006understanding: develops a model that looks at the link between user behavior/awareness and pollution of a p2p network. |
yoshida2009controlling: shows that index poisoning is an effective way of dealing with copyright violations when looking at the Winny network for small sets of files. This approach has the potential to disrupt the network as a whole, which might or might not be desirable for an adversary. |
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OK, + add 4th or 5th section. start .tex in https://www.google.nl/search?q=ieeee+format format https://scholar.google.com/scholar?q=dht+poisoning the Tribler voting and spam prevention mechanism |
This was the user-study where the assumption that expert users can quickly assess whether something is spam is questioned: Lee, Uichin, et al. "Understanding Pollution Dynamics in P2P File Sharing." IPTPS. Vol. 6. 2006. |
first warmup task: understand and plot key daya from AllChannel content discovery and voting mechanism. Plot ideas:
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I would also like to propose a different issue title, as "adversarial search" is usually used in the context of e.g. game related A.I. things. How about "Spam-resilient search in decentralized systems" |
Problem can be split in two parts:
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Survey paper possible elements:
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ToDo:
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Draft version: |
Draft feedback:
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draft v2 |
Also @synctext , how would you like me to cite https://github.com/blockchain-lab/shared_vision_towards_programmable_economy/blob/master/tex/article.tex? |
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Given how many legitimate news organizations and people are routinely labelled 'troll' by their competitors (RT / AlJazeera / CNN / FOX are, even if they are biased on questions of russian/qatar/US-blue-team/US-red-team interest) - the question of 'why did this work as effectively as it did' has an underlying truth component of 'because what they were saying was just as true of a constructed narrative of social facts as the competing consensus was'. It's not the whole reason why they are successful but if we're thinking about search and mass media we should keep in mind that in addition to the mass media perception shifting going on from one player in the 'troll account' narrative, there is great (perhaps greater) mass media perception management going on from the other player as well. Some success by the other players may serve to balance out the bias of the network itself in the favour of the incumbents. To phrase in the context of, say, Kelong Cong's paper 3.3...the 'honest region' does not include either the blue or red team and everyone associated with it, both meatspace and bot, to the extent that shared, necessary illusions involved in group membership are held. |
@ichorid See this ticket of related work. Especially the 8000 fake Twitter accounts. |
@synctext thanks, I'll take this stuff into account. |
related #3615 |
Broader vision, beyond keyword search. An extensive technical analysis of the threat model in troubled regions. Aid workers are exposed to difficult challenges, see On Enforcing the Digital Immunity of a Large Humanitarian Organization. |
Status update after a few years:
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Keyword search within a self-organising system is a challenging unsolved problem.
Detecting and removing spam has proven to be extremely difficult. Creating a trustworthy search service, out of unreliable and possibly fraudulent resources is a challenge. A starting point is creating a web-of-trust or other feedback mechanism.
Existing work:
Web of trust for voting within Tribler:
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