anirban · basu - publications

Practical confidential data cleaning using trusted execution environments

2025-08-04T00:00:00+00:00

Anirban Basu, Masayuki Yoshino and Minako Toba

Abstract: Data cleaning, also known as data cleansing or data scrubbing, is the process of identifying and correcting errors, inconsistencies, and inaccuracies in datasets. It is a crucial step in statistical analysis and machine learning as the quality of the input data directly affects the reliability and validity of the results obtained from any analysis. Data cleaning, when outsourced, poses privacy and confidentiality challenges. To address these, there has been recent research focus on privacy and confidentiality preserving data cleaning. In this paper, we propose a practical qualitative data cleaning system that preserves the privacy and confidentiality of the data utilising trusted execution environments. We have implemented our system in Python and deployed it using the Gramine library operating system on Intel Software Guard Extensions (SGX) hardware.

address	Chania, Greece
booktitle	Proceedings of the IEEE International Conference on Cyber Security and Resilience (CSR)
day	04
doi	10.1109/CSR64739.2025.11130151
keywords	data-privacy, statistical-analysis, operating-systems, machine-learning, cleaning, software, security, reliability, resilience, python, trusted-execution-environments, data-cleaning, security, privacy, confidentiality
month	08
pages	342-349

Cite this publication, using BibTeX

@inproceedings{basu2025practical,
  abstract = {Data cleaning, also known as data cleansing or data scrubbing, is the process of identifying and correcting errors, inconsistencies, and inaccuracies in datasets. It is a crucial step in statistical analysis and machine learning as the quality of the input data directly affects the reliability and validity of the results obtained from any analysis. Data cleaning, when outsourced, poses privacy and confidentiality challenges. To address these, there has been recent research focus on privacy and confidentiality preserving data cleaning. In this paper, we propose a practical qualitative data cleaning system that preserves the privacy and confidentiality of the data utilising trusted execution environments. We have implemented our system in Python and deployed it using the Gramine library operating system on Intel Software Guard Extensions (SGX) hardware.},
  address = {Chania, Greece},
  author = {Basu, Anirban and Yoshino, Masayuki and Toba, Minako},
  booktitle = {Proceedings of the IEEE International Conference on Cyber Security and Resilience (CSR)},
  day = {4},
  doi = {10.1109/CSR64739.2025.11130151},
  keywords = {Data privacy;Statistical analysis;Operating systems;Machine learning;Cleaning;Software;Security;Reliability;Resilience;Python;trusted execution environments;data cleaning;security;privacy;confidentiality},
  month = {August},
  pages = {342-349},
  title = {Practical confidential data cleaning using trusted execution environments},
  year = {2025},
}

SCATMAN: A Framework for Enhancing Trustworthiness in Digital Supply Chains

2023-11-01T00:00:00+00:00

Michael Eckel, Anirban Basu, Satoshi Kai, Hevais Simo Fhom, Sinisa Dukanovic, Henk Birkholz, Shingo Hane and Matthias Lieske

Abstract: In this paper, we present a framework and an architecture that aim to enable and manage trust in supply chains. Our architecture addresses the authenticity and integrity of devices and processes within heterogeneous system landscapes. We identify and discuss the current challenges in digital supply chains and lay out security, privacy, and interoperability requirements that must be met for successful implementation. We hypothesize that the overall perception of trust in a supply chain depends on the trustworthiness of all digital systems involved, including hardware, software, and information flow. Our proposed architecture helps enhance trustworthiness based on verifiable, indisputable, and believable digital evidence for devices and processes in supply chains, including the entire hardware and software lifecycles. We actively advocate for a mixed landscape of centralized and decentralized solutions for the storage of evidence and trust information. This can include traditional centralized databases and distributed ledger technologies. We discuss the auditability and accountability of digital evidence using trust-enabling technologies, and present a preliminary proof-of-concept (PoC) implementation in a real-world application scenario.

address	Exeter, UK
booktitle	Proceedings of the IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)
doi	10.1109/TrustCom60117.2023.00110
keywords	privacy, distributed-ledger, digital-systems, supply-chains, distributed-databases, computer-architecture, software, trustworthiness, integrity, transparency, trusted-computing, confidential-computing, society-5-0, industrie-4-0, digital-twin, supply-chain-security, distributed-system-security, smart-factory, blockchain-technology
month	11
pages	750-761

