scholarly journals BFLP: An Adaptive Federated Learning Framework for Internet of Vehicles

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Yongqiang Peng ◽  
Zongyao Chen ◽  
Zexuan Chen ◽  
Wei Ou ◽  
Wenbao Han ◽  
...  
Keyword(s):  
Privacy Preservation ◽  
Human Beings ◽  
Computing Power ◽  
Internet Of Vehicles ◽  
Learning Framework ◽  
Actual Application ◽  
Vehicle Systems ◽  
Learning Technique ◽  
Encryption Algorithms ◽  
Lightweight Encryption

Applications of Internet of Vehicles (IoV) make the life of human beings more intelligent and convenient. However, in the present, there are some problems in IoV, such as data silos and poor privacy preservation. To address the challenges in IoV, we propose a blockchain-based federated learning pool (BFLP) framework. BFLP allows the models to be trained without sharing raw data, and it can choose the most suitable federated learning method according to actual application scenarios. Considering the poor computing power of vehicle systems, we construct a lightweight encryption algorithm called CPC to protect privacy. To verify the proposed framework, we conducted experiments in obstacle-avoiding and traffic forecast scenarios. The results show that the proposed framework can effectively protect the user's privacy, and it is more stable and efficient compared with traditional machine learning technique. Also, we compare the CPC algorithm with other encryption algorithms. And the results show that its calculation cost is much lower compared to other symmetric encryption algorithms.

LIGHTWEIGHT CRYPTOGRAPHIC ALGORITHM IMPLEMENTATION IN A MICROCONTROLLER SYSTEM

2021 ◽  
Vol 17 (1) ◽  
pp. 260-264
Author(s):  
Alexandru VULPE ◽  
Raluca ANDREI ◽  
Alexandru BRUMARU ◽  
Octavian FRATU
Keyword(s):  
The Internet ◽  
Continuous Increase ◽  
Security Issues ◽  
Cryptographic Algorithm ◽  
Physical Limitations ◽  
Encryption Algorithms ◽  
Iot Devices ◽  
The Cost ◽  
Algorithm Implementation ◽  
Lightweight Encryption

Abstract: With the development of mobile devices and the advent of smartphones, the Internet has become part of everyday life. Any category of information about weather, flight schedule, etc. it is just a click away from the keyboard. This availability of data has led to a continuous increase in connectivity between devices, from any corner of the world. Combining device connectivity with systems automation allows the collection of information, its analysis and implicitly decision-making on the basis of information. Their introduction and continued expansion of devices that communicate in networks (including the Internet) have made security issues very important devices as well as for users. One of the main methodologies that ensures data confidentiality is encryption, which protects data from unauthorized access, but at the cost of using extensive mathematical models. Due to the nature of IoT devices, the resources allocated to a device can be constrained by certain factors, some of which are related to costs and others to the physical limitations of the device. Ensuring the confidentiality of data requires the use of encryption algorithms for these interconnected devices, which provide protection while maintaining the operation of that device. The need for these types of algorithms has created conditions for the growth and development of the concept of lightweight encryption, which aim to find encryption systems that can be implemented on these categories of devices, with limited hardware and software requirements. The paper proposes a lightweight cryptographic algorithm implemented on a microcontroller system, comparing its performances with those of the already existing system (based on x86).

scholarly journals A study secure multi authentication based data classification model in cloud based system

2020 ◽  
Vol 9 (3) ◽  
pp. 240
Author(s):  
Sakshi Kaushal ◽  
Bala Buksh
Keyword(s):  
Machine Learning ◽  
Cloud Computing ◽  
Data Classification ◽  
Classification Model ◽  
Sensitive Data ◽  
Learning Technique ◽  
Mathematical Algorithms ◽  
Encryption Algorithms ◽  
Cloud Applications ◽  
Technology Resources

Cloud computing is the most popular term among enterprises and news. The concepts come true because of fast internet bandwidth and advanced cooperation technology. Resources on the cloud can be accessed through internet without self built infrastructure. Cloud computing is effectively manage the security in the cloud applications. Data classification is a machine learning technique used to predict the class of the unclassified data. Data mining uses different tools to know the unknown, valid patterns and relationships in the dataset. These tools are mathematical algorithms, statistical models and Machine Learning (ML) algorithms. In this paper author uses improved Bayesian technique to classify the data and encrypt the sensitive data using hybrid stagnography. The encrypted and non encrypted sensitive data is sent to cloud environment and evaluate the parameters with different encryption algorithms.

