Zhiguo Chen^1,*, Xiaorui Zhang^1,2, Sungryul Kim³

Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 891-908, 2021, DOI:10.32604/iasc.2021.016933

Abstract The rapid growth of malware poses a significant threat to the security of computer systems. Analysts now need to examine thousands of malware samples daily. It has become a challenging task to determine whether a program is a benign program or malware. Making accurate decisions about the program is crucial for anti-malware products. Precise malware detection techniques have become a popular issue in computer security. Traditional malware detection uses signature-based strategies, which are the most widespread method used in commercial anti-malware software. This method works well against known malware but cannot detect new malware. To overcome the deficiency of the… More >

Luis-Eduardo Bautista-Villalpando^1,*, Alain Abran²

Computer Systems Science and Engineering, Vol.37, No.2, pp. 203-218, 2021, DOI:10.32604/csse.2021.015437

Abstract Cyberattacks are difficult to prevent because the targeted companies and organizations are often relying on new and fundamentally insecure cloud-based technologies, such as the Internet of Things. With increasing industry adoption and migration of traditional computing services to the cloud, one of the main challenges in cybersecurity is to provide mechanisms to secure these technologies. This work proposes a Data Security Framework for cloud computing services (CCS) that evaluates and improves CCS data security from a software engineering perspective by evaluating the levels of security within the cloud computing paradigm using engineering methods and techniques applied to CCS. This framework… More >

Jun Shi¹, Zhujun Zhang², Yangyang Li^1,*, Rui Wang¹, Hao Shi¹, Xile Li³

CMC-Computers, Materials & Continua, Vol.57, No.1, pp. 69-80, 2018, DOI:10.32604/cmc.2018.03688

Abstract The electromagnetic waves emitted from devices can be a source of information leakage and can cause electromagnetic compatibility (EMC) problems. Electromagnetic radiation signals from computer displays can be a security risk if they are intercepted and reconstructed. In addition, the leaks may reveal the hardware information of the computer, which is more important for some attackers, protectors and security inspection workers. In this paper, we propose a statistical distribution based algorithm (SD algorithm) to extracted eigenvalues from electromagnetic radiate video signals, and then classified computers by using classifier based on Bayesian and SVM. We can identify computers automatically and accurately… More >