Gang Long, Zhaoxin Zhang^*

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1667-1685, 2024, DOI:10.32604/cmc.2024.052082 - 15 October 2024

Abstract The secure and normal operation of distributed networks is crucial for accurate parameter estimation. However, distributed networks are frequently susceptible to Byzantine attacks. Considering real-life scenarios, this paper investigates a probability Byzantine (PB) attack, utilizing a Bernoulli distribution to simulate the attack probability. Historically, additional detection mechanisms are used to mitigate such attacks, leading to increased energy consumption and burdens on distributed nodes, consequently diminishing operational efficiency. Differing from these approaches, an adaptive updating distributed estimation algorithm is proposed to mitigate the impact of PB attacks. In the proposed algorithm, a penalty strategy is initially More >

P. Renukadevi^1,*, A. Rajiv Kannan²

Computer Systems Science and Engineering, Vol.44, No.1, pp. 629-645, 2023, DOI:10.32604/csse.2023.024217 - 01 June 2022

Abstract About 170 nations have been affected by the COvid VIrus Disease-19 (COVID-19) epidemic. On governing bodies across the globe, a lot of stress is created by COVID-19 as there is a continuous rise in patient count testing positive, and they feel challenging to tackle this situation. Most researchers concentrate on COVID-19 data analysis using the machine learning paradigm in these situations. In the previous works, Long Short-Term Memory (LSTM) was used to predict future COVID-19 cases. According to LSTM network data, the outbreak is expected to finish by June 2020. However, there is a chance… More >