A Lightweight Authentication and Encryption Protocol for Secure Communications Between Resource-Limited Devices Without Hardware Modification

2018 ◽  
pp. 1-46
Author(s):  
Piotr Ksiazak ◽  
William Farrelly ◽  
Kevin Curran
Keyword(s):  
Ubiquitous Computing ◽  
Secure Communications ◽  
Wireless Devices ◽  
Authentication Protocols ◽  
It Industry ◽  
Processing Power ◽  
Resource Limited ◽  
Encryption Algorithms ◽  
Lightweight Authentication ◽  
Lightweight Encryption

In this chapter, the authors examine the theoretical context for the security of wireless communication between ubiquitous computing devices and present an implementation that addresses this need. The number of resource-limited wireless devices utilized in many areas of the IT industry is growing rapidly. Some of the applications of these devices pose real security threats that can be addressed using authentication and cryptography. Many of the available authentication and encryption software solutions are predicated on the availability of ample processing power and memory. These demands cannot be met by most ubiquitous computing devices; thus, there is a need to apply lightweight cryptography primitives and lightweight authentication protocols that meet these demands in any application of security to devices with limited resources. The analysis of the lightweight solutions is divided into lightweight authentication protocols and lightweight encryption algorithms. The authors present a prototype running on the nRF9E5 microcontroller that provides necessary authentication and encryption on resource-limited devices.

IOTs

2021 ◽  
pp. 131-147
Author(s):  
N. Raghavendra Rao
Keyword(s):  
Information Technology ◽  
Cloud Computing ◽  
Internet Of Things ◽  
The Internet ◽  
Human Beings ◽  
Computing Power ◽  
Telecommunication Technology ◽  
Information And Communication ◽  
Ubiquitous And Pervasive Computing ◽  
Made In

Information technology has advanced by delivering an exponential increase in computing power. Telecommunication technology has likewise advanced communicating capabilities. Convergence of these two technologies has become possible due to the rapid advancements made in the respective technology. This convergence is termed as information and communication technology as a discipline. Many concepts are emerging in this discipline. These concepts enable business, government, and human beings to reach new realities in their required activities. Some of these concepts have created various opportunities for designing and manufacturing electronic devices. When these devices are connected to other devices and systems over the internet, this is now known as internet of things (IoT). This chapter gives a brief overview of the concepts such as cloud computing and ubiquitous and pervasive computing in the context of internet of things. Further, this chapter discusses five case illustrations with the relevance of internet of things.

scholarly journals A Survey of IoT Security Based on a Layered Architecture of Sensing and Data Analysis

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3625 ◽  
Author(s):  
Hichem Mrabet ◽  
Sana Belguith ◽  
Adeeb Alhomoud ◽  
Abderrazak Jemai
Keyword(s):  
Machine Learning Algorithms ◽  
Cloud Services ◽  
Transport Layer ◽  
Security Threats ◽  
Application Layer ◽  
Research Issues ◽  
Layered Architecture ◽  
Survey Paper ◽  
Encryption Algorithms ◽  
Lightweight Encryption

The Internet of Things (IoT) is leading today’s digital transformation. Relying on a combination of technologies, protocols, and devices such as wireless sensors and newly developed wearable and implanted sensors, IoT is changing every aspect of daily life, especially recent applications in digital healthcare. IoT incorporates various kinds of hardware, communication protocols, and services. This IoT diversity can be viewed as a double-edged sword that provides comfort to users but can lead also to a large number of security threats and attacks. In this survey paper, a new compacted and optimized architecture for IoT is proposed based on five layers. Likewise, we propose a new classification of security threats and attacks based on new IoT architecture. The IoT architecture involves a physical perception layer, a network and protocol layer, a transport layer, an application layer, and a data and cloud services layer. First, the physical sensing layer incorporates the basic hardware used by IoT. Second, we highlight the various network and protocol technologies employed by IoT, and review the security threats and solutions. Transport protocols are exhibited and the security threats against them are discussed while providing common solutions. Then, the application layer involves application protocols and lightweight encryption algorithms for IoT. Finally, in the data and cloud services layer, the main important security features of IoT cloud platforms are addressed, involving confidentiality, integrity, authorization, authentication, and encryption protocols. The paper is concluded by presenting the open research issues and future directions towards securing IoT, including the lack of standardized lightweight encryption algorithms, the use of machine-learning algorithms to enhance security and the related challenges, the use of Blockchain to address security challenges in IoT, and the implications of IoT deployment in 5G and beyond.

