scholarly journals A Practical and Efficient Node Blind SignCryption Scheme for the IoT Device Network

2021 ◽  
Vol 12 (1) ◽  
pp. 278
Author(s):  
Ming-Te Chen ◽  
Hsuan-Chao Huang
Keyword(s):  
Data Privacy ◽  
Computation Time ◽  
Limited Resource ◽  
Memory Space ◽  
Resource Limitations ◽  
Smart Glasses ◽  
Smart Watch ◽  
Cloud Server ◽  
Iot Devices ◽  
Resource Conditions

In recent years, Internet of Things (IoT for short) research has become one of the top ten most popular research topics. IoT devices also embed many sensing chips for detecting physical signals from the outside environment. In the wireless sensing network (WSN for short), a human can wear several IoT devices around her/his body such as a smart watch, smart band, smart glasses, etc. These IoT devices can collect analog environment data around the user’s body and store these data into memory after data processing. Thus far, we have discovered that some IoT devices have resource limitations such as power shortages or insufficient memory for data computation and preservation. An IoT device such as a smart band attempts to upload a user’s body information to the cloud server by adopting the public-key crypto-system to generate the corresponding cipher-text and related signature for concrete data security; in this situation, the computation time increases linearly and the device can run out of memory, which is inconvenient for users. For this reason, we consider that, if the smart IoT device can perform encryption and signature simultaneously, it can save significant resources for the execution of other applications. As a result, our approach is to design an efficient, practical, and lightweight, blind sign-cryption (SC for short) scheme for IoT device usage. Not only can our methodology offer the sensed data privacy protection efficiently, but it is also fit for the above application scenario with limited resource conditions such as battery shortage or less memory space in the IoT device network.

LeaD: Learn to Decode Vibration-based Communication for Intelligent Internet of Things

2021 ◽  
Vol 17 (3) ◽  
pp. 1-25
Author(s):  
Guangrong Zhao ◽  
Bowen Du ◽  
Yiran Shen ◽  
Zhenyu Lao ◽  
Lizhen Cui ◽  
...  
Keyword(s):  
Machine Learning ◽  
Transmission Rate ◽  
Low Cost ◽  
Communication Protocols ◽  
Computation Time ◽  
Classification Problem ◽  
Smart Devices ◽  
Smart Watch ◽  
Iot Devices ◽  
Short Messages

In this article, we propose, LeaD , a new vibration-based communication protocol to Lea rn the unique patterns of vibration to D ecode the short messages transmitted to smart IoT devices. Unlike the existing vibration-based communication protocols that decode the short messages symbol-wise, either in binary or multi-ary, the message recipient in LeaD receives vibration signals corresponding to bits-groups. Each group consists of multiple symbols sent in a burst and the receiver decodes the group of symbols as a whole via machine learning-based approach. The fundamental behind LeaD is different combinations of symbols (1 s or 0 s) in a group will produce unique and reproducible patterns of vibration. Therefore, decoding in vibration-based communication can be modeled as a pattern classification problem. We design and implement a number of different machine learning models as the core engine of the decoding algorithm of LeaD to learn and recognize the vibration patterns. Through the intensive evaluations on large amount of datasets collected, the Convolutional Neural Network (CNN)-based model achieves the highest accuracy of decoding (i.e., lowest error rate), which is up to 97% at relatively high bits rate of 40 bits/s. While its competing vibration-based communication protocols can only achieve transmission rate of 10 bits/s and 20 bits/s with similar decoding accuracy. Furthermore, we evaluate its performance under different challenging practical settings and the results show that LeaD with CNN engine is robust to poses, distances (within valid range), and types of devices, therefore, a CNN model can be generally trained beforehand and widely applicable for different IoT devices under different circumstances. Finally, we implement LeaD on both off-the-shelf smartphone and smart watch to measure the detailed resources consumption on smart devices. The computation time and energy consumption of its different components show that LeaD is lightweight and can run in situ on low-cost smart IoT devices, e.g., smartwatches, without accumulated delay and introduces only marginal system overhead.

scholarly journals New Authentication Algorithm Based on Verifiable Encryption with Digital Identity

Cryptography ◽  
2019 ◽  
Vol 3 (3) ◽  
pp. 19 ◽  
Author(s):  
Maki Kihara ◽  
Satoshi Iriyama
Keyword(s):  
Internet Of Things ◽  
Computation Time ◽  
Key Distribution ◽  
Digital Identity ◽  
Encrypted Data ◽  
Private Data ◽  
Cloud Server ◽  
Secret Keys ◽  
Iot Devices ◽  
Verifiable Encryption

