Difference between revisions of "Journal:Digital transformation risk management in forensic science laboratories"
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==Introduction== | ==Introduction== | ||
[[Forensic laboratory|Forensic science laboratories]] are becoming more reliant on computers and data for both administrative and analytical operations. These technological advances create new opportunities and risks for all [[Forensic science|forensic disciplines]], not only to digital evidence.<ref name="PollittAFrame19">{{cite web |url=https://www.nist.gov/system/files/documents/2018/01/10/osac_ts_0002.pdf |format=PDF |title=A Framework for Harmonizing Forensic Science Practices and Digital/Multimedia Evidence |author=Pollitt, M.; Casey, E.; Jaquet-Chiffelle, D.-O. et al. |publisher=OSAC |date=February 2019}}</ref> With proper preparation and management, forensic laboratories can employ technology effectively to improve performance and quality, while mitigating the associated risks. However, many forensic laboratories do not understand the subtlety and expertise required to manage risks of digital transformation, inadvisedly treating it as simply a technical component of existing [[Quality management system|quality management processes]]. Forensic laboratories that fail to realize the need for forensic digital preparedness to actively manage risks associated with digital transformations are vulnerable to significant expense, disruption, and liability when problems arise. | |||
Forensic laboratories rely on technology for much more than communication and routine business functions. Sophisticated equipment for processing chemical and biological materials are operated using computers and save results in digital form. [[Mass spectrometry|Mass spectrometers]], DNA analysis systems, and other [[laboratory]] equipment save their results in raw data files. Digital evidence is processed using specialized hardware and software, although not all forensic laboratories have integrated this new discipline. Forensic laboratories are using computerized case management systems for tracking treatment of all evidential exhibits and forensic results. Automated systems with [[artificial intelligence]] (AI) are being used to support forensic analysis. In reality, digital transformations—the use of digital technology to make existing processes more efficient and effective, and to develop new solutions to emerging problems—are well underway, and forensic laboratories require a robust strategy to manage the associated risks and realize the opportunities. | |||
This increased dependence on digital technology creates risks and opportunities for forensic laboratories. Potential pitfalls include loss of data needed to perform forensic analysis, errors in [[Data analysis|analysis]] of physical traces (e.g., DNA, fingerprint, face) caused by computer hardware or software, ability to tamper with raw data files generated by laboratory equipment, and incorrect [[information]] input into [[laboratory information management system]]s (LIMS). Possible benefits are traceability and integrity of traces, reliability and reproducibility of results from information extracted from traces and stored as raw data, and use of AI to support forensic analysis. | |||
Lessons can be learned from the digital forensic domain, including forensic digital preparedness and accreditation challenges. Primary challenges encountered by digital forensic laboratories adopting quality standards include<ref name="TullyQuality20">{{cite journal |title=Quality standards for digital forensics: Learning from experience in England & Wales |journal=Forensic Science International: Digital Investigation |author=Tully, G.; Cohen, N.; Compton, D. et al. |volume=32 |at=200905 |year=2020 |doi=10.1016/j.fsidi.2020.200905}}</ref>: | |||
* Inaccurate or insufficient information in technical records, including [[chain of custody]], and no mechanism to detect subsequent changes to records. | |||
* Problems with the security of information technology systems and the [[backup]] processes of data. | |||
* Missing or insufficiently detailed procedures for treating digital data, and personnel not following documented procedures consistently. | |||
* Lack of robust [[Quality control|quality checking]] mechanisms, and issues with validation of methods. | |||
This paper presents risks and opportunities associated with digital transformation of forensic laboratories, providing examples based on the authors’ experiences. Examples have been anonymized, as the intention is to illustrate general lessons learned rather than critique specific laboratories. This work then presents forensic digital preparedness, a set of recommendations to help laboratories navigate risks associated with digital transformations, including mishandled exhibits, allegations of employee misconduct, and disclosure requirements. The role of digital forensic capabilities and expertise in risk management of digital transformations in laboratories is discussed. This work culminates with broader implications for international standards such as [[ISO/IEC 17025]], which are used to assess and accredit laboratories. | |||
==Risks and remedies== | |||
Revision as of 18:47, 29 March 2021
| Full article title | Digital transformation risk management in forensic science laboratories |
|---|---|
| Journal | Forensic Science International |
| Author(s) | Casey, Eoghan; Souvignet, Thomas R. |
| Author affiliation(s) | University of Lausanne |
| Primary contact | Email: thomas dot souvignet at unil dot ch |
| Year published | 2020 |
| Volume and issue | 316 |
| Article # | 110486 |
| DOI | 10.1016/j.forsciint.2020.110486 |
| ISSN | 0379-0738 |
| Distribution license | Creative Commons Attribution 4.0 International |
| Website | https://www.sciencedirect.com/science/article/pii/S0379073820303480 |
| Download | https://www.sciencedirect.com/science/article/pii/S0379073820303480/pdfft (PDF) |
 |
This article should be considered a work in progress and incomplete. Consider this article incomplete until this notice is removed. |
Abstract
Technological advances are changing how forensic laboratories operate in all forensic disciplines, not only digital. Computers support workflow management and enable evidence analysis (physical and digital), while new technology enables previously unavailable forensic capabilities. Used properly, the integration of digital systems supports greater efficiency and reproducibility, and drives digital transformation of forensic laboratories. However, without the necessary preparations, these digital transformations can undermine the core principles and processes of forensic laboratories. Forensic preparedness concentrating on digital data reduces the cost and operational disruption of responding to various kinds of problems, including misplaced exhibits, allegations of employee misconduct, disclosure requirements, and information security breaches.
