Recent advances in industrial wireless sensor networks towards efficient management in IoT

With the accelerated development of Internet-of- Things (IoT), wireless sensor networks (WSN) are gaining importance in the continued advancement of information and communication technologies, and have been connected and integrated with Internet in vast industrial applications. However, given the fact that most wireless sensor devices are resource constrained and operate on batteries, the communication overhead and power consumption are therefore important issues for wireless sensor networks design. In order to efficiently manage these wireless sensor devices in a unified manner, the industrial authorities should be able to provide a network infrastructure supporting various WSN applications and services that facilitate the management of sensor-equipped real-world entities. This paper presents an overview of industrial ecosystem, technical architecture, industrial device management standards and our latest research activity in developing a WSN management system. The key approach to enable efficient and reliable management of WSN within such an infrastructure is a cross layer design of lightweight and cloud-based RESTful web service

KYoT: Self-sovereign IoT Identification with a Physically Unclonable Function

The integration of Internet-of-Things (IoT) and Blockchains (BC) for trusted and decentralized approaches enabled modern use cases, such as supply chain tracing, smart cities, and IoT data marketplaces. For these it is essential to identify reliably IoT devices, since the producer-consumer trust is not guaranteed by a Trusted Third Party (TTP). Therefore, this work proposes a Know Your IoT device platform (KYoT), which enables the self-sovereign identification of IoT devices on the Ethereum BC. KYoT permits manufacturers and device owners to register and verify IoT devices in a self-sovereign fashion, while data storage security is ensured. KYoT deploys an SRAM-based (Static Random Access Memory) Physically Unclonable Function (PUF), which takes advantage of the manufacturing variability of devices’ SRAM chips to derive a unique identifying key for each IoT device. The self-sovereign identification mechanism introduced is based on the ERC 734 and ERC 735 Ethereum identity standards

Contributions on using embedded memory circuits as physically unclonable functions considering reliability issues