Cite this publication, using BibTeX

@inproceedings{eckel2023scatman,
  abstract = {In this paper, we present a framework and an architecture that aim to enable and manage trust in supply chains. Our architecture addresses the authenticity and integrity of devices and processes within heterogeneous system landscapes. We identify and discuss the current challenges in digital supply chains and lay out security, privacy, and interoperability requirements that must be met for successful implementation. We hypothesize that the overall perception of trust in a supply chain depends on the trustworthiness of all digital systems involved, including hardware, software, and information flow. Our proposed architecture helps enhance trustworthiness based on verifiable, indisputable, and believable digital evidence for devices and processes in supply chains, including the entire hardware and software lifecycles. We actively advocate for a mixed landscape of centralized and decentralized solutions for the storage of evidence and trust information. This can include traditional centralized databases and distributed ledger technologies. We discuss the auditability and accountability of digital evidence using trust-enabling technologies, and present a preliminary proof-of-concept (PoC) implementation in a real-world application scenario.},
  address = {Exeter, UK},
  author = {Eckel, Michael and Basu, Anirban and Kai, Satoshi and Simo Fhom, Hevais and Dukanovic, Sinisa and Birkholz, Henk and Hane, Shingo and Lieske, Matthias },
  booktitle = {Proceedings of the IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)},
  doi = {10.1109/TrustCom60117.2023.00110},
  keywords = {Privacy;Distributed ledger;Digital systems;Supply chains;Distributed databases;Computer architecture;Software;trustworthiness;integrity;transparency;Trusted Computing;confidential computing;Society 5.0;Industrie 4.0;digital twin;supply chain security;distributed system security;smart factory;blockchain technology},
  month = {November},
  pages = {750-761},
  title = {SCATMAN: A Framework for Enhancing Trustworthiness in Digital Supply Chains},
  year = {2023},
}

Software and its perceived trustworthiness

2023-10-19T00:00:00+00:00

Anirban Basu and Satoshi Kai

Abstract: Trust is a pervasive and essential driver for sustainable interactions between social entities and the functioning of a society as a whole. Trust, from the decisional perspective, has been summarised as 'the act of choosing to put oneself into a situation of risk, where the outcomes are dependent on the actions of another' [18]. Trust is observed to be contextual, subjective, idiosyncratic and often only really understood from the perspective of an individual [8]. The term trust system, coined in [23], is 'where computational tools, humans and trust reasoning capabilities come together to accomplish something where trust is an enabling factor'. In software supply chains and value chains, adequate measures do not exit beyond attempts to enforce trust through cryptographic verification, in order to faciliate stakeholders to make trust deliberations about the entities in supply and value chains. In this position paper, we propose the blueprint of a framework for the assessment of perceived trustworthiness in software supply chains such that a trustor is empowered, as opposed to enforced, to make decisions based on their trust deliberations.

address	Amsterdam, Netherlands
booktitle	Proceedings of the IFIP WG 11.11 International Conference on Trust Management (IFIPTM)
day	19
doi	10.1007/978-3-031-76714-2_7
isbn	978-3-031-76714-2
keywords	trust, trustworthiness, perceived-trustworthiness, software-supply-chain, security
month	10
pages	105-120
publisher	Springer Nature, Switzerland

Cite this publication, using BibTeX

@inproceedings{basu2023perceivedtrustworthiness,
  abstract = {Trust is a pervasive and essential driver for sustainable interactions between social entities and the functioning of a society as a whole. Trust, from the decisional perspective, has been summarised as 'the act of choosing to put oneself into a situation of risk, where the outcomes are dependent on the actions of another' [18]. Trust is observed to be contextual, subjective, idiosyncratic and often only really understood from the perspective of an individual [8]. The term trust system, coined in [23], is 'where computational tools, humans and trust reasoning capabilities come together to accomplish something where trust is an enabling factor'. In software supply chains and value chains, adequate measures do not exit beyond attempts to enforce trust through cryptographic verification, in order to faciliate stakeholders to make trust deliberations about the entities in supply and value chains. In this position paper, we propose the blueprint of a framework for the assessment of perceived trustworthiness in software supply chains such that a trustor is empowered, as opposed to enforced, to make decisions based on their trust deliberations.},
  address = {Amsterdam, Netherlands},
  author = {Basu, Anirban and Kai, Satoshi},
  booktitle = {Proceedings of the IFIP WG 11.11 International Conference on Trust Management (IFIPTM)},
  day = {19},
  doi = {10.1007/978-3-031-76714-2_7},
  isbn = {978-3-031-76714-2},
  keywords = {trust;trustworthiness;perceived trustworthiness;software supply chain;security},
  month = {October},
  pages = {105-120},
  publisher = {Springer Nature, Switzerland},
  title = {Software and its perceived trustworthiness},
  year = {2023},
}

The ethical implications of using digital traces: studying explainability and trust during a pandemic

2021-11-29T00:00:00+00:00

Natasha Dwyer, Hector Miller-Bakewell, Tessa Darbyshire, Anirban Basu and Steve Marsh

