RC PUF: A Low-Cost and an Easy-to-Design PUF for Resource-Constrained IoT Devices

The Internet of Things (IoT) paradigm envisions a world where everyday things interchange information between each other in a way that allows users to make smarter decisions in a given context. Even though IoT has many advantages, its characteristics make it very vulnerable to security attacks. Ciphers are a security primitive that can prevent some of the attacks; however, the constrained computing and energy resources of IoT devices impede them from implementing current ciphers. This article presents the stream cipher Generador de Bits Pseudo Aleatorios (GBPA) based on Salsa20 cipher, which is part of the eSTREAM project, but designed for resource-constrained IoT devices of Class 0. GBPA has lower program and data memory requirements compared with Salsa20 and lightweight ciphers. These properties allow low-cost resource-constrained IoT devices, 29.5% of the embedded systems in the market, to be able to implement a security service that they are currently incapable of, to preserve the user’s data privacy and protect the system from attacks that could damage it. For the evaluation of its output, three statistical test suites were used: NIST Statistical Test Suite (STS), DIEHARD and EACirc, with good results. The GBPA cipher provides security without having a negative impact on the computing resources of IoT devices.

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Approximate CPU Design for IoT End-Devices with Learning Capabilities

Electronics ◽

10.3390/electronics9010125 ◽

2020 ◽

Vol 9 (1) ◽

pp. 125 ◽

Cited By ~ 3

Author(s):

İbrahim Taştan ◽

Mahmut Karaca ◽

Arda Yurdakul

Keyword(s):

Power Consumption ◽

Low Cost ◽

Reducing Power ◽

Approximate Computing ◽

Resource Constrained ◽

Data Set ◽

Learning Capabilities ◽

Machine Learning Applications ◽

Constrained Learning ◽

Iot Devices

With the rise of Internet of Things (IoT), low-cost resource-constrained devices have to be more capable than traditional embedded systems, which operate on stringent power budgets. In order to add new capabilities such as learning, the power consumption planning has to be revised. Approximate computing is a promising paradigm for reducing power consumption at the expense of inaccuracy introduced to the computations. In this paper, we set forth approximate computing features of a processor that will exist in the next generation low-cost resource-constrained learning IoT devices. Based on these features, we design an approximate IoT processor which benefits from RISC-V ISA. Targeting machine learning applications such as classification and clustering, we have demonstrated that our processor reinforced with approximate operations can save power up to 23% for ASIC implementation while at least 90% top-1 accuracy is achieved on the trained models and test data set.

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Curve25519 based lightweight end-to-end encryption in resource constrained autonomous 8-bit IoT devices

Cybersecurity ◽

10.1186/s42400-021-00078-6 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Shafi Ullah ◽

Raja Zahilah

Keyword(s):

Hash Function ◽

Low Cost ◽

General Purpose ◽

Resource Constrained ◽

Physical Systems ◽

Computational Capability ◽

Calculated Curve ◽

Key Exchange Protocols ◽

Iot Devices ◽

Generator Function

AbstractRobust encryption techniques require heavy computational capability and consume large amount of memory which are unaffordable for resource constrained IoT devices and Cyber-Physical Systems with an inclusion of general-purpose data manipulation tasks. Many encryption techniques have been introduced to address the inability of such devices, lacking in robust security provision at low cost. This article presents an encryption technique, implemented on a resource constrained IoT device (AVR ATmega2560) through utilizing fast execution and less memory consumption properties of curve25519 in a novel and efficient lightweight hash function. The hash function utilizes GMP library for multi-precision arithmetic calculations and pre-calculated curve points to devise a good cipher block using ECDH based key exchange protocols and large random prime number generator function.

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Design of Resistor-Capacitor Physically Unclonable Function for Resource-Constrained IoT Devices

Sensors ◽

10.3390/s20020404 ◽

2020 ◽

Vol 20 (2) ◽

pp. 404

Author(s):

Sangjae Lee ◽

Mi-Kyung Oh ◽

Yousung Kang ◽

Dooho Choi

Keyword(s):

Small Difference ◽

Low Cost ◽

Resource Constrained ◽

Active Components ◽

Unique Identifier ◽

Passive Components ◽

The Past ◽

Design Flexibility ◽

Cryptographic Keys ◽

Iot Devices

Keeping IoT devices secure has been a major challenge recently. One of the possible solutions to secure IoT devices is to use a physically unclonable function (PUF). A PUF is a security primitive that can generate device-specific cryptographic information by extracting the features of hardware uncertainty. Because PUF instances are very difficult to replicate even by the manufacturer, the generated bit sequence can be used as cryptographic keys or as a unique identifier for the device. Regarding the implementation of PUF, the majority of PUFs introduced over the past decade are in the form of active components and have been implemented as separate chips or embedded as a part of a chip, making it difficult to use them in low-cost IoT devices due to cost and design flexibility. One approach to easily adopt PUFs in resource-constrained IoT devices is to use passive components such as resistors and capacitors (RC) that can be configured at low cost. The main feature of this RC-based PUF is that it extracts the small difference caused by charging and discharging of RC circuits and uses it as a response. In this paper, we extend the previous research and show the possibility to secure IoT devices by using the RC-based PUF.