[eng] Moving towards Internet-of-Things (IoT) era, hardware security becomes a crucial research topic, because of the growing demand of electronic products that are remotely connected through networks. Novel hardware security primitives based on manufacturing process variability are proposed to enhance the security of the IoT systems. As a trusted root that provides physical randomness, a physically unclonable function is an essential base for hardware security. SRAM devices are becoming one of the most promising alternatives for the implementation of embedded physical unclonable functions as the start-up value of each bit-cell depends largely on the variability related with the manufacturing process. Not all bit-cells experience the same degree of variability, so it is possible that some cells randomly modify their logical starting value, while others will start-up always at the same value. However, physically unclonable function applications, such as identification and key generation, require more constant logical starting value to assure high reliability in PUF response. For this reason, some kind of post-processing is needed to correct the errors in the PUF response. Unfortunately, those cells that have more constant logic output are difficult to be detected in advance. This work characterizes by simulation the start-up value reproducibility proposing several metrics suitable for reliability estimation during design phases. The aim is to be able to predict by simulation the percentage of cells that will be suitable to be used as PUF generators. We evaluate the metrics results and analyze the start-up values reproducibility considering different external perturbation sources like several power supply ramp up times, previous internal values in the bit-cell, and different temperature scenarios. The characterization metrics can be exploited to estimate the number of suitable SRAM cells for use in PUF implementations that can be expected from a specific SRAM design.[cat] En l’era de la Internet de les coses (IoT), garantir la seguretat del hardware ha esdevingut un tema de recerca crucial, en especial a causa de la creixent demanda de productes electrònics que es connecten remotament a través de xarxes. Per millorar la seguretat dels sistemes IoT, s’han proposat noves solucions hardware basades en la variabilitat dels processos de fabricació. Les funcions físicament inclonables (PUF) constitueixen una font fiable d’aleatorietat física i són una base essencial per a la seguretat hardware. Les memòries SRAM s’estan convertint en una de les alternatives més prometedores per a la implementació de funcions físicament inclonables encastades. Això és així ja que el valor d’encesa de cada una de les cel·les que formen els bits de la memòria depèn en gran mesura de la variabilitat pròpia del procés de fabricació. No tots els bits tenen el mateix grau de variabilitat, així que algunes cel·les canvien el seu estat lògic d’encesa de forma aleatòria entre enceses, mentre que d’altres sempre assoleixen el mateix valor en totes les enceses. No obstant això, les funcions físicament inclonables, que s’utilitzen per generar claus d’identificació, requereixen un valor lògic d’encesa constant per tal d’assegurar una resposta fiable del PUF. Per aquest motiu, normalment es necessita algun tipus de postprocessament per corregir els possibles errors presents en la resposta del PUF. Malauradament, les cel·les que presenten una resposta més constant són difícils de detectar a priori. Aquest treball caracteritza per simulació la reproductibilitat del valor d’encesa de cel·les SRAM, i proposa diverses mètriques per estimar la fiabilitat de les cel·les durant les fases de disseny de la memòria. L'objectiu és ser capaç de predir per simulació el percentatge de cel·les que seran adequades per ser utilitzades com PUF. S’avaluen els resultats de diverses mètriques i s’analitza la reproductibilitat dels valors d’encesa de les cel·les considerant diverses fonts de pertorbacions externes, com diferents rampes de tensió per a l’encesa, els valors interns emmagatzemats prèviament en les cel·les, i diferents temperatures. Es proposa utilitzar aquestes mètriques per estimar el nombre de cel·les SRAM adients per ser implementades com a PUF en un disseny d‘SRAM específic.[spa] En la era de la Internet de las cosas (IoT), garantizar la seguridad del hardware se ha convertido en un tema de investigación crucial, en especial a causa de la creciente demanda de productos electrónicos que se conectan remotamente a través de redes. Para mejorar la seguridad de los sistemas IoT, se han propuesto nuevas soluciones hardware basadas en la variabilidad de los procesos de fabricación. Las funciones físicamente inclonables (PUF) constituyen una fuente fiable de aleatoriedad física y son una base esencial para la seguridad hardware. Las memorias SRAM se están convirtiendo en una de las alternativas más prometedoras para la implementación de funciones físicamente inclonables empotradas. Esto es así, puesto que el valor de encendido de cada una de las celdas que forman los bits de la memoria depende en gran medida de la variabilidad propia del proceso de fabricación. No todos los bits tienen el mismo grado de variabilidad. Así pues, algunas celdas cambian su estado lógico de encendido de forma aleatoria entre encendidos, mientras que otras siempre adquieren el mismo valor en todos los encendidos. Sin embargo, las funciones físicamente inclonables, que se utilizan para generar claves de identificación, requieren un valor lógico de encendido constante para asegurar una respuesta fiable del PUF. Por este motivo, normalmente se necesita algún tipo de posprocesado para corregir los posibles errores presentes en la respuesta del PUF. Desafortunadamente, las celdas que presentan una respuesta más constante son difíciles de detectar a priori. Este trabajo caracteriza por simulación la reproductibilidad del valor de encendido de celdas SRAM, y propone varias métricas para estimar la fiabilidad de las celdas durante las fases de diseño de la memoria. El objetivo es ser capaz de predecir por simulación el porcentaje de celdas que serán adecuadas para ser utilizadas como PUF. Se evalúan los resultados de varias métricas y se analiza la reproductibilidad de los valores de encendido de las celdas considerando varias fuentes de perturbaciones externas, como diferentes rampas de tensión para el encendido, los valores internos almacenados previamente en las celdas, y diferentes temperaturas. Se propone utilizar estas métricas para estimar el número de celdas SRAM adecuadas para ser implementadas como PUF en un diseño de SRAM específico

An Improved Public Unclonable Function Design for Xilinx FPGAs for Hardware Security Applications

