Mengxiao Wang^1,2, Jing Huang^1,2,*

Computer Systems Science and Engineering, Vol.47, No.1, pp. 1023-1042, 2023, DOI:10.32604/csse.2023.039569 - 26 May 2023

Abstract Due to the anonymity of blockchain, frequent security incidents and attacks occur through it, among which the Ponzi scheme smart contract is a classic type of fraud resulting in huge economic losses. Machine learning-based methods are believed to be promising for detecting ethereum Ponzi schemes. However, there are still some flaws in current research, e.g., insufficient feature extraction of Ponzi scheme smart contracts, without considering class imbalance. In addition, there is room for improvement in detection precision. Aiming at the above problems, this paper proposes an ethereum Ponzi scheme detection scheme through opcode context analysis… More >

Wang Ning^1,*, Siliang Chen^2,*, Fu Qiang², Haitao Tang², Shen Jie²

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5951-5965, 2023, DOI:10.32604/cmc.2023.035558 - 28 December 2022

Abstract With the popularity of online payment, how to perform credit card fraud detection more accurately has also become a hot issue. And with the emergence of the adaptive boosting algorithm (Adaboost), credit card fraud detection has started to use this method in large numbers, but the traditional Adaboost is prone to overfitting in the presence of noisy samples. Therefore, in order to alleviate this phenomenon, this paper proposes a new idea: using the number of consecutive sample misclassifications to determine the noisy samples, while constructing a penalty factor to reconstruct the sample weight assignment. Firstly,… More >

R. Sujatha¹, B. Venkata Siva Krishna¹, Jyotir Moy Chatterjee², P. Rahul Naidu¹, NZ Jhanjhi^3,*, Challa Charita¹, Eza Nerin Mariya¹, Mohammed Baz⁴

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 525-541, 2022, DOI:10.32604/iasc.2022.021216 - 26 October 2021

Abstract In the current times, COVID-19 has taken a handful of people’s lives. So, vaccination is crucial for everyone to avoid the spread of the disease. However, not every vaccine will be perfect or will get success for everyone. In the present work, we have analyzed the data from the Vaccine Adverse Event Reporting System and understood that the vaccines given to the people might or might not work considering certain demographic factors like age, gender, and multiple other variables like the state of living, etc. This variable is considered because it explains the unmentioned variables… More >

Sherif S. M. Ghoneim^1,*, Amr E. Rashed², Nagy I. Elkalashy¹

Intelligent Automation & Soft Computing, Vol.30, No.2, pp. 467-479, 2021, DOI:10.32604/iasc.2021.016681 - 11 August 2021

Abstract This study uses several artificial intelligence approaches to detect and estimate electrical faults in photovoltaic (PV) farms. The fault detection approaches of random forest, logistic regression, naive Bayes, AdaBoost, and CN2 rule induction were selected from a total of 12 techniques because they produced better decisions for fault detection. The proposed techniques were designed using distributed PV current measurements, plant current, plant voltage, and power. Temperature, radiation, and fault resistance were treated randomly. The proposed classification model was created using the Orange platform. A classification tree was visualized, consisting of seven nodes and four leaves,… More >