Abstract: Digital technologies give researchers new opportunities to access the most personal thoughts of those who use them. The ethics and implications of using data from peoples' everyday interactions have recently become a mainstream topic of concern (Lucivero, 2020). In some contexts, such as governance, it can be argued that algorithmically-generated decisions are valued over individuals' and communities' expertise (Danaher, 2016). As with other projects described in this book, our work is being carried out during the COVID-19 pandemic. The crisis has highlighted the ethical complications that occur when vulnerable individuals requiring information are surveilled in a rapidly changing environment. Currently, worldwide legislative changes are determining how data-intensive technologies, including forms of data collection and surveillance, are used. Recent history indicates that once the initial threat has passed, legislation remains and becomes the 'new normal' (Lodders and Paterson, 2020). Organisations, including universities, are establishing mechanisms for collecting and managing stakeholder data, which will remain in place after the pandemic. The collected data will become part of the hidden curriculum, the subtle messages students receive about what an institution values, and the nature of the power relations inherent in its interactions (Kayama et al, 2015). In this chapter we outline and engage with the ethical practices involved in performing such data collection, with a particular focus on the use of chatbot transcripts. We particularly highlight the impact of crisis scenarios on 'information anxiety' (Blundell et al, 2014) in undergraduate students and evaluate the potential of chatbots as a tool to improve information literacy. Chatbots can be used to enable individuals to seek information ranging from functional to personal, including information that may be sensitive or personal in nature.

address	Bristol, UK
booktitle	Qualitative and Digital Research in Times of Crisis: Methods, Reflexivity, and Ethics
day	29
doi	10.51952/9781447363828.ch008
keywords	social-research-methods, qualitative-methods, creative-methods, disaster-and-crisis-management, research-practices, research-ethics, research-reflexivity, researcher-positionality, digital-research-methods, digital-data, digital-traces, data-ethics, data-privacy, data-protection, data-security, data-sharing, data-reuse
month	11
pages	129-142
publisher	Policy Press
url	Link

Cite this publication, using BibTeX

@incollection{dwyer2021ethical,
  abstract = {Digital technologies give researchers new opportunities to access the most personal thoughts of those who use them. The ethics and implications of using data from peoples' everyday interactions have recently become a mainstream topic of concern (Lucivero, 2020). In some contexts, such as governance, it can be argued that algorithmically-generated decisions are valued over individuals' and communities' expertise (Danaher, 2016). As with other projects described in this book, our work is being carried out during the COVID-19 pandemic. The crisis has highlighted the ethical complications that occur when vulnerable individuals requiring information are surveilled in a rapidly changing environment. Currently, worldwide legislative changes are determining how data-intensive technologies, including forms of data collection and surveillance, are used. Recent history indicates that once the initial threat has passed, legislation remains and becomes the 'new normal' (Lodders and Paterson, 2020). Organisations, including universities, are establishing mechanisms for collecting and managing stakeholder data, which will remain in place after the pandemic. The collected data will become part of the hidden curriculum, the subtle messages students receive about what an institution values, and the nature of the power relations inherent in its interactions (Kayama et al, 2015). In this chapter we outline and engage with the ethical practices involved in performing such data collection, with a particular focus on the use of chatbot transcripts. We particularly highlight the impact of crisis scenarios on 'information anxiety' (Blundell et al, 2014) in undergraduate students and evaluate the potential of chatbots as a tool to improve information literacy. Chatbots can be used to enable individuals to seek information ranging from functional to personal, including information that may be sensitive or personal in nature.},
  address = {Bristol, UK},
  author = {Dwyer, Natasha and Miller-Bakewell, Hector and Darbyshire, Tessa and Basu, Anirban and Marsh, Steve},
  booktitle = {Qualitative and Digital Research in Times of Crisis: Methods, Reflexivity, and Ethics},
  day = {29},
  doi = {10.51952/9781447363828.ch008},
  keywords = {Social research methods; Qualitative methods; Creative methods; Disaster and crisis management; Research practices; Research ethics; Research reflexivity; Researcher positionality; Digital research methods; Digital data; Digital traces; Data ethics; Data privacy; Data protection; Data security; Data sharing; Data reuse},
  month = {November},
  pages = {129-142},
  publisher = {Policy Press},
  title = {The ethical implications of using digital traces: studying explainability and trust during a pandemic},
  url = {https://bristoluniversitypressdigital.com/view/book/9781447363828/ch008.xml},
  year = {2021},
}

Thinking about Trust: People, Process, and Place

2020-06-12T00:00:00+00:00

Stephen Marsh, Tosan Atele-Williams, Anirban Basu, Natasha Dwyer, Peter R. Lewis, Hector Miller-Bakewell and Jeremy Pitt