We propose a new authentication algorithm for small internet of things (IoT) devices without key distribution and secure servers. Encrypted private data are stored on the cloud server in the registration step and compared with incoming encrypted data without decryption in the verification step. We call a set of encryptions that can verify two encrypted data items without decryption a verifiable encryption (VE). In this paper, we define VE, and claim that several cryptosystems belong to the VE class. Moreover, we introduce an authentication algorithm based on VE, and show an example of the algorithm and discuss its performance and security. As the algorithm neither shares any secret keys nor decrypts, its computation time becomes very small.

scholarly journals Practical Cross-Layer Radio Frequency-Based Authentication Scheme for Internet of Things

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4034
Author(s):  
Arie Haenel ◽  
Yoram Haddad ◽  
Maryline Laurent ◽  
Zonghua Zhang
Keyword(s):  
Internet Of Things ◽  
Radio Frequency ◽  
Real Life ◽  
Computation Time ◽  
Cost Effective ◽  
Battery Life ◽  
Cross Layer ◽  
Security Level ◽  
Cost Of Energy ◽  
Iot Devices

The Internet of Things world is in need of practical solutions for its security. Existing security mechanisms for IoT are mostly not implemented due to complexity, budget, and energy-saving issues. This is especially true for IoT devices that are battery powered, and they should be cost effective to be deployed extensively in the field. In this work, we propose a new cross-layer approach combining existing authentication protocols and existing Physical Layer Radio Frequency Fingerprinting technologies to provide hybrid authentication mechanisms that are practically proved efficient in the field. Even though several Radio Frequency Fingerprinting methods have been proposed so far, as a support for multi-factor authentication or even on their own, practical solutions are still a challenge. The accuracy results achieved with even the best systems using expensive equipment are still not sufficient on real-life systems. Our approach proposes a hybrid protocol that can save energy and computation time on the IoT devices side, proportionally to the accuracy of the Radio Frequency Fingerprinting used, which has a measurable benefit while keeping an acceptable security level. We implemented a full system operating in real time and achieved an accuracy of 99.8% for the additional cost of energy, leading to a decrease of only ~20% in battery life.

Efficient Electromagnetic Analysis of a Dispersive Head Model Due to Smart Glasses Embedded Antennas at Wi-Fi and 5G Frequencies

2021 ◽  
Vol 36 (2) ◽  
pp. 159-167
Author(s):  
Fatih Kaburcuk ◽  
Atef Elsherbeni
Keyword(s):  
Numerical Study ◽  
Computation Time ◽  
Human Head ◽  
Head Model ◽  
Computer Memory ◽  
Large Computer ◽  
Smart Glasses ◽  
Embedded Antennas ◽  
Human Head Model ◽  
Difference Time

Numerical study of electromagnetic interaction between an adjacent antenna and a human head model requires long computation time and large computer memory. In this paper, two speeding up techniques for a dispersive algorithm based on finite-difference time-domain method are used to reduce the required computation time and computer memory. In order to evaluate the validity of these two speeding up techniques, specific absorption rate (SAR) and temperature rise distributions in a dispersive human head model due to radiation from an antenna integrated into a pair of smart glasses are investigated. The antenna integrated into the pair of smart glasses have wireless connectivity at 2.4 GHz and 5th generation (5G) cellular connectivity at 4.9 GHz. Two different positions for the antenna integrated into the frame are considered in this investigation. These techniques provide remarkable reduction in computation time and computer memory.

Provably Secure Authentication Approach for Data Security in Cloud Using Hashing, Encryption, and Chebyshev-Based Authentication

2022 ◽  
Vol 16 (1) ◽  
pp. 0-0
Keyword(s):  
Data Security ◽  
Security Analysis ◽  
Data Communication ◽  
Computation Time ◽  
Computational Time ◽  
Security Issues ◽  
Authentication Mechanism ◽  
Cloud Server ◽  
Secure Authentication ◽  
Provably Secure

Secure and efficient authentication mechanism becomes a major concern in cloud computing due to the data sharing among cloud server and user through internet. This paper proposed an efficient Hashing, Encryption and Chebyshev HEC-based authentication in order to provide security among data communication. With the formal and the informal security analysis, it has been demonstrated that the proposed HEC-based authentication approach provides data security more efficiently in cloud. The proposed approach amplifies the security issues and ensures the privacy and data security to the cloud user. Moreover, the proposed HEC-based authentication approach makes the system more robust and secured and has been verified with multiple scenarios. However, the proposed authentication approach requires less computational time and memory than the existing authentication techniques. The performance revealed by the proposed HEC-based authentication approach is measured in terms of computation time and memory as 26ms, and 1878bytes for 100Kb data size, respectively.