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RPPUF: An Ultra-Lightweight Reconfigurable Pico-Physically Unclonable Function for Resource-Constrained IoT Devices

Electronics ◽

10.3390/electronics10233039 ◽

2021 ◽

Vol 10 (23) ◽

pp. 3039

Author(s):

Zhao Huang ◽

Liang Li ◽

Yin Chen ◽

Zeyu Li ◽

Quan Wang ◽

...

Keyword(s):

Low Cost ◽

Resource Constrained ◽

Security Issues ◽

Resource Limited ◽

Field Programmable ◽

Hardware Resource ◽

Inherent Nature ◽

Iot Devices ◽

Multiple Samples ◽

The Internet Of Things

With the advancement of the Internet of Things (IoTs) technology, security issues have received an increasing amount of attention. Since IoT devices are typically resource-limited, conventional security solutions, such as classical cryptography, are no longer applicable. A physically unclonable function (PUF) is a hardware-based, low-cost alternative solution to provide security for IoT devices. It utilizes the inherent nature of hardware to generate a random and unpredictable fingerprint to uniquely identify an IoT device. However, despite existing PUFs having exhibited a good performance, they are not suitable for effective application on resource-constrained IoT devices due to the limited number of challenge-response pairs (CRPs) generated per unit area and the large hardware resources overhead. To solve these problems, this article presents an ultra-lightweight reconfigurable PUF solution, which is named RPPUF. Our method is built on pico-PUF (PPUF). By incorporating configurable logics, one single RPPUF can be instantiated into multiple samples through configurable information K. We implement and verify our design on the Xilinx Spartan-6 field programmable gate array (FPGA) microboards. The experimental results demonstrate that, compared to previous work, our method increases the uniqueness, reliability and uniformity by up to 4.13%, 16.98% and 10.5%, respectively, while dramatically reducing the hardware resource overhead by 98.16% when a 128-bit PUF response is generated. Moreover, the bit per cost (BPC) metric of our proposed RPPUF increased by up to 28.5 and 53.37 times than that of PPUF and the improved butterfly PUF, respectively. This confirms that the proposed RPPUF is ultra-lightweight with a good performance, making it more appropriate and efficient to apply in FPGA-based IoT devices with constrained resources.

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Bringing Security to The Smallest Embedded Systems

10.34048/2017.1.f5 ◽

2017 ◽

Author(s):

JOSEPH YIU

Keyword(s):

Internet Of Things ◽

Embedded Systems ◽

Low Cost ◽

Security Requirements ◽

The Internet ◽

Security Measures ◽

Significant Challenge ◽

Iot Devices

The increasing need for security in microcontrollers Security has long been a significant challenge in microcontroller applications(MCUs). Traditionally, many microcontroller systems did not have strong security measures against remote attacks as most of them are not connected to the Internet, and many microcontrollers are deemed to be cheap and simple. With the growth of IoT (Internet of Things), security in low cost microcontrollers moved toward the spotlight and the security requirements of these IoT devices are now just as critical as high-end systems due to:

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Virtualizing AI at the Distributed Edge Towards Intelligent IoT Applications

Journal of Sensor and Actuator Networks ◽

10.3390/jsan10010013 ◽

2021 ◽

Vol 10 (1) ◽

pp. 13

Author(s):

Claudia Campolo ◽

Giacomo Genovese ◽

Antonio Iera ◽

Antonella Molinaro

Keyword(s):

Resource Constraints ◽

Smart Cities ◽

Traditional Approach ◽

Low Cost ◽

Iot Applications ◽

Software And Hardware ◽

Iot Devices ◽

Consumer Devices ◽

Hardware Platforms ◽

Smart Factories

Several Internet of Things (IoT) applications are booming which rely on advanced artificial intelligence (AI) and, in particular, machine learning (ML) algorithms to assist the users and make decisions on their behalf in a large variety of contexts, such as smart homes, smart cities, smart factories. Although the traditional approach is to deploy such compute-intensive algorithms into the centralized cloud, the recent proliferation of low-cost, AI-powered microcontrollers and consumer devices paves the way for having the intelligence pervasively spread along the cloud-to-things continuum. The take off of such a promising vision may be hurdled by the resource constraints of IoT devices and by the heterogeneity of (mostly proprietary) AI-embedded software and hardware platforms. In this paper, we propose a solution for the AI distributed deployment at the deep edge, which lays its foundation in the IoT virtualization concept. We design a virtualization layer hosted at the network edge that is in charge of the semantic description of AI-embedded IoT devices, and, hence, it can expose as well as augment their cognitive capabilities in order to feed intelligent IoT applications. The proposal has been mainly devised with the twofold aim of (i) relieving the pressure on constrained devices that are solicited by multiple parties interested in accessing their generated data and inference, and (ii) and targeting interoperability among AI-powered platforms. A Proof-of-Concept (PoC) is provided to showcase the viability and advantages of the proposed solution.