Abstract: This brief paper is about trust. It explores the phenomenon from various angles, with the implicit assumptions that trust can be measured in some ways, that trust can be compared and rated, and that trust is of worth when we consider entities from data, through artificial intelligences, to humans, with side trips along the way to animals. It explores trust systems and trust empowerment as opposed to trust enforcement, the creation of trust models, applications of trust, and the reasons why trust is of worth.

day	12
doi	10.1016/j.patter.2020.100039
issue	3
journal	Elsevier Cell Patterns
keywords	trust, trustworthiness, data, people, trust-empowerment, artificial-intelligence
month	06
publisher	Elsevier
volume	1

Cite this publication, using BibTeX

@article{marsh2020thinking,
  abstract = {This brief paper is about trust. It explores the phenomenon from various angles, with the implicit assumptions that trust can be measured in some ways, that trust can be compared and rated, and that trust is of worth when we consider entities from data, through artificial intelligences, to humans, with side trips along the way to animals. It explores trust systems and trust empowerment as opposed to trust enforcement, the creation of trust models, applications of trust, and the reasons why trust is of worth.},
  author = {Marsh, Stephen and Atele-Williams, Tosan and Basu, Anirban and Dwyer, Natasha and Lewis, Peter R.\  and Miller-Bakewell, Hector and Pitt, Jeremy},
  day = {12},
  doi = {10.1016/j.patter.2020.100039},
  issue = {3},
  journal = {Elsevier Cell Patterns},
  keywords = {trust;trustworthiness;data;people;trust empowerment;artificial intelligence},
  month = {June},
  publisher = {Elsevier},
  title = {Thinking about Trust: People, Process, and Place},
  volume = {1},
  year = {2020},
}

Privacy-friendly platform for healthcare data in cloud based on blockchain environment

2019-01-08T00:00:00+00:00

Abdullah Al Omar, Md Zakirul Alam Bhuiyan, Anirban Basu, Shinsaku Kiyomoto and Mohammad Shahriar Rahman

Abstract: Data in cloud has always been a point of attraction for the cyber attackers. Nowadays healthcare data in cloud has become their new interest. Attacks on these healthcare data can result in annihilating consequences for the healthcare organizations. Decentralization of these cloud data can minimize the effect of attacks. Storing and running computation on sensitive private healthcare data in cloud are possible by decentralization which is enabled by peer to peer (P2P) network. By leveraging the decentralized or distributed property, blockchain technology ensures the accountability and integrity. Different solutions have been proposed to control the effect of attacks using decentralized approach but these solutions somehow failed to ensure overall privacy of patient centric systems. In this paper, we present a patient centric healthcare data management system using blockchain technology as storage which helps to attain privacy. Cryptographic functions are used to encrypt patient's data and to ensure pseudonymity. We analyze the data processing procedures and also the cost effectiveness of the smart contracts used in our system.

day	08
doi	10.1016/j.future.2018.12.044
issn	0167-739X
journal	Future Generation Computer Systems
keywords	blockchain, decentralization, healthcare-data-in-cloud, pseudonymity, privacy, security, smart-contract
month	01
pages	511–521
volume	95

Cite this publication, using BibTeX

@article{ALOMAR2019,
  abstract = {Data in cloud has always been a point of attraction for the cyber attackers. Nowadays healthcare data in cloud has become their new interest. Attacks on these healthcare data can result in annihilating consequences for the healthcare organizations. Decentralization of these cloud data can minimize the effect of attacks. Storing and running computation on sensitive private healthcare data in cloud are possible by decentralization which is enabled by peer to peer (P2P) network. By leveraging the decentralized or distributed property, blockchain technology ensures the accountability and integrity. Different solutions have been proposed to control the effect of attacks using decentralized approach but these solutions somehow failed to ensure overall privacy of patient centric systems. In this paper, we present a patient centric healthcare data management system using blockchain technology as storage which helps to attain privacy. Cryptographic functions are used to encrypt patient's data and to ensure pseudonymity. We analyze the data processing procedures and also the cost effectiveness of the smart contracts used in our system.},
  author = {Abdullah Al Omar and Md Zakirul Alam Bhuiyan and Basu, Anirban and Shinsaku Kiyomoto and Mohammad Shahriar Rahman},
  day = {8},
  doi = {10.1016/j.future.2018.12.044},
  issn = {0167-739X},
  journal = {Future Generation Computer Systems},
  keywords = {Blockchain, Decentralization, Healthcare data in cloud, Pseudonymity, Privacy, Security, Smart contract},
  month = {January},
  pages = {511–521},
  title = {Privacy-friendly platform for healthcare data in cloud based on blockchain environment},
  volume = {95},
  year = {2019},
}