scholarly journals Text File Privacy on the Cloud Based on Diagonal Fragmentation and Encryption

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Tawfiq Barhoom ◽  
Mahmoud Abu Shawish
Keyword(s):  
Data Privacy ◽  
Cloud Services ◽  
Text File ◽  
Layer Model ◽  
Encrypted Data ◽  
Cloud Server ◽  
Cloud Environments ◽  
Encryption Algorithms ◽  
Well Data ◽  
Encryption Method

Despite the growing reliance on cloud services and software, privacy is somewhat difficult. We store our data on remote servers in cloud environments that are untrusted. If we do not handle the stored data well, data privacy can be violated with no awareness on our part. Although it requires expensive computation, encrypting the data before sending it appears to be a solution to this problem. So far, all known solutions to protect textual files using encryption algorithms fell short of privacy expectations. Thus is because encrypting cannot stand by itself. The encrypted data on the cloud server becomes full file in the hand causing the privacy of this data to be intrusion-prone, thus allowing intruders to access the file data once they can decrypt it. This study aimed to develop an effective cloud confidentiality model based on combining fragmentation and encryption of text files to compensate for reported deficiency in encryption methods. The fragmentation method used the strategy of dividing text files into two triangles through the axis. Whereas the encryption method used the Blowfish algorithm. The research concluded that high confidentiality is achieved by building a multi-layer model: encryption, chunk, and fragmentation of every chunk to prevent intruders from reaching the data even if they were able to decrypt the file. Using the privacy accuracy equation (developed for the purpose in this research), the model achieved accuracy levels of 96% and 90% when using 100 and 200 words in each chunk on small, medium, and large files respectively.

scholarly journals Distributed Architecture for an Integrated Development Environment, Large Trace Analysis, and Visualization

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5560
Author(s):  
Yonni Chen Kuang Piao ◽  
Naser Ezzati-jivan ◽  
Michel R. Dagenais
Keyword(s):  
Programming Languages ◽  
Trace Analysis ◽  
Development Environment ◽  
Integrated Development ◽  
Resource Limitations ◽  
Execution Traces ◽  
Integrated Development Environments ◽  
Visualization Tools ◽  
Iot Devices ◽  
Server Architecture

Integrated development environments (IDEs) provide many useful tools such as a code editor, a compiler, and a debugger for creating software. These tools are highly sophisticated, and their development requires a significant effort. Traditionally, an IDE supports different programming languages via plugins that are not usually reusable in other IDEs. Given the high complexity and constant evolution of popular programming languages, such as C++ and even Java, the effort to update those plugins has become unbearable. Thus, recent work aims to modularize IDEs and reuse the existing parser implementation directly in compilers. However, when IDE debugging tools are insufficient at detecting performance defects in large and multithreaded systems, developers must use tracing and trace visualization tools in their software development process. Those tools are often standalone applications and do not interoperate with the new modular IDEs, thus losing the power and the benefits of many features provided by the IDE. The structure and use cases of tracing tools, with the potentially massive execution traces, significantly differ from the other tools in IDEs. Thus, it is a considerable challenge, one which has not been addressed previously, to integrate them into the new modular IDEs. In this paper, we propose an efficient modular client–server architecture for trace analysis and visualization that solves those problems. The proposed architecture is well suited for performance analysis on Internet of Things (IoT) devices, where resource limitations often prohibit data collection, processing, and visualization all on the same device. The experimental evaluation demonstrated that our proposed flexible and reusable solution is scalable and has a small acceptable performance overhead compared to the standalone approach.

Distributed Ledger Technology based Property Transaction System with Support for IoT Devices

2021 ◽  
pp. 299-319
Author(s):  
Nikita Singh ◽  
Manu Vardhan
Keyword(s):  
Network Bandwidth ◽  
Remote Locations ◽  
Distributed Ledger ◽  
Distributed Ledger Technology ◽  
Cloud Server ◽  
Operational Models ◽  
Property Registration ◽  
Iot Devices ◽  
Financial Transactions ◽  
Server Architecture

Blockchain-based distributed ledger technology (DLT) is transforming the existing operational models of economy, financial transactions and other government machineries so as to allow these to operate in a much more secure and decentralized manner. This research focuses on providing framework for decentralized and secure P2P infrastructure for handling e-stamp and property registration mechanism along with interface for verification of document originality. The proposed efficient consensus mechanism reduces the overhead of broadcasting a new block by more than 50% coupled with saving CPU computation power along with network bandwidth. To ensure that even people at remote locations with constrained resources are able to participate and harness these benefits, a cloud server architecture & web interface for verification of property registered deed is also proposed.

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