This work gives pertinent examples of problems and risks involving technology that have occurred in forensic laboratories, along with opportunities and risk mitigation strategies, based on the authors’ experiences. It also presents recommendations to help forensic laboratories prepare for and manage these risks, to use technology effectively, and ultimately strengthen forensic science. The importance of involving digital forensic expertise in risk management of digital transformations in laboratories is emphasized. Forensic laboratories that do not adopt forensic digital preparedness will produce results based on digital data and processes that cannot be verified independently, leaving them vulnerable to challenge. The recommendations in this work could enhance international standards such as ISO/IEC 17025, which are used to assess and accredit laboratories.
Keywords: forensic science, digital transformations, forensic laboratories, forensic preparedness, forensic digital preparedness, risk management, ISO/IEC 17025
Introduction
Forensic science laboratories are becoming more reliant on computers and data for both administrative and analytical operations. These technological advances create new opportunities and risks for all forensic disciplines, not only to digital evidence.[1] With proper preparation and management, forensic laboratories can employ technology effectively to improve performance and quality, while mitigating the associated risks. However, many forensic laboratories do not understand the subtlety and expertise required to manage risks of digital transformation, inadvisedly treating it as simply a technical component of existing quality management processes. Forensic laboratories that fail to realize the need for forensic digital preparedness to actively manage risks associated with digital transformations are vulnerable to significant expense, disruption, and liability when problems arise.
Forensic laboratories rely on technology for much more than communication and routine business functions. Sophisticated equipment for processing chemical and biological materials are operated using computers and save results in digital form. Mass spectrometers, DNA analysis systems, and other laboratory equipment save their results in raw data files. Digital evidence is processed using specialized hardware and software, although not all forensic laboratories have integrated this new discipline. Forensic laboratories are using computerized case management systems for tracking treatment of all evidential exhibits and forensic results. Automated systems with artificial intelligence (AI) are being used to support forensic analysis. In reality, digital transformations—the use of digital technology to make existing processes more efficient and effective, and to develop new solutions to emerging problems—are well underway, and forensic laboratories require a robust strategy to manage the associated risks and realize the opportunities.
This increased dependence on digital technology creates risks and opportunities for forensic laboratories. Potential pitfalls include loss of data needed to perform forensic analysis, errors in analysis of physical traces (e.g., DNA, fingerprint, face) caused by computer hardware or software, ability to tamper with raw data files generated by laboratory equipment, and incorrect information input into laboratory information management systems (LIMS). Possible benefits are traceability and integrity of traces, reliability and reproducibility of results from information extracted from traces and stored as raw data, and use of AI to support forensic analysis.
Lessons can be learned from the digital forensic domain, including forensic digital preparedness and accreditation challenges. Primary challenges encountered by digital forensic laboratories adopting quality standards include[2]:
- Inaccurate or insufficient information in technical records, including chain of custody, and no mechanism to detect subsequent changes to records.
- Problems with the security of information technology systems and the backup processes of data.
- Missing or insufficiently detailed procedures for treating digital data, and personnel not following documented procedures consistently.
- Lack of robust quality checking mechanisms, and issues with validation of methods.
This paper presents risks and opportunities associated with digital transformation of forensic laboratories, providing examples based on the authors’ experiences. Examples have been anonymized, as the intention is to illustrate general lessons learned rather than critique specific laboratories. This work then presents forensic digital preparedness, a set of recommendations to help laboratories navigate risks associated with digital transformations, including mishandled exhibits, allegations of employee misconduct, and disclosure requirements. The role of digital forensic capabilities and expertise in risk management of digital transformations in laboratories is discussed. This work culminates with broader implications for international standards such as ISO/IEC 17025, which are used to assess and accredit laboratories.
Risks and remedies
References
- ↑ Pollitt, M.; Casey, E.; Jaquet-Chiffelle, D.-O. et al. (February 2019). "A Framework for Harmonizing Forensic Science Practices and Digital/Multimedia Evidence" (PDF). OSAC. https://www.nist.gov/system/files/documents/2018/01/10/osac_ts_0002.pdf.
- ↑ Tully, G.; Cohen, N.; Compton, D. et al. (2020). "Quality standards for digital forensics: Learning from experience in England & Wales". Forensic Science International: Digital Investigation 32: 200905. doi:10.1016/j.fsidi.2020.200905.
Notes
This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added.
