mireabulletinRussian Technological JournalRussian Technological Journal2782-32102500-316XRTU MIREA10.32362/2500-316X-2026-14-3-83-105QIOHGImireabulletin-1540Research ArticleМИКРО- И НАНОЭЛЕКТРОНИКА. ФИЗИКА КОНДЕНСИРОВАННОГО СОСТОЯНИЯMICRO- AND NANOELECTRONICS. CONDENSED MATTER PHYSICSФизически неклонируемые функции в аналоговых интегральных схемахPhysically unclonable functions in analog integrated circuitshttps://orcid.org/0000-0001-6264-1231ПевцовЕ. Ф.PevtsovE. Ph.

Певцов Евгений Филиппович, к.т.н., директор структурного подразделения «Центр проектирования интегральных схем, устройств наноэлектроники и микросистем»

Scopus Author ID 6602652601, ResearcherID M-2709-2016

119454, Москва, пр-т Вернадского, д. 78

Evgenii Ph. Pevtsov, Cand. Sci. (Eng.), Director of Center for the Design of Integrated Circuits, Nanoelectronics Devices and Microsystems

Scopus Author ID 6602652601, ResearcherID M-2709-2016 

78, Vernadskogo pr., Moscow, 119454 

pevtsov@mirea.ruhttps://orcid.org/0000-0003-3519-6683ДеменковаТ. А.DemenkovaT. A.

Деменкова Татьяна Александровна, к.т.н., доцент, кафедра вычислительной техники, Институт информационных технологий

Scopus Author ID 57192958412, ResearcherID AAB-3937-2020

119454, Москва, пр-т Вернадского, д. 78

Tatyana A. Demenkova, Cand. Sci. (Eng.), Associate Professor, Computer Technology Department, Institute of Information Technologies

Scopus Author ID 57192958412, ResearcherID AAB-3937-2020 

78, Vernadskogo pr., Moscow, 119454 

demenkova@mirea.ruhttps://orcid.org/0009-0006-3603-6322МалетоМ. И.MaletoM. I.

Малето Михаил Иванович, к.т.н., ведущий инженер структурного подразделения «Центр проектирования интегральных схем, устройств наноэлектроники и микросистем»

119454, Москва, пр-т Вернадского, д. 78

Mikhail I. Maleto, Cand. Sci. (Eng.), Center for the Design of Integrated Circuits, Nanoelectronics Devices and Microsystems

78, Vernadskogo pr., Moscow, 119454 

maleto@yandex.ruСиговА. С.SigovA. S.

Сигов Александр Сергеевич, академик Российской академии наук, д.ф.-м.н., профессор, президент 

Scopus Author ID 35557510600, ResearcherID L-4103-2017 

119454, Москва, пр-т Вернадского, д. 78

Alexander S. Sigov, Academician at the Russian Academy of Sciences, Dr. Sci. (Phys.–Math.), Professor, President

Scopus Author ID 35557510600, ResearcherID L-4103-2017 

78, Vernadskogo pr., Moscow, 119454 

sigov@mirea.ruhttps://orcid.org/0009-0000-3976-7872КоротаевЮ. А.KorotaevYu. A.

Коротаев Юрий Александрович, аспирант, кафедра наноэлектроники, Институт перспективных технологий и индустриального программирования

119454, Москва, пр-т Вернадского, д. 78

Yuri A. Korotaev, Postgraduate Student, Department of Nanoelectronics, Institute for Advanced Technologies and Industrial Programming

78, Vernadskogo pr., Moscow, 119454 

korotaevyua@yandex.ruhttps://orcid.org/0009-0006-9073-8798ЕвгеньевН. Д.EvgenevN. D.

Евгеньев Никита Давидович,студент, кафедра вычислительной техники, Институт информационных технологий

119454, Москва, пр-т Вернадского, д. 78

Nikita D. Evgenev, Student, Computer Technology Department, Institute of Information Technologies 

78, Vernadskogo pr., Moscow, 119454 

nikita.evgenev.10@gmail.comМИРЭА – Российский технологический университетРоссияMIREA – Russian Technological UniversityRussian Federation20260206202614383105Copyright © Певцов Е.Ф., Деменкова Т.А., Малето М.И., Сигов А.С., Коротаев Ю.А., Евгеньев Н.Д., 20262026Певцов Е.Ф., Деменкова Т.А., Малето М.И., Сигов А.С., Коротаев Ю.А., Евгеньев Н.Д.Pevtsov E.P., Demenkova T.A., Maleto M.I., Sigov A.S., Korotaev Y.A., Evgenev N.D.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.rtj-mirea.ru/jour/article/view/1540Цели

Цели. Целью работы является комплексный обзор аналоговых и пассивных физически неклонируемых функций (ФНФ), анализ уязвимостей к атакам на основе машинного обучения и разбор практических сценариев применения в современных интегральных схемах и устройствах интернета вещей.