In the modern era we are moving towards completely connecting many useful electronic devices to each other through internet. There is a great need for secure electronic devices and systems. A lot of money is being invested in protecting the electronic devices and systems from hacking and other forms of malicious attacks. Physical Unclonable Function (PUF) is a low-cost hardware scheme that provides affordable security for electronic devices and systems. This thesis proposes an improved PUF design for Xilinx FPGAs and evaluates and compares its performance and reliability compared to existing PUF designs. Furthermore, the utility of the proposed PUF was demonstrated by using it for hardware Intellectual Property (IP) core licensing and authentication. Hardware Trojan can be used to provide evaluation copy of IP cores for a limited time. After that it disables the functionality of the IP core. A finite state machine (FSM) based hardware trojan was integrated with a binary divider IP core and evaluated for licensing and authentication applications. The proposed PUF was used in the design of hardware trojan. Obfuscation metric measures the effectiveness of hardware trojan. A moderately good obfuscation level was achieved for our hardware trojan

Design of hardware-based security solutions for interconnected systems

Among all the different research lines related to hardware security, there is a particular topic that strikingly attracts attention. That topic is the research regarding the so-called Physical Unclonable Functions (PUF). The PUFs, as can be seen throughout the Thesis, present the novel idea of connecting digital values uniquely to a physical entity, just as human biometrics does, but with electronic devices. This beautiful idea is not free of obstacles, and is the core of this Thesis. It is studied from different angles in order to better understand, in particular, SRAM PUFs, and to be able to integrate them into complex systems that expand their potential. During Chapter 1, the PUFs, their properties and their main characteristics are defined. In addition, the different types of PUFs, and their main applications in the field of security are also summarized. Once we know what a PUF is, and the types of them we can find, throughout Chapter 2 an exhaustive analysis of the SRAM PUFs is carried out, given the wide availability of SRAMs today in most electronic circuits (which dramatically reduces the cost of deploying any solution). An algorithm is proposed to improve the characteristics of SRAM PUFs, both to generate identifiers and to generate random numbers, simultaneously. The results of this Chapter demonstrates the feasibility of implementing the algorithm, so in the following Chapters it is explored its integration in both hardware and software systems. In Chapter 3 the hardware design and integration of the algorithm introduced in Chapter 2 is described. The design is presented together with some examples of use that demonstrate the possible practical realizations in VLSI designs. In an analogous way, in Chapter 4 the software design and integration of the algorithm introduced in Chapter 2 is described. The design is presented together with some examples of use that demonstrate the possible practical realizations in low-power IoT devices. The algorithm is also described as part of a secure firmware update protocol that has been designed to be resistant to most current attacks, ensuring the integrity and trustworthiness of the updated firmware.In Chapter 5, following the integration of PUF-based solutions into protocols, PUFs are used as part of an authentication protocol that uses zero-knowledge proofs. The cryptographic protocol is a Lattice-based post-quantum protocol that guarantees the integrity and anonymity of the identity generated by the PUF. This type of architecture prevents any type of impersonation or virtual copy of the PUF, since this is unknown and never leaves the device. Specifically, this type of design has been carried out with the aim of having traceability of identities without ever knowing the identity behind, which is very interesting for blockchain technologies. Finally, in Chapter 6 a new type of PUF, named as BPUF (Behavioral and Physical Unclonable Function), is proposed and analyzed according to the definitions given in Chapter 1. This new type of PUF significantly changes the metrics and concepts to which we were used to in previous Chapters. A new multi-modal authentication protocol is presented in this Chapter, taking advantage of the challenge-response tuples of BPUFs. An example of BPUFs is illustrated with SRAMs. A proposal to integrate the BPUFs described in Chapter 6 into the protocol of Chapter 5, as well as the final remarks of the Thesis, can be found in Chapter 7

