scholarly journals Approximate CPU Design for IoT End-Devices with Learning Capabilities

Electronics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 125 ◽  
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.

scholarly journals A Lightweight Cipher Based on Salsa20 for Resource-Constrained IoT Devices

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3326 ◽  
Author(s):  
Evangelina Lara ◽  
Leocundo Aguilar ◽  
Jesús García ◽  
Mauricio Sanchez
Keyword(s):  
Data Privacy ◽  
Negative Impact ◽  
Low Cost ◽  
Statistical Test ◽  
Resource Constrained ◽  
Data Memory ◽  
Iot Devices ◽  
Lightweight Cipher ◽  
The Internet Of Things ◽  
Test Suites

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.

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

Cybersecurity ◽  
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.

scholarly journals PRISEC: Comparison of Symmetric Key Algorithms for IoT Devices

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4312 ◽  
Author(s):  
Daniel A. F. Saraiva ◽  
Valderi Reis Quietinho Leithardt ◽  
Diandre de Paula ◽  
André Sales Mendes ◽  
Gabriel Villarrubia González ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Power Consumption ◽  
Advanced Encryption Standard ◽  
The Internet ◽  
Secure Communications ◽  
Resource Constrained ◽  
Symmetric Key ◽  
Iot Devices ◽  
Resource Constrained Devices ◽  
Constrained Devices

With the growing number of heterogeneous resource-constrained devices connected to the Internet, it becomes increasingly challenging to secure the privacy and protection of data. Strong but efficient cryptography solutions must be employed to deal with this problem, along with methods to standardize secure communications between these devices. The PRISEC module of the UbiPri middleware has this goal. In this work, we present the performance of the AES (Advanced Encryption Standard), RC6 (Rivest Cipher 6), Twofish, SPECK128, LEA, and ChaCha20-Poly1305 algorithms in Internet of Things (IoT) devices, measuring their execution times, throughput, and power consumption, with the main goal of determining which symmetric key ciphers are best to be applied in PRISEC. We verify that ChaCha20-Poly1305 is a very good option for resource constrained devices, along with the lightweight block ciphers SPECK128 and LEA.

scholarly journals The Wireless Solution to Realize Green IoT: Cellular Networks with Energy Efficient and Energy Harvesting Schemes

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 5875
Author(s):  
Yuan Ren ◽  
Xuewei Zhang ◽  
Guangyue Lu
Keyword(s):  
Energy Harvesting ◽  
Power Consumption ◽  
Real Time ◽  
Energy Efficient ◽  
Fog Computing ◽  
Random Access ◽  
Reducing Power ◽  
Effective Strategies ◽  
Iot Devices

With the tremendous increase of heterogeneous Internet of Things (IoT) devices and the different service requirements of these IoT applications, machine-type communication (MTC) has attracted considerable attention from both industry and academia. Owing to the prominent advantages of supporting pervasive connectivity and wide area coverage, the cellular network is advocated as the potential wireless solution to realize IoT deployment for MTC, and this creative network paradigm is called the cellular IoT (C-IoT). In this paper, we propose the three-layer structured C-IoT architecture for MTC and review the challenges for deploying green C-IoT. Then, effective strategies for realizing green C-IoT are presented, including the energy efficient and energy harvesting schemes. We put forward several strategies to make the C-IoT run in an energy-saving manner, such as efficient random access and barring mechanisms, self-adapting machine learning predictions, scheduling optimization, resource allocation, fog computing, and group-oriented transmission. As for the energy harvesting schemes, the ambient and dedicated energy harvesting strategies are investigated. Afterwards, we give a detailed case study, which shows the effectiveness of reducing power consumption for the proposed layered C-IoT architecture. Additionally, for real-time and non-real-time applications, the power consumption of different on-off states for MTC devices is discussed.

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

Sensors ◽  
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.

scholarly journals Power Efficient Random Access for Massive NB-IoT Connectivity

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4944 ◽  
Author(s):  
Mamta Agiwal ◽  
Mukesh Kumar Maheshwari ◽  
Hu Jin
Keyword(s):  
Power Consumption ◽  
Average Power ◽  
Power Saving ◽  
Random Access ◽  
Reducing Power ◽  
Low Complexity ◽  
Power Efficient ◽  
Average Power Consumption ◽  
Channel Conditions ◽  
Iot Devices

