Detecting and analyzing market manipulation on Bitcoin // Detecting and analyzing market manipulation on Bitcoin
ABG-129770
ADUM-63750 |
Thesis topic | |
2025-03-20 |
Université Côte d'Azur
Sophia Antipolis Cedex - France
Detecting and analyzing market manipulation on Bitcoin // Detecting and analyzing market manipulation on Bitcoin
- Computer science
Bitcoin, blockchain
Bitcoin, blockchain
Bitcoin, blockchain
Topic description
The subject is only described in English. B2/C1 level of English is mandatory to apply.
Price manipulation in stock markets is an important but difficult subject as trades are not public. Bitcoin [4][5] offers a public ledger of a $500B market and 14 years of history. It also attracted in the past years big and institutional investors. It is therefore a perfect model to explore price manipulations. However, all transactions on bitcoin are pseudo anonymous, hierarchical deterministic wallets foster using a different address per transaction, and there is no known known way to reconstruct all transactions from a single entity trying to manipulate the price.
The objectives of this Ph.D. thesis are the following.
1) Explore how to reconstruct the transaction history of entities by associating stream of transactions for different addresses. We propose to explore multiple techniques such as exploiting graph properties of the transaction graph [1][2] and using unsupervised machine learning to cluster addresses belonging to a single entity.
2) Explore existing market manipulation techniques [3] and seek for their presence on bitcoin.
3) Conceive a surveillance system (possibly based on machine learning) to detect early any attempt to market manipulation.
Note on the summary: A Ph.D. thesis is a long journey built between the student and the supervisor. During this journey, the initial plan is never fully followed and serendipity is the norm. The presented summary gives the theme and a direction, not a detailed work plan that would be defined and adapted during the Ph.D. thesis.
The subject is only described in English. B2/C1 level of English is mandatory to apply.
Price manipulation in stock markets is an important but difficult subject as trades are not public. Bitcoin [4][5] offers a public ledger of a $500B market and 14 years of history. It also attracted in the past years big and institutional investors. It is therefore a perfect model to explore price manipulations. However, all transactions on bitcoin are pseudo anonymous, hierarchical deterministic wallets foster using a different address per transaction, and there is no known known way to reconstruct all transactions from a single entity trying to manipulate the price.
The objectives of this Ph.D. thesis are the following.
1) Explore how to reconstruct the transaction history of entities by associating stream of transactions for different addresses. We propose to explore multiple techniques such as exploiting graph properties of the transaction graph [1][2] and using unsupervised machine learning to cluster addresses belonging to a single entity.
2) Explore existing market manipulation techniques [3] and seek for their presence on bitcoin.
3) Conceive a surveillance system (possibly based on machine learning) to detect early any attempt to market manipulation.
Note on the summary: A Ph.D. thesis is a long journey built between the student and the supervisor. During this journey, the initial plan is never fully followed and serendipity is the norm. The presented summary gives the theme and a direction, not a detailed work plan that would be defined and adapted during the Ph.D. thesis.
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The subject is only described in English. B2/C1 level of English is mandatory to apply.
Price manipulation in stock markets is an important but difficult subject as trades are not public. Bitcoin [4][5] offers a public ledger of a $500B market and 14 years of history. It also attracted in the past years big and institutional investors. It is therefore a perfect model to explore price manipulations. However, all transactions on bitcoin are pseudo anonymous, hierarchical deterministic wallets foster using a different address per transaction, and there is no known known way to reconstruct all transactions from a single entity trying to manipulate the price.
The objectives of this Ph.D. thesis are the following.
1) Explore how to reconstruct the transaction history of entities by associating stream of transactions for different addresses. We propose to explore multiple techniques such as exploiting graph properties of the transaction graph [1][2] and using unsupervised machine learning to cluster addresses belonging to a single entity.
2) Explore existing market manipulation techniques [3] and seek for their presence on bitcoin.
3) Conceive a surveillance system (possibly based on machine learning) to detect early any attempt to market manipulation.
Note on the summary: A Ph.D. thesis is a long journey built between the student and the supervisor. During this journey, the initial plan is never fully followed and serendipity is the norm. The presented summary gives the theme and a direction, not a detailed work plan that would be defined and adapted during the Ph.D. thesis.
The subject is only described in English. B2/C1 level of English is mandatory to apply.
Price manipulation in stock markets is an important but difficult subject as trades are not public. Bitcoin [4][5] offers a public ledger of a $500B market and 14 years of history. It also attracted in the past years big and institutional investors. It is therefore a perfect model to explore price manipulations. However, all transactions on bitcoin are pseudo anonymous, hierarchical deterministic wallets foster using a different address per transaction, and there is no known known way to reconstruct all transactions from a single entity trying to manipulate the price.
The objectives of this Ph.D. thesis are the following.