SRAM PUF의 신뢰성 개선을 위한 전원 공급 기법

학위논문 (석사) -- 서울대학교 대학원 : 융합과학기술대학원 융합과학부(지능형융합시스템전공), 2021. 2. 전동석.PUF (Physically Unclonable Function)은 하드웨어 레벨의 인증 과 정에서 널리 이용되는 방법이다. 그 중에서도 SRAM PUF는 가장 잘 알 려진 PUF의 방법론이다. 그러나 예측 불가능한 동작으로 인해 발생되는 낮은 재생산성과 전원 공급 과정에서 발생하는 노이즈의 문제를 가지고 있다. 본 논문에서는 효과적으로 SRAM PUF의 재생산성을 향상시킬 수 있는 두 가지 전원 공급 기법을 제안한다. 제시한 기법들은 값이 산출되 는 영역 혹은 전원 공급원의 기울기(ramp-up 시간)를 조절함으로써 원 하지 않는 비트의 뒤집힘(flipping) 현상을 줄인다. 180nm 공정으로 제 작된 테스트 칩을 이용한 측정 결과 재생산성이 2.2배 향상되었을 뿐만 아니라 NUBs(Native Unstable Bits)는 54.87% 그리고 BER (Bit Error Rate)는 55.05% 감소한 것을 확인하였다.Physically unclonable function (PUF) is a widely used hardware-level identification method. SRAM-based PUFs are the most well-known PUF topology, but they typically suffer from low reproducibility due to non-deterministic behaviors and noise during power-up process. In this work, we propose two power-up control techniques that effectively improve reproducibility of the SRAM PUFs. The techniques reduce undesirable bit flipping during evaluation by controlling either evaluation region or power supply ramp-up speed. Measurement results from the 180 nm test chip confirm that native unstable bits (NUBs) are reduced by 54.87% and bit error rate (BER) decreases by 55.05% while reproducibility increases by 2.2×.Chapter 1 Introduction 1 1.1 PUF in Hardware Securit 1 1.2 Prior Works and Motivation 2 Chapter 2 Related works and Motivation 5 2.1 Uniqueness 7 2.2 Reproducibility 7 2.3 Hold Static Noise Margin (SNM) 8 2.4 Bit Error Rate (BER) 9 2.5 PUF Static Noise Margin Ratio (PSNMratio) 9 Chapter 3 Microarchitecture-Aware Code Generation 11 3.1 Scheme 1: Developing Fingerprint in Sub-Threshold Region 13 3.2 Scheme 2: Controlling Voltage Ramp-up Speed 17 Chapter 4 Experimental Evaluation 19 4.1 Experimental Setup 19 4.2 Evaluation Results 21 Chapter 5 Conclusion 28 Bibliography 29 Abstract in Korean 33Maste

Design of Hardware with Quantifiable Security against Reverse Engineering

Semiconductors are a 412 billion dollar industry and integrated circuits take on important roles in human life, from everyday use in smart-devices to critical applications like healthcare and aviation. Saving today\u27s hardware systems from attackers can be a huge concern considering the budget spent on designing these chips and the sensitive information they may contain. In particular, after fabrication, the chip can be subject to a malicious reverse engineer that tries to invasively figure out the function of the chip or other sensitive data. Subsequent to an attack, a system can be subject to cloning, counterfeiting, or IP theft. This dissertation addresses some issues concerning the security of hardware systems in such scenarios. First, the issue of privacy risks from approximate computing is investigated in Chapter 2. Simulation experiments show that the erroneous outputs produced on each chip instance can reveal the identity of the chip that performed the computation, which jeopardizes user privacy. The next two chapters deal with camouflaging, which is a technique to prevent reverse engineering from extracting circuit information from the layout. Chapter 3 provides a design automation method to protect camouflaged circuits against an adversary with prior knowledge about the circuit\u27s viable functions. Chapter 4 provides a method to reverse engineer camouflaged circuits. The proposed reverse engineering formulation uses Boolean Satisfiability (SAT) solving in a way that incorporates laser fault injection and laser voltage probing capabilities to figure out the function of an aggressively camouflaged circuit with unknown gate functions and connections. Chapter 5 addresses the challenge of secure key storage in hardware by proposing a new key storage method that applies threshold-defined behavior of memory cells to store secret information in a way that achieves a high degree of protection against invasive reverse engineering. This approach requires foundry support to encode the secrets as threshold voltage offsets in transistors. In Chapter 6, a secret key storage approach is introduced that does not rely on a trusted foundry. This approach only relies on the foundry to fabricate the hardware infrastructure for key generation but not to encode the secret key. The key is programmed by the IP integrator or the user after fabrication via directed accelerated aging of transistors. Additionally, this chapter presents the design of a working hardware prototype on PCB that demonstrates this scheme. Finally, chapter 7 concludes the dissertation and summarizes possible future research

