چالش‌های حقوقی سیستم‌های هویت بیومتریک در اجرای قانون و سیاست تشخیص (صدا)، مطالعۀ موردی: پروژۀ سیپ در اروپا

نوع مقاله : مقاله پژوهشی

نویسندگان

1 پژوهشگر دکتری حقوق بینالملل عمومی دانشگاه آزاد اسلامی واحد تهران شمال،تهران، ایران

2 استادیار گروه حقوق دانشگاه آزاد اسلامی واحد تهران شمال، تهران، ایران

چکیده

امروزه صداشناسی، که در تشــخیص هویــت اشــخاص کاربردی بی‌همتا دارد، به‌منزلۀ یکــی از روش‌هاش مــدرن درحــال پیشــرفت است. از این روش، به‌منزلۀ ادلۀ ابزاری مستند و مستدل در محاکم، نفیاً یا اثباتاً استفاده می‌شود. در رویکرد «تشخیص هویـت» با صـورت‌نگـاری و ترسـیم نمـودار ارتعاشـات صـوتی اصوات انسانی آزمـایش می‌شوند. منحصربه‌فردبودن صدای انسان در زمینۀ تشخیص مجرمان جرایم نوظهور ازطریق فنّاوری‌های فوق نوین، مانند تروریسم سایبر، تهدید به بمب‌گـذاری در هواپیماهـا و ابنیۀ دولتـی‌ با تلفن به قصـد اخـاذی و آدم‌ربایی کمـک بزرگـی است. درحال حاضر، سیستم‌های هویت بیومتریک یکی از طرق اجرای قانون در اروپاست. توجه به جمع‌آوری داده‌های بیومتریک در مقایسه با روش‌های وقت‌گیر، مانند انگشت‌نگاری و تشخیص چهره، نگرانی‌هایی را دربارۀ تأثیر این قبیل فنّاوری‌ها در حوزۀ تجسس و تفحص برای ضابطان قضایی از منظر حقوق اساسی بشر به وجود آورده است. پژوهش حاضر، چالش‌های حقوقی پروژۀ اخیر اروپا با عنوان «سیستم یکپارچۀ شناسایی سخن‌گوی صوتی (سیپ)» را، که به‌منزلۀ ابتکاری نوین برای راه‌اندازی اولین پایگاه دادۀ بین‌المللی بیومتریک صوتی به‌کار می‌رود، بررسی می‌کند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Legal Challenges of Biometric Identity Systems in Law Enforcement of Recognition Policy (Voice): A Case Study of Siip in Europe

نویسندگان [English]

  • Sima Hatami, 1
  • Fathollah Rahimi 2
  • Ehsan Agha Mohammad Aghaei 2
  • Esmaeil Shahsavandi 2
1 1 PhD Candidate in Public International Law, Azad University, North Tehran Branch, Tehran, Iran
2 Assistant Professor of Law, Azad University, North Tehran Branch, Tehran, Iran
چکیده [English]

Today, voice Identification technology is developing as one of the modern techniques, which has a unique application in identifying the identity of people in the form of recorded voice. This method can be used in courts and tribunals, not only to convict people but also as a definite proof to prove the innocence of accused persons. In this approach, "identity recognition" is tested through face painting and the sound vibration diagram method of human voices. The uniqueness of the human voice is a great help for law enforcement in identifying criminals, especially in the field of emerging new crimes with technology. Ultra-modern, such as cyber terrorism, which threatens to bomb aeroplanes, government buildings, etc., or over the phone with the intention of extortion in the kidnapping. Biometric identity systems are currently a prominent feature of contemporary law enforcement in Europe, as the focus on time-consuming biometric data collection, such as fingerprinting and facial recognition, raises concerns about the impact of these technologies on surveillance. For judicial officers from the perspective of fundamental human rights. In particular, this paper examines the recent European project, the Integrated System for Voice Speaker Identification (SIIP), as a new Europe-wide initiative to create the first international voice biometric database, now the third largest biometric database in the world as used by Interpol.

کلیدواژه‌ها [English]