Sensors enabled Internet of things (IoT) has become an integral part of the modern, digital and connected ecosystem. Narrowband IoT (NB-IoT) technology is one of its economical versions preferable when low power and resource limited sensors based applications are considered. One of the major characteristics of NB-IoT technology is its offer of reliable coverage enhancement (CE) which is achieved by repeating the transmission of signals. This repeated transmission of the same signal challenges power saving in low complexity NB-IoT devices. Additionally, the NB-IoT devices are expected to suffer from congestion due to simultaneous random access procedures (RAPs) from an enormous number of devices. Multiple RAP reattempts would further reduce the power saving in NB-IoT devices. We propose a novel power efficient RAP (PE-RAP) for reducing power consumption of NB-IoT devices in a highly congested environment. The existing RAP do not differentiate the failures due to poor channel conditions or due to collision. After the RAP failure either due to collision or poor channel, the devices can apply power ramping or can transit to a higher CE level with higher repetition configuration. In the proposed PE-RAP, the NB-IoT devices can re-ascertain the channel conditions after an RAP attempt failure such that the impediments due to poor channel are reduced. The power increments and repetition enhancements are applied only when necessary. We probabilistically obtain the chances of RAP reattempts. Subsequently, we evaluate the average power consumption by devices in different CE levels for different repetition configurations. We validate our analysis by simulation studies.

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

Electronics ◽  
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.

scholarly journals The Hardware Design and Implementation of a Key Exchange Protocol for Low-cost IoT Devices

2019 ◽  
Vol 8 (2S6) ◽  
pp. 79-85
Keyword(s):  
Power Consumption ◽  
Low Cost ◽  
Logic Gates ◽  
Public Key Cryptography ◽  
Key Exchange ◽  
Public Key ◽  
Key Exchange Protocol ◽  
General Data Protection Regulation ◽  
Processor Core ◽  
Iot Devices

The General Data Protection Regulation (GDPR) which was enforced in May 2018 clearly stated that the protection of data by organizations is a mandatory task. Protecting or securing data on data collecting and sensing devices used in the Internet-of-Things (IoT) platform is a challenge for the fact that the devices are resource-constrained in terms of operation frequency, hardware area, computational complexity, and power consumption. The first step to securing data on low-cost IoT devices is to generate keys for subsequent encryption and authentication. This paper, therefore, proposes and implements a lightweight key exchange protocol with the capability of authenticating the generated key without the need for public-key cryptography. The protocol is meant to be simple and make use of minimal hardware resources. It uses components such as the pseudorandom number and bit generators, dot product, XOR gates, shift registers and basic logic gates making it very resource-efficient. The hardware architecture of the protocol was implemented using Verilog Hardware Description Language (HDL) and synthesized using Xilinx ISE 14.7 software which includes XPower Analyzer for power estimation. The protocol was tested on a Field Programmable Gate Array (FPGA) board with a synthesizable Reduced Instruction Set Computer Five (RISC-V) processor core. The synthesis and simulation results which include area, maximum frequency, latency, and power consumption show that the protocol is suitable for IoT low-cost devices as compared to standard public-key primitives.

scholarly journals ReliefE: feature ranking in high-dimensional spaces via manifold embeddings

2021 ◽  
Author(s):  
Blaž Škrlj ◽  
Sašo Džeroski ◽  
Nada Lavrač ◽  
Matej Petković
Keyword(s):  
Sparse Matrix ◽  
Real Life ◽  
High Dimensional ◽  
Feature Ranking ◽  
Data Sets ◽  
Data Set ◽  
Learning Capabilities ◽  
Machine Learning Applications ◽  
High Utility ◽  
Low Dimensional

AbstractFeature ranking has been widely adopted in machine learning applications such as high-throughput biology and social sciences. The approaches of the popular Relief family of algorithms assign importances to features by iteratively accounting for nearest relevant and irrelevant instances. Despite their high utility, these algorithms can be computationally expensive and not-well suited for high-dimensional sparse input spaces. In contrast, recent embedding-based methods learn compact, low-dimensional representations, potentially facilitating down-stream learning capabilities of conventional learners. This paper explores how the Relief branch of algorithms can be adapted to benefit from (Riemannian) manifold-based embeddings of instance and target spaces, where a given embedding’s dimensionality is intrinsic to the dimensionality of the considered data set. The developed ReliefE algorithm is faster and can result in better feature rankings, as shown by our evaluation on 20 real-life data sets for multi-class and multi-label classification tasks. The utility of ReliefE for high-dimensional data sets is ensured by its implementation that utilizes sparse matrix algebraic operations. Finally, the relation of ReliefE to other ranking algorithms is studied via the Fuzzy Jaccard Index.

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