KBC: Multiple Key Generation using Key Block Chaining

Prajapati, Payal; Chaudhari, Kinjal

doi:10.1016/j.procs.2020.03.224

Cited by 9 publications

(4 citation statements)

References 13 publications

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“…Authentication methods encompass various structures, one of which is the Cipher-based Message Authentication Code (CMAC). This technique relies on a strong cryptographic foundation, typically leveraging a block cipher like AES (Advanced Encryption Standard) operating in Cipher Block Chaining (CBC) mode [6], [7]. By utilizing a private secret key shared between the sender and recipient, CMAC processes fixed-size data blocks, potentially applying padding if the message size isn't a multiple of the block size.…”

Section: Related Workmentioning

confidence: 99%

Enhancing Security Mechanisms for IoT-Fog Networks

Mansour,

Sakhi,

Kzaz

et al. 2024

Journal of Robotics and Control

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This study contributes to improving Morocco's fish canning industry by integrating artificial intelligence (AI). The primary objective involves developing an AI and image processing-based system to monitor and guarantee canning process quality in the facility. It commenced with an IoT-enabled device capable of capturing and processing images, leading to the creation of an AI-driven system adept at accurately categorizing improperly crimped cans. Further advancements focused on reinforcing communication between IoT devices and servers housing individual client's neural network weights. These weights are vital, ensuring the functionality of our IoT device. The efficiency of the IoT device in categorizing cans relies on updated neural network weights from the Fog server, crucial for continual refinement and adaptation to diverse can shapes. Securing communication integrity between devices and the server is imperative to avoid disruptions in can classification, emphasizing the need for secure channels. In this paper, our key scientific contribution revolves around devising a security protocol founded on HMAC. This protocol guarantees authentication and preserves the integrity of neural network weights exchanged between Fog computing nodes and IoT devices. The innovative addition of a comprehensive dictionary within the Fog server significantly bolsters security measures, enhancing the overall safety between these interconnected entities.

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Section: Related Workmentioning

confidence: 99%

Enhancing Security Mechanisms for IoT-Fog Networks

Mansour,

Sakhi,

Kzaz

et al. 2024

Journal of Robotics and Control

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“…Christidis and Devetsikiotis (2016) observed that the utilization of resources, information sharing, practices of automation and privacy in data transfer can be improved by blockchain-enabled IoT system. The stochasticity, transparency, functionality, reliability and hardiness of a system can be improved with security and robustness by using blockchain (Parjapati and Chaudhari, 2020;Sund et al, 2020). Further, observing the current trends of issues from literature on the importance of blockchain technology in different sectors, the authors of current research paper are trying to find answer to following research question in coming sections of current research paper:…”

Section: Rq1 What Are the Dominance Challenges Of Iiot Implementation...mentioning

confidence: 99%

IIoT implementation challenges: analysis and mitigation by blockchain

Kumar

Sindhwani

Singh

2021

JGOSS

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Purpose The purpose of this methodology is to categorise the challenges into cause and effect group. The modern scenario of customization, personalization and multi-restrictive working because of pandemics has affected the operations of manufacturing small and medium enterprises (SMEs). In the new normal, the digitalization of manufacturing SMEs can be the path breaker. Modern digitalization includes a mix of technologies such as the industrial internet of things (IIoT), the internet of things, cyber-physical system and big data analytics. This digitalization can help in achieving new design changes, efficient production scheduling, smart manufacturing and unrestricted on-time delivery of quality products. This research paper aims to recognize and analyze the challenges faced while implementing IIoT technologies in manufacturing SMEs and tries to find the possibility of mitigating challenges by blockchain technology. Design/methodology/approach There were ten challenges of IIoT implementation identified from the literature review and experts’ opinions. To collect information from Indian manufacturing SMEs, a survey tool was formed in the form of a questionnaire. On the fundament of responses received from industrial experts, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique has been used for categorizing these challenges into cause and effect groups. Further, the authors tried to mitigate observed challenges with the help of blockchain technology. Findings With the implementation of IIoT technologies, the manufacturing processes become conciliatory, effective and traceable in real time. Observation of the current study states that the top effect group challenges such as the security of data and reliability of technologies can be mitigated by enabling blockchain technologies. The authors conclude that blockchain-enabled IIoT technologies will be highly beneficial for the Indian SMEs strategically and practically in the current scenario. Research limitations/implications Methodology of DEMATEL focuses on responses received from experts. The broader approach of survey from manufacturing organizations is compromised due to small sample size in this methodology. Experts approached for survey were from manufacturing SMEs of Delhi National Capital Region only. Broader survey-based techniques may be applied covering different sectors of SMEs in future work. Practical implications Technologies such as blockchain can facilitate advanced security in the application of IIoT and other such practices. While dealing with significant issues and challenges of new technologies, blockchain gives an edge of balance in the current scenario. Its properties of fixity, temper evident and circumvent fraud make this technology ideal for the digitalization of the manufacturing systems in SMEs. Originality/value Digitalization of manufacturing facilities is the need of the hour. Pandemic challenges have highlighted the urgency of it. This research will motivate and guide the manufacturing SMEs in planning strategies and long-term policies in implementing modern technologies and coping up with the pandemic challenges.

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“…The study provides evidence on the impact of political influence [25], data protection events [26], specific news and/or announcements [27], national policies [28], and other factors. The investigation through this angle is critical; likewise, the potential security perspectives on domains related to the monetary business sectors are urgent to keep up the integrity of the gathered data as well as their analysis [29,30]. In addition, it is important to understand the potential effects of several domains on financial market volatility.…”

Section: Related Workmentioning

confidence: 99%

Comparative Analysis of Recurrent Neural Networks in Stock Price Prediction for Different Frequency Domains

Dey¹,

Hossain²,

Hossain

et al. 2021

Algorithms

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Investors in the stock market have always been in search of novel and unique techniques so that they can successfully predict stock price movement and make a big profit. However, investors continue to look for improved and new techniques to beat the market instead of old and traditional ones. Therefore, researchers are continuously working to build novel techniques to supply the demand of investors. Different types of recurrent neural networks (RNN) are used in time series analyses, especially in stock price prediction. However, since not all stocks’ prices follow the same trend, a single model cannot be used to predict the movement of all types of stock’s price. Therefore, in this research we conducted a comparative analysis of three commonly used RNNs—simple RNN, Long Short Term Memory (LSTM), and Gated Recurrent Unit (GRU)—and analyzed their efficiency for stocks having different stock trends and various price ranges and for different time frequencies. We considered three companies’ datasets from 30 June 2000 to 21 July 2020. The stocks follow different trends of price movements, with price ranges of $30, $50, and $290 during this period. We also analyzed the performance for one-day, three-day, and five-day time intervals. We compared the performance of RNN, LSTM, and GRU in terms of R2 value, MAE, MAPE, and RMSE metrics. The results show that simple RNN is outperformed by LSTM and GRU because RNN is susceptible to vanishing gradient problems, while the other two models are not. Moreover, GRU produces lesser errors comparing to LSTM. It is also evident from the results that as the time intervals get smaller, the models produce lower errors and higher reliability.

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KBC: Multiple Key Generation using Key Block Chaining

Cited by 9 publications

References 13 publications

Enhancing Security Mechanisms for IoT-Fog Networks

Enhancing Security Mechanisms for IoT-Fog Networks

IIoT implementation challenges: analysis and mitigation by blockchain

Comparative Analysis of Recurrent Neural Networks in Stock Price Prediction for Different Frequency Domains

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