FBIA: A Fog-Based Identity Authentication Scheme for Privacy Preservation in Internet of Vehicles

2020 ◽  
Vol 69 (5) ◽  
pp. 5403-5415
Author(s):  
Liangjun Song ◽  
Gang Sun ◽  
Hongfang Yu ◽  
Xiaojiang Du ◽  
Mohsen Guizani
Keyword(s):  
Privacy Preservation ◽  
Identity Authentication ◽  
Authentication Scheme ◽  
Internet Of Vehicles

scholarly journals Application of a Lightweight Encryption Algorithm to a Quantized Speech Image for Secure IoT

2018 ◽  
Author(s):  
Mourad Talbi ◽  
Med Salim Bouhalel
Keyword(s):  
Internet Of Things ◽  
Data Security ◽  
Speech Signal ◽  
Block Cipher ◽  
Encryption Algorithm ◽  
Encryption Algorithms ◽  
Computationally Expensive ◽  
Complex Algorithm ◽  
Lightweight Encryption ◽  
Image Simulations

The IoT Internet of Things being a promising technology of the future. It is expected to connect billions of devices. The increased communication number is expected to generate data mountain and the data security can be a threat. The devices in the architecture are fundamentally smaller in size and low powered. In general, classical encryption algorithms are computationally expensive and this due to their complexity and needs numerous rounds for encrypting, basically wasting the constrained energy of the gadgets. Less complex algorithm, though, may compromise the desired integrity. In this paper we apply a lightweight encryption algorithm named as Secure IoT (SIT) to a quantized speech image for Secure IoT. It is a 64-bit block cipher and requires 64-bit key to encrypt the data. This quantized speech image is constructed by first quantizing a speech signal and then splitting the quantized signal into frames. Then each of these frames is transposed for obtaining the different columns of this quantized speech image. Simulations result shows the algorithm provides substantial security in just five encryption rounds.

scholarly journals A Traffic-Aware Federated Imitation Learning Framework for Motion Control at Unsignalized Intersections with Internet of Vehicles

Electronics ◽  
2021 ◽  
Vol 10 (24) ◽  
pp. 3050
Author(s):  
Tianhao Wu ◽  
Mingzhi Jiang ◽  
Yinhui Han ◽  
Zheng Yuan ◽  
Xinhang Li ◽  
...  
Keyword(s):  
Motion Control ◽  
Imitation Learning ◽  
Selection Strategy ◽  
Communication Overhead ◽  
Model Interaction ◽  
Internet Of Vehicles ◽  
Traffic Lights ◽  
Learning Framework ◽  
Unsignalized Intersections ◽  
Control Optimization

The wealth of data and the enhanced computation capabilities of Internet of Vehicles (IoV) enable the optimized motion control of vehicles passing through an intersection without traffic lights. However, more intersections and demands for privacy protection pose new challenges to motion control optimization. Federated Learning (FL) can protect privacy via model interaction in IoV, but traditional FL methods hardly deal with the transportation issue. To address the aforementioned issue, this study proposes a Traffic-Aware Federated Imitation learning framework for Motion Control (TAFI-MC), consisting of Vehicle Interactors (VIs), Edge Trainers (ETs), and a Cloud Aggregator (CA). An Imitation Learning (IL) algorithm is integrated into TAFI-MC to improve motion control. Furthermore, a loss-aware experience selection strategy is explored to reduce communication overhead between ETs and VIs. The experimental results show that the proposed TAFI-MC outperforms imitated rules in the respect of collision avoidance and driving comfort, and the experience selection strategy can reduce communication overheads while ensuring convergence.

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