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All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control)
Nowshad Amin
Universiti Tenaga Nasional
Computer Science & IT Electrical & Electronics Engineering

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Forecasting number of vulnerabilities using long short-term neural memory network Mohammad Shamsul Hoque; Norziana Jamil; Nowshad Amin; Azril Azam Abdul Rahim; Razali B. Jidin
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4381-4391

Abstract

Cyber-attacks are launched through the exploitation of some existing vulnerabilities in the software, hardware, system and/or network. Machine learning algorithms can be used to forecast the number of post release vulnerabilities. Traditional neural networks work like a black box approach; hence it is unclear how reasoning is used in utilizing past data points in inferring the subsequent data points. However, the long short-term memory network (LSTM), a variant of the recurrent neural network, is able to address this limitation by introducing a lot of loops in its network to retain and utilize past data points for future calculations. Moving on from the previous finding, we further enhance the results to predict the number of vulnerabilities by developing a time series-based sequential model using a long short-term memory neural network. Specifically, this study developed a supervised machine learning based on the non-linear sequential time series forecasting model with a long short-term memory neural network to predict the number of vulnerabilities for three vendors having the highest number of vulnerabilities published in the national vulnerability database (NVD), namely microsoft, IBM and oracle. Our proposed model outperforms the existing models with a prediction result root mean squared error (RMSE) of as low as 0.072.
Salsa20 based lightweight security scheme for smart meter communication in smart grid S. M. Salim Reza; Md Murshedul Arifeen; Sieh Kiong Tiong; Md Akhteruzzaman; Nowshad Amin; Mohammad Shakeri; Afida Ayob; Aini Hussain
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 1: February 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i1.14798

Abstract

The traditional power gird is altering dramatically to a smart power grid with the escalating development of information and communication technology (ICT). Among thousands of electronic devices connected to the grid through communication network, smart meter (SM) is the core networking device. The consolidation of ICT to the electronic devices centered on SM open loophole for the adversaries to launch cyber-attack. Therefore, for protecting the network from the adversaries it is required to design lightweight security mechanism for SM, as conventional cryptography schemes poses extensive computational cost, processing delay and overhead which is not suitable to be used in SM. In this paper, we have proposed a security mechanism consolidating elliptic curve cryptography (ECC) and Salsa20 stream cipher algorithm to ensure security of the network as well as addressing the problem of energy efficiency and lightweight security solution. We have numerically analyzed the performance of our proposed scheme in case of energy efficiency and processing time which reveals that the suggested mechanism is suitable to be used in SM as it consumes less power and requires less processing time to encrypt or decrypt.
Co-Authors Afida Ayob Aini Hussain Azril Azam Abdul Rahim Md Akhteruzzaman Md Murshedul Arifeen Mohammad Shakeri Mohammad Shamsul Hoque Norziana Jamil Razali B. Jidin S. M. Salim Reza Sieh Kiong Tiong