  • Voice Identification
  • Biometric
  • Identity
  • Recognition policy
هداوند، مهدی و جم، فرهاد (1400). مفهوم دولت تنظیم‌گر: تحلیل تنظیم‌گری به مثابۀ ابزار حکمرانی. راهبرد، 30(۹۹)، 266-۲۲۷.
Abdelwhab, A., & Viriri, S. (2018). A survey on soft biometrics for human identification. Machine Learning and Biometrics, p. 37
Alegre, F., Soldi, G., & Evans, N. (2014, May). Evasion and obfuscation in automatic speaker verification. In 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 749-753). IEEE.‏
Amoore, L. (2019). Doubt and the algorithm: On the partial accounts of machine learning. Theory, Culture & Society36(6), 147-169.‏
Amoore, L. (2020). Cloud ethics: Algorithms and the attributes of ourselves and others. Duke University Press.‏
Andrejevic, M. (2013). Exploitation in the data mine. In Internet and surveillance (pp. 71-88). Routledge.
Aronowitz, H., Hoory, R., Pelecanos, J., & Nahamoo, D. (2011). New developments in voice biometrics for user authentication. In Twelfth Annual Conference of the International Speech Communication Association.‏, Florence, Italy, 28–31 August 2011, pp.17–20.
Bell, Derrick A. A. (1995). Who’s Afraid of Critical Race Theory University of Illino law reviw, 1995(4), pp. 893-910.
Watch, B. B. (2018). Face off: The lawless growth of facial recognition in UK policing. Obtenido de: bigbrotherwatch. org. uk/wp-content/uploads/2018/05/Face-Off-final-digital-1. pdf. Consultado el22. Available at: https://bigbrotherwatch.org.uk/wpcontent/uploads/2018/05/Face-Off-final-digital-1.pdf.
Bora, A. (2017). Semantics of ruling: reflective theories of regulation, governance and law. In Society, Regulation and Governance (pp. 15-37). Edward Elgar Publishing.‏
Bourdieu, P. (1982). Classification Struggles. Cambridge and Medford, MA: Polity.
Bourdieu, P. (2018). Classification Struggles. Cambridge and Medford, MA: Polity.
Brayne, S. (2020). Predict and surveil: Data, discretion, and the future of policing. Oxford University Press, USA.‏
Brayne, S., & Christin, A. (2021). Technologies of crime prediction: The reception of algorithms in policing and criminal courts. Social problems68(3), 608-624.‏
Browne, S. (2015). Dark Matters: On the Surveillance of Blackness. Durham: Duke University Press.
Buolamwini, J., & Gebru, T. (2018, January). Gender shades: Intersectional accuracy disparities in commercial gender classification. In Conference on fairness, accountability and transparency (pp. 77-91). PMLR.‏
 Burke, P. J., & Stets, J. E. (2009). Identity theory: Oxford University Press. New York, NY.‏
Cheney-Lippold, J. (2017). We are data. In We Are Data. New York University Press.‏
Couldry, N. (2010). Why voice matters: Culture and politics after neoliberalism. Sage publications.‏
Couldry, N., & Mejias, U. A. (2019). Data colonialism: Rethinking big data’s relation to the contemporary subject. Television & New Media20(4), 336-349.‏
Dantcheva, A., Elia, P., & Ross, A. (2015). What else does your biometric data reveal? A survey on soft biometrics. IEEE Transactions on Information Forensics and Security11(3), 441-467.‏
Dehak, N., Kenny, P.J., Dehak, R., Dumouchel, P., Ouellet, P. (2011). Front-end factor analysis for speaker verification. IEEE Transactions on Audio. Speech, and Language Processing, 19(4), p. 788–798.
Dencik, L., Hintz, A., & Cable, J. (2016). Towards data justice? The ambiguity of anti-surveillance resistance in political activism. Big Data & Society3(2), 1–12.
Edri (2020). Facial recognition & biometric surveillance: document pool. Available at: https://edri.org/our-work/facial-recognitiondocument-pool/ (accessed 4 June 2021).
European Commission (2017) Speaker identification integrated project. September 10th 2017. Available at: https://cordis. europa.eu/project/id/607784 (accessed 17 June 2021).
Fanon, F. (2008). Black skin, white masks. Grove press.‏
Ferras, M., Madikeri, S. R., Dey, S., Motlícek, P., & Bourlard, H. (2016). Inter-Task System Fusion for Speaker Recognition. In INTERSPEECH (pp. 1810-1814).‏
Jansen, F., Sánchez-Monedero, J., & Dencik, L. (2021). Biometric identity systems in law enforcement and the politics of (voice) recognition: The case of SiiP. Big Data & Society8(2), 20539517211063604.
‏Fourcade, M., & Healy, K. (2017). Seeing like a market. Socio-economic review15(1), 9-29.‏
Fussey, P., & Murray, D. (2019). Independent report on the London Metropolitan Police Service’s trial of live facial recognition technology. Available at: https:// repository.essex.ac.uk/24946/1/London-Met-Police-Trial-ofFacial-Recognition-Tech-Report-2.pdf.
Garland, D. (2004). Beyond the culture of control. Critical review of international social and political philosophy7(2), 160-189.‏.
Gates, K. A. (2011). Our biometric future: Facial recognition technology and the culture of surveillance (Vol. 2). NYU Press.‏
Haggerty, K. D., & Ericson, R. V. (2000). The surveillant assemblage. The British journal of sociology51(4), 605-622.‏
Herzig, R. (2017). The Role of Symbolic Capital in Digital Inequality: Lessons from The Student Room's Reputation System (Doctoral dissertation, University of East Anglia).‏
Interpol (2018a). Speaker 04. Available at: https://www.youtube. com/watch?v=foXSJCtHSqs (accessed 18 June 2021).