Non-invasive Techniques Towards Recovering Highly Secure Unclonable Cryptographic Keys and Detecting Counterfeit Memory Chips

Due to the ubiquitous presence of memory components in all electronic computing systems, memory-based signatures are considered low-cost alternatives to generate unique device identifiers (IDs) and cryptographic keys. On the one hand, this unique device ID can potentially be used to identify major types of device counterfeitings such as remarked, overproduced, and cloned. On the other hand, memory-based cryptographic keys are commercially used in many cryptographic applications such as securing software IP, encrypting key vault, anchoring device root of trust, and device authentication for could services. As memory components generate this signature in runtime rather than storing them in memory, an attacker cannot clone/copy the signature and reuse them in malicious activity. However, to ensure the desired level of security, signatures generated from two different memory chips should be completely random and uncorrelated from each other. Traditionally, memory-based signatures are considered unique and uncorrelated due to the random variation in the manufacturing process. Unfortunately, in previous studies, many deterministic components of the manufacturing process, such as memory architecture, layout, systematic process variation, device package, are ignored. This dissertation shows that these deterministic factors can significantly correlate two memory signatures if those two memory chips share the same manufacturing resources (i.e., manufacturing facility, specification set, design file, etc.). We demonstrate that this signature correlation can be used to detect major counterfeit types in a non-invasive and low-cost manner. Furthermore, we use this signature correlation as side-channel information to attack memory-based cryptographic keys. We validate our contribution by collecting data from several commercially available off-the-shelf (COTS) memory chips/modules and considering different usage-case scenarios

NoisFre: Noise-Tolerant Memory Fingerprints from Commodity Devices for Security Functions

Building hardware security primitives with on-device memory fingerprints is a compelling proposition given the ubiquity of memory in electronic devices, especially for low-end Internet of Things devices for which cryptographic modules are often unavailable. However, the use of fingerprints in security functions is challenged by the small, but unpredictable variations in fingerprint reproductions from the same device due to measurement noise. Our study formulates a novel and pragmatic approach to achieve highly reliable fingerprints from device memories. We investigate the transformation of raw fingerprints into a noise-tolerant space where the generation of fingerprints is intrinsically highly reliable. We derive formal performance bounds to support practitioners to easily adopt our methods for applications. Subsequently, we demonstrate the expressive power of our formalization by using it to investigate the practicability of extracting noise-tolerant fingerprints from commodity devices. Together with extensive simulations, we have employed 119 chips from five different manufacturers for extensive experimental validations. Our results, including an end-to-end implementation demonstration with a low-cost wearable Bluetooth inertial sensor capable of on-demand and runtime key generation, show that key generators with failure rates less than $10^-6$ can be efficiently obtained with noise-tolerant fingerprints with a single fingerprint snapshot to support ease-of-enrollment.Comment: Accepted to IEEE Transactions on Dependable and Secure Computing. Yansong Gao and Yang Su contributed equally to the study and are co-first authors in alphabetical orde