No abstract

No abstract

No abstract

This paper presents a literature review on applications of Levy flight. Nowadays, Levy flight laws has been used for a broad class of processes such as in physical, chemical, biological, statistical and also in financial. From the review, Levy flight technique has been applied mostly in physics area where the researchers use Levy flight technique to solve and optimize the problem regarding diffusive, scaling and transmission. This paper also reviews the latest researches using modified Levy flight technique such as truncated, smoothly truncated and gradually truncated Levy Flight for optimization. Finally, future trends of Levy flight are discussed.

In recent years the amount of malware spreading through the internet and infecting computers and other communication devices has tremendously increased. To date, countless techniques and methodologies have been proposed to detect and neutralize these malicious agents. However, as new and automated malware generation techniques emerge, a lot of malware continues to be produced, which can bypass some state-of-the-art malware detection methods. Therefore, there is a need for the classification and detection of these adversarial agents that can compromise the security of people, organizations, and countless other forms of digital assets. In this paper, we propose a spatial attention and convolutional neural network (SACNN) based on deep learning framework for image-based classification of 25 well-known malware families with and without class balancing. Performance was evaluated on the Malimg benchmark dataset using precision, recall, specificity, precision, and F1 score on which our proposed model with class balancing reached 97.42%, 97.95%, 97.33%, 97.11%, and 97.32%. We also conducted experiments on SACNN with class balancing on benign class, also produced above 97%. The results indicate that our proposed model can be used for image-based malware detection with high performance, despite being simpler as compared to other