Interpol (2018b). Speaker Identification Integrated Project. Available at: https://www.interpol.int/en/Who-we-are/Legalframework/Information-communications-and-technology-ICTlaw-projects/Speaker-Identification-Integrated-Project-SIIP (accessed 8 December, 2021).
Kak, A. (2020). Regulating biometrics: Global approaches and urgent questions. AI Now Institute, September1.‏
Khelif, K., Mombrun, Y., Backfried, G., Sahito, F., Scarpato, L., Motlicek, P., Madikeri, S. R., Kelly, D, Hazzani, G. & Chatzigavriil, E. (2017, September). Towards a breakthrough speaker identification approach for law enforcement agencies: SIIP. In 2017 European Intelligence and Security Informatics Conference (EISIC) (pp. 32-39). IEEE.‏
Khelif, K., Mombrun, Y., Hazzani, G., Motlicek, P., Madikeri, S., Sahito, F., & Backfried, G. (2018). SIIP: An innovative speaker identification approach for law enforcement agencies. In STO meeting proceedings paper, NATO-OTAN (pp. 1-14).‏
Kind, C. (2019). Biometrics and facial recognition technology–where next. Ada Lovelace Institute. Available at: https://www.adalovelaceinstitute.org/blog/biometrics-and-facialrecognition-technology-where-next/ (accessed 4 July 2021).
Kindt, E. (2020). A first attempt at regulating biometric data in the European Union. Regulating Biometrics: Global Approaches and Open Questions. New York: AI Now, p. 62-69.‏
Kofman, A. (2018). Interpol rolls out international voice identification database using samples from 192 law enforcement agencies. The Intercept25.‏
 Kroemer, H., & Kittel, C. (1980). Thermal Physics. (2nd ed.) W.H. Freeman Company.
Leese, M. (2022). Fixing state vision: Interoperability, biometrics, and identity management in the EU. Geopolitics27(1), 113-133.‏ DOI: 10.1080/14650045.2020.1830764.
Li, S.Z. & Jain, A.K. (2015). Encyclopedia of Biometrics. Boston, MA: Springer
Liberty (2020) Liberty wins ground-breaking victory against facial recognition tech. In: Liberty. Available at: https://www. libertyhumanrights.org.uk/issue/liberty-wins-groundbreaking-victory-against-facial-recognition-tech/ (accessed 26 June 2021).
Lyon, D. (2008). Biometrics, identification and surveillance. Bioethics22(9), 499-508.‏
Madikeri, S., Motlicek, P., & Dey, S. (2019, May). A Bayesian approach to inter-task fusion for speaker recognition. In ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 5786-5790). IEEE.‏
Marciano, A. (2019). Reframing biometric surveillance: from a means of inspection to a form of control. Ethics and Information Technology21(2), 127-136.‏
McBride, C. (2013). Recognition. Camridge, Malden: Polity.
Morrison, G. S., Sahito, F. H., Jardine, G., Djokic, D., Clavet, S., Berghs, S., & Dorny, C. G. (2016). INTERPOL survey of the use of speaker identification by law enforcement agencies. Forensic science international263, 92-100.‏
Park, U., & Jain, A. K. (2010). Face matching and retrieval using soft biometrics. IEEE Transactions on Information Forensics and Security5(3), 406-415.‏
Poddar, A., Sahidullah, M., & Saha, G. (2019). Quality measures for speaker verification with short utterances. Digital Signal Processing88, 66-79.‏
Pollack, I., Pickett, J. M., & Sumby, W. H. (1954). On the identification of speakers by voice. the Journal of the Acoustical Society of America26(3), 403-406.‏
Rashid, R. A., Mahalin, N. H., Sarijari, M. A., & Aziz, A. A. A. (2008, May). Security system using biometric technology: Design and implementation of Voice Recognition System (VRS). In 2008 international conference on computer and communication engineering (pp. 898-902). IEEE.‏
Sánchez-Monedero, J., & Dencik, L. (2022). The politics of deceptive borders:‘biomarkers of deceit’and the case of iBorderCtrl. Information, Communication & Society25(3), 413-430. DOI: 10.1080/ 1369118X.2020.1792530.
Scott, J. C. (2020). Seeing like a state: How certain schemes to improve the human condition have failed. yale university Press.‏
Taylor, C. (1994). Multiculturalism: Examining the Politics of Recognition. Princeton, NJ: Princeton University Press.
Taylor, L. (2017). What is data justice? The case for connecting digital rights and freedoms globally. Big Data & Society4(2), 1-14.‏
Turow, J. (2021). The Voice Catchers: How Marketers Listen In to Exploit Your Feelings, Your Privacy, and Your Wallet. New Haven: Yale University Press.
Valentino-DeVries, J. (2020). How the Police Use Facial Recognition, and Where It Falls Short-The New York Times. URL: https://www. nytimes. com/2020/01/12/technology/facial-recognition-police. html.‏
Van der Ploeg, I. (1999). The illegal body:Eurodac'and the politics of biometric identification. Ethics and Information Technology1, 295-302.‏
Van Zoonen, L. (2013). From identity to identification: fixating the fragmented self. Media, Culture & Society35(1), 44-51.‏
Williams, P. (2015). Criminalising the other: Challenging the race-gang nexus. Race & Class56(3), 18-35.‏
Williams, P., & Clarke, B. (2016). Dangerous associations: Joint enterprise, gangs and racism. Centre for Crime and Justice Studies, 1-24.‏
Young, I. M. (1990). Justice and the Politics of Difference. Princeton University Press.‏