Siddiqui Muhammad Yasir¹, Hyunsik Ahn^2,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1847-1861, 2023, DOI:10.32604/cmc.2023.035698

Abstract Deep learning has been constantly improving in recent years, and a significant number of researchers have devoted themselves to the research of defect detection algorithms. Detection and recognition of small and complex targets is still a problem that needs to be solved. The authors of this research would like to present an improved defect detection model for detecting small and complex defect targets in steel surfaces. During steel strip production, mechanical forces and environmental factors cause surface defects of the steel strip. Therefore, the detection of such defects is key to the production of high-quality products. Moreover, surface defects of… More >

Pradeep Kumar Singh¹, Pijush Kanti Dutta Pramanik¹, Madhumita Sardar¹, Anand Nayyar^2,3,*, Mehedi Masud⁴, Prasenjit Choudhury¹

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2827-2846, 2022, DOI:10.32604/cmc.2022.020437

Abstract A collaborative filtering-based recommendation system has been an integral part of e-commerce and e-servicing. To keep the recommendation systems reliable, authentic, and superior, the security of these systems is very crucial. Though the existing shilling attack detection methods in collaborative filtering are able to detect the standard attacks, in this paper, we prove that they fail to detect a new or unknown attack. We develop a new attack model, named Obscure attack, with unknown features and observed that it has been successful in biasing the overall top-N list of the target users as intended. The Obscure attack is able to… More >