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A low-cost wireless endoscope camera: a preliminary report

African Journal of Urology ◽

10.1186/s12301-021-00127-z ◽

2021 ◽

Vol 27 (1) ◽

Author(s):

J. M. Lazarus ◽

M. Ncube

Keyword(s):

Minimally Invasive Surgery ◽

Minimally Invasive ◽

Video Transmission ◽

Low Cost ◽

Battery Life ◽

Resource Constrained ◽

High Definition ◽

Industry Standard ◽

Constrained Environments ◽

The Cost

Abstract Background Technology currently used for surgical endoscopy was developed and is manufactured in high-income economies. The cost of this equipment makes technology transfer to resource constrained environments difficult. We aimed to design an affordable wireless endoscope to aid visualisation during rigid endoscopy and minimally invasive surgery (MIS). The initial prototype aimed to replicate a 4-mm lens used in rigid cystoscopy. Methods Focus was placed on using open-source resources to develop the wireless endoscope to significantly lower the cost and make the device accessible for resource-constrained settings. An off the shelf miniature single-board computer module was used because of its low cost (US$10) and its ability to handle high-definition (720p) video. Open-source Linux software made monitor mode (“hotspot”) wireless video transmission possible. A 1280 × 720 pixel high-definition tube camera was used to generate the video signal. Video is transmitted to a standard laptop computer for display. Bench testing included latency of wireless digital video transmission. Comparison to industry standard wired cameras was made including weight and cost. The battery life was also assessed. Results In comparison with industry standard cystoscope lens, wired camera, video processing unit and light source, the prototype costs substantially less. (US$ 230 vs 28 000). The prototype is light weight (184 g), has no cables tethering and has acceptable battery life (of over 2 h, using a 1200 mAh battery). The camera transmits video wirelessly in near real time with only imperceptible latency of < 200 ms. Image quality is high definition at 30 frames per second. Colour rendering is good, and white balancing is possible. Limitations include the lack of a zoom. Conclusion The novel wireless endoscope camera described here offers equivalent high-definition video at a markedly reduced cost to contemporary industry wired units and could contribute to making minimally invasive surgery possible in resource-constrained environments.

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Multi-Blockchain-Based IoT Data Processing Techniques to Ensure the Integrity of IoT Data in AIoT Edge Computing Environments

Sensors ◽

10.3390/s21103515 ◽

2021 ◽

Vol 21 (10) ◽

pp. 3515

Author(s):

Sung-Ho Sim ◽

Yoon-Su Jeong

Keyword(s):

Low Cost ◽

Third Party ◽

Monitoring And Control ◽

Constant Size ◽

Computing Environments ◽

Iot Devices ◽

Cloud Servers ◽

The Cost ◽

Processing Techniques ◽

And Control

As the development of IoT technologies has progressed rapidly recently, most IoT data are focused on monitoring and control to process IoT data, but the cost of collecting and linking various IoT data increases, requiring the ability to proactively integrate and analyze collected IoT data so that cloud servers (data centers) can process smartly. In this paper, we propose a blockchain-based IoT big data integrity verification technique to ensure the safety of the Third Party Auditor (TPA), which has a role in auditing the integrity of AIoT data. The proposed technique aims to minimize IoT information loss by multiple blockchain groupings of information and signature keys from IoT devices. The proposed technique allows IoT information to be effectively guaranteed the integrity of AIoT data by linking hash values designated as arbitrary, constant-size blocks with previous blocks in hierarchical chains. The proposed technique performs synchronization using location information between the central server and IoT devices to manage the cost of the integrity of IoT information at low cost. In order to easily control a large number of locations of IoT devices, we perform cross-distributed and blockchain linkage processing under constant rules to improve the load and throughput generated by IoT devices.

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An Efficient Container Management Scheme for Resource Constrained Intelligent IoT Devices

IEEE Internet of Things Journal ◽

10.1109/jiot.2020.3037181 ◽

2020 ◽

pp. 1-1

Author(s):

Prateek Chhikara ◽

Rajkumar Tekchandani ◽

Neeraj Kumar ◽

Mohammad S. Obaidat

Keyword(s):

Resource Constrained ◽

Management Scheme ◽

Container Management ◽

Iot Devices

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