1) Explore how to reconstruct the transaction history of entities by associating stream of transactions for different addresses. We propose to explore multiple techniques such as exploiting graph properties of the transaction graph [1][2] and using unsupervised machine learning to cluster addresses belonging to a single entity.
2) Explore existing market manipulation techniques [3] and seek for their presence on bitcoin.
3) Conceive a surveillance system (possibly based on machine learning) to detect early any attempt to market manipulation.
Note on the summary: A Ph.D. thesis is a long journey built between the student and the supervisor. During this journey, the initial plan is never fully followed and serendipity is the norm. The presented summary gives the theme and a direction, not a detailed work plan that would be defined and adapted during the Ph.D. thesis.
------------------------------------------------------------------------------------------------------------------------------------------------------------------------
------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Début de la thèse : 01/10/2025
Price manipulation in stock markets is an important but difficult subject as trades are not public. Bitcoin [4][5] offers a public ledger of a $500B market and 14 years of history. It also attracted in the past years big and institutional investors. It is therefore a perfect model to explore price manipulations. However, all transactions on bitcoin are pseudo anonymous, hierarchical deterministic wallets foster using a different address per transaction, and there is no known known way to reconstruct all transactions from a single entity trying to manipulate the price.
The objectives of this Ph.D. thesis are the following.
1) Explore how to reconstruct the transaction history of entities by associating stream of transactions for different addresses. We propose to explore multiple techniques such as exploiting graph properties of the transaction graph [1][2] and using unsupervised machine learning to cluster addresses belonging to a single entity.
2) Explore existing market manipulation techniques [3] and seek for their presence on bitcoin.
3) Conceive a surveillance system (possibly based on machine learning) to detect early any attempt to market manipulation.
Note on the summary: A Ph.D. thesis is a long journey built between the student and the supervisor. During this journey, the initial plan is never fully followed and serendipity is the norm. The presented summary gives the theme and a direction, not a detailed work plan that would be defined and adapted during the Ph.D. thesis.
The subject is only described in English. B2/C1 level of English is mandatory to apply.
Price manipulation in stock markets is an important but difficult subject as trades are not public. Bitcoin [4][5] offers a public ledger of a $500B market and 14 years of history. It also attracted in the past years big and institutional investors. It is therefore a perfect model to explore price manipulations. However, all transactions on bitcoin are pseudo anonymous, hierarchical deterministic wallets foster using a different address per transaction, and there is no known known way to reconstruct all transactions from a single entity trying to manipulate the price.
The objectives of this Ph.D. thesis are the following.
1) Explore how to reconstruct the transaction history of entities by associating stream of transactions for different addresses. We propose to explore multiple techniques such as exploiting graph properties of the transaction graph [1][2] and using unsupervised machine learning to cluster addresses belonging to a single entity.
2) Explore existing market manipulation techniques [3] and seek for their presence on bitcoin.
3) Conceive a surveillance system (possibly based on machine learning) to detect early any attempt to market manipulation.
Note on the summary: A Ph.D. thesis is a long journey built between the student and the supervisor. During this journey, the initial plan is never fully followed and serendipity is the norm. The presented summary gives the theme and a direction, not a detailed work plan that would be defined and adapted during the Ph.D. thesis.
------------------------------------------------------------------------------------------------------------------------------------------------------------------------
------------------------------------------------------------------------------------------------------------------------------------------------------------------------
The subject is only described in English. B2/C1 level of English is mandatory to apply.
Price manipulation in stock markets is an important but difficult subject as trades are not public. Bitcoin [4][5] offers a public ledger of a $500B market and 14 years of history. It also attracted in the past years big and institutional investors. It is therefore a perfect model to explore price manipulations. However, all transactions on bitcoin are pseudo anonymous, hierarchical deterministic wallets foster using a different address per transaction, and there is no known known way to reconstruct all transactions from a single entity trying to manipulate the price.
The objectives of this Ph.D. thesis are the following.
1) Explore how to reconstruct the transaction history of entities by associating stream of transactions for different addresses. We propose to explore multiple techniques such as exploiting graph properties of the transaction graph [1][2] and using unsupervised machine learning to cluster addresses belonging to a single entity.
2) Explore existing market manipulation techniques [3] and seek for their presence on bitcoin.
3) Conceive a surveillance system (possibly based on machine learning) to detect early any attempt to market manipulation.
Note on the summary: A Ph.D. thesis is a long journey built between the student and the supervisor. During this journey, the initial plan is never fully followed and serendipity is the norm. The presented summary gives the theme and a direction, not a detailed work plan that would be defined and adapted during the Ph.D. thesis.
The subject is only described in English. B2/C1 level of English is mandatory to apply.