Методы

Методы. Использованы методы количественной оценки различий реализаций ФНФ и признаков их формального описания, включая вычислимость, уникальность, реализуемость, сложность создания клонов, защиту от несанкционированного доступа.

Результаты

Результаты. Показано, что аналоговые ФНФ относятся к классу «сильных» ФНФ, но требуют специальных мер для подавления влияния факторов внешней среды и старения. Приведены примеры, демонстрирующие близкую к идеальной уникальность (inter-HD1 ≈ 50%) при высокой стабильности (intra-HD2 < 1%) и рекордные энергетические показатели (единицы – десятки фДж/бит). Пассивные ФНФ характеризуются высокой стабильностью, но относятся к «слабым» ФНФ. Рассмотрены атаки на основе машинного обучения, показано, что конволюционные нейронные сети и многослойные перцептроны превосходят классические подходы. Средства защиты на уровне протокола, ограничивающие объем доступной злоумышленнику информации, позволяют избежать модификации архитектуры ФНФ.

Выводы

Выводы. Аналоговые и пассивные ФНФ расширяют спектр средств аппаратной аутентификации и защитыот подделок, особенно для маломощных и ресурсно-ограниченных устройств интернета вещей. Наиболее перспективны архитектуры с внутренней калибровкой и малыми накладными расходами по площади/потреблению, а также пассивные решения для задач однократной идентификации и контроля вмешательства. Остаются открытыми задачи стандартизации процедур чтения/оцифровки, повышения устойчивости к изменениям внешней среды и различным атакам, а также совмещения с коррекцией ошибок и постобработкой на кристалле. Для выбора архитектур ФНФ необходимо тщательное моделирование угроз и применение стратегий глубокой защиты с учетом будущих достижений машинного обучения.

Objectives

Objectives. The paper provides a comprehensive overview of analog and passive physical unclonable functions (PUFs), analyzing their vulnerabilities to machine-learning (ML) attacks, and assessing their practical deployment in modern integrated circuits and Internet of Things (IoT) devices.

Methods

Methods. Quantitative metrics were used to compare PUF implementations and their formal properties, such as computability, uniqueness, implementability, difficulty of cloning, and protection against unauthorized access.

Results

Results. Analog PUFs were shown to belong to the class of “strong” PUFs. However, special measures are required to counteract environmental and ageing effects. Examples are cited to demonstrate their near-ideal uniqueness (inter-Hamming distance ≈ 50%), high stability (intra-Hamming distance < 1%), and excellent energy performance (from units to tens of femtojoules per bit). While characterized by high stability, passive PUFs are classified as “weak” PUFs. A consideration of ML-based modeling attacks confirmed that convolutional neural networks and multilayer perceptrons outperform classical approaches. By limiting the amount of data available to an attacker, protocol-level protection prevents the PUF architecture from being modified.

Conclusions

Conclusions. Analog and passive PUFs expand the range of tools available for hardware authentication and anticounterfeiting, particularly in low-power, resource-constrained IoT nodes. The most promising directions include architectures with on-chip self-calibration and minimal area/power overhead, as well as passive schemes for onetime identification and tamper evidence. However, open challenges remain in terms of standardizing readout and digitization procedures, increasing robustness to environmental variation and diverse attacks, and integrating error correction and post-processing on the chip. The practical adoption and selection of architectures requires conservative threat modeling and defense-in-depth strategies that account for current attack capabilities and likely future advances in ML.

физически неклонируемая функцияаналоговые ФНФпассивные ФНФML-атакиаппаратная безопасностьаутентификация устройствинтернет вещейphysically unclonable functionanalog PUFspassive PUFsML attackshardware securitydevice authenticationInternet of ThingsРабота выполнена при поддержке Министерства науки и высшего образования РФ (Государственное задание для университетов № FSFZ-2026-0003) и с применением оборудования Центра коллективного пользования РТУ МИРЭА (соглашение от 01.09.2021 № 075-15-2021-689, уникальный идентификационный номер 2296.61321X0010).This work was supported by the Ministry of Science and Higher Education of the Russian Federation (State task for universities No. FSFZ-2026-0003) and using the equipment of the Center for Collective Use of RTU MIREA (agreement dated September 01, 2021, No. 075-15-2021-689, unique identification number 2296.61321X0010).ReferencesПевцов Е.Ф., Деменкова Т.А., Коротаев Ю.А., Сигов А.С. 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The authors declare that there are no conflicts of interest present.