Price manipulation in stock markets is an important but difficult subject as trades are not public. Bitcoin [4][5] offers a public ledger of a $500B market and 14 years of history. It also attracted in the past years big and institutional investors. It is therefore a perfect model to explore price manipulations. However, all transactions on bitcoin are pseudo anonymous, hierarchical deterministic wallets foster using a different address per transaction, and there is no known known way to reconstruct all transactions from a single entity trying to manipulate the price.
The objectives of this Ph.D. thesis are the following.
1) Explore how to reconstruct the transaction history of entities by associating stream of transactions for different addresses. We propose to explore multiple techniques such as exploiting graph properties of the transaction graph [1][2] and using unsupervised machine learning to cluster addresses belonging to a single entity.
2) Explore existing market manipulation techniques [3] and seek for their presence on bitcoin.
3) Conceive a surveillance system (possibly based on machine learning) to detect early any attempt to market manipulation.
Note on the summary: A Ph.D. thesis is a long journey built between the student and the supervisor. During this journey, the initial plan is never fully followed and serendipity is the norm. The presented summary gives the theme and a direction, not a detailed work plan that would be defined and adapted during the Ph.D. thesis.
------------------------------------------------------------------------------------------------------------------------------------------------------------------------
------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Début de la thèse : 01/10/2025
Funding category
Funding further details
Contrat doctoral EDSTIC-UCA ou EUR-DS4H
Presentation of host institution and host laboratory
Université Côte d'Azur
Institution awarding doctoral degree
Université Côte d'Azur
Graduate school
84 STIC - Sciences et Technologies de l'Information et de la Communication
Candidate's profile
The profile is only described in English. B2/C1 level of English is mandatory to apply.
The candidate must hold a Master or equivalent degree when starting the PhD.
The candidate required skills are:
- C1 level in English (possibly B2 close to reach C1)
- Excellent programming and systems skills. We will work in a Linux environment with python and with its data science libraries (numpy, pandas, seaborn, scikit-learn, statmodels). We also use Git. If the candidate is not fluent in Python, they must be *fluent* in another language and able to learn Python fast.
- Excellent communication skills. An important part of the Ph.D. is to communicate on the results. The candidate must be ready to write high quality papers and give stunning talks. These skills will be nurtured during the Ph.D. thesis.
- Curious, highly motivated, hard worker, autonomous, perfectionist. A good sign you have a profile to make an excellent Ph.D. thesis is when you cannot stand to do not understand something and can work night and day to get it (or make your stuff work).
Before deciding to make a Ph.D. thesis, you must read references in this page to be sure you made the right decision
http://www-sop.inria.fr/members/Arnaud.Legout/phdstudents.html
If you apply, I expect that you will directly get in touch with me very early in the process (arnaud.legout@inria.fr) to discuss if you are a good fit for the subject and I am a good fit as a supervisor. Discussing early with a potential supervisor about the subject and the supervision style (even if you are not sure to apply) is a sign of maturity and will be highly appreciated.
The profile is only described in English. B2/C1 level of English is mandatory to apply.
The candidate must hold a Master or equivalent degree when starting the PhD.
The candidate required skills are:
- C1 level in English (possibly B2 close to reach C1)
- Excellent programming and systems skills. We will work in a Linux environment with python and with its data science libraries (numpy, pandas, seaborn, scikit-learn, statmodels). We also use Git. If the candidate is not fluent in Python, they must be *fluent* in another language and able to learn Python fast.
- Excellent communication skills. An important part of the Ph.D. is to communicate on the results. The candidate must be ready to write high quality papers and give stunning talks. These skills will be nurtured during the Ph.D. thesis.
- Curious, highly motivated, hard worker, autonomous, perfectionist. A good sign you have a profile to make an excellent Ph.D. thesis is when you cannot stand to do not understand something and can work night and day to get it (or make your stuff work).
Before deciding to make a Ph.D. thesis, you must read references in this page to be sure you made the right decision
http://www-sop.inria.fr/members/Arnaud.Legout/phdstudents.html
If you apply, I expect that you will directly get in touch with me very early in the process (arnaud.legout@inria.fr) to discuss if you are a good fit for the subject and I am a good fit as a supervisor. Discussing early with a potential supervisor about the subject and the supervision style (even if you are not sure to apply) is a sign of maturity and will be highly appreciated.
The profile is only described in English. B2/C1 level of English is mandatory to apply. The candidate must hold a Master or equivalent degree when starting the PhD. The candidate required skills are: - C1 level in English (possibly B2 close to reach C1) - Excellent programming and systems skills. We will work in a Linux environment with python and with its data science libraries (numpy, pandas, seaborn, scikit-learn, statmodels). We also use Git. If the candidate is not fluent in Python, they must be *fluent* in another language and able to learn Python fast. - Excellent communication skills. An important part of the Ph.D. is to communicate on the results. The candidate must be ready to write high quality papers and give stunning talks. These skills will be nurtured during the Ph.D. thesis. - Curious, highly motivated, hard worker, autonomous, perfectionist. A good sign you have a profile to make an excellent Ph.D. thesis is when you cannot stand to do not understand something and can work night and day to get it (or make your stuff work). Before deciding to make a Ph.D. thesis, you must read references in this page to be sure you made the right decision http://www-sop.inria.fr/members/Arnaud.Legout/phdstudents.html If you apply, I expect that you will directly get in touch with me very early in the process (arnaud.legout@inria.fr) to discuss if you are a good fit for the subject and I am a good fit as a supervisor. Discussing early with a potential supervisor about the subject and the supervision style (even if you are not sure to apply) is a sign of maturity and will be highly appreciated. The profile is only described in English. B2/C1 level of English is mandatory to apply. The candidate must hold a Master or equivalent degree when starting the PhD. The candidate required skills are: - C1 level in English (possibly B2 close to reach C1) - Excellent programming and systems skills. We will work in a Linux environment with python and with its data science libraries (numpy, pandas, seaborn, scikit-learn, statmodels). We also use Git. If the candidate is not fluent in Python, they must be *fluent* in another language and able to learn Python fast. - Excellent communication skills. An important part of the Ph.D. is to communicate on the results. The candidate must be ready to write high quality papers and give stunning talks. These skills will be nurtured during the Ph.D. thesis. - Curious, highly motivated, hard worker, autonomous, perfectionist. A good sign you have a profile to make an excellent Ph.D. thesis is when you cannot stand to do not understand something and can work night and day to get it (or make your stuff work). Before deciding to make a Ph.D. thesis, you must read references in this page to be sure you made the right decision http://www-sop.inria.fr/members/Arnaud.Legout/phdstudents.html If you apply, I expect that you will directly get in touch with me very early in the process (arnaud.legout@inria.fr) to discuss if you are a good fit for the subject and I am a good fit as a supervisor. Discussing early with a potential supervisor about the subject and the supervision style (even if you are not sure to apply) is a sign of maturity and will be highly appreciated.
The profile is only described in English. B2/C1 level of English is mandatory to apply. The candidate must hold a Master or equivalent degree when starting the PhD. The candidate required skills are: - C1 level in English (possibly B2 close to reach C1) - Excellent programming and systems skills. We will work in a Linux environment with python and with its data science libraries (numpy, pandas, seaborn, scikit-learn, statmodels). We also use Git. If the candidate is not fluent in Python, they must be *fluent* in another language and able to learn Python fast. - Excellent communication skills. An important part of the Ph.D. is to communicate on the results. The candidate must be ready to write high quality papers and give stunning talks. These skills will be nurtured during the Ph.D. thesis. - Curious, highly motivated, hard worker, autonomous, perfectionist. A good sign you have a profile to make an excellent Ph.D. thesis is when you cannot stand to do not understand something and can work night and day to get it (or make your stuff work). Before deciding to make a Ph.D. thesis, you must read references in this page to be sure you made the right decision http://www-sop.inria.fr/members/Arnaud.Legout/phdstudents.html If you apply, I expect that you will directly get in touch with me very early in the process (arnaud.legout@inria.fr) to discuss if you are a good fit for the subject and I am a good fit as a supervisor. Discussing early with a potential supervisor about the subject and the supervision style (even if you are not sure to apply) is a sign of maturity and will be highly appreciated. The profile is only described in English. B2/C1 level of English is mandatory to apply. The candidate must hold a Master or equivalent degree when starting the PhD. The candidate required skills are: - C1 level in English (possibly B2 close to reach C1) - Excellent programming and systems skills. We will work in a Linux environment with python and with its data science libraries (numpy, pandas, seaborn, scikit-learn, statmodels). We also use Git. If the candidate is not fluent in Python, they must be *fluent* in another language and able to learn Python fast. - Excellent communication skills. An important part of the Ph.D. is to communicate on the results. The candidate must be ready to write high quality papers and give stunning talks. These skills will be nurtured during the Ph.D. thesis. - Curious, highly motivated, hard worker, autonomous, perfectionist. A good sign you have a profile to make an excellent Ph.D. thesis is when you cannot stand to do not understand something and can work night and day to get it (or make your stuff work). Before deciding to make a Ph.D. thesis, you must read references in this page to be sure you made the right decision http://www-sop.inria.fr/members/Arnaud.Legout/phdstudents.html If you apply, I expect that you will directly get in touch with me very early in the process (arnaud.legout@inria.fr) to discuss if you are a good fit for the subject and I am a good fit as a supervisor. Discussing early with a potential supervisor about the subject and the supervision style (even if you are not sure to apply) is a sign of maturity and will be highly appreciated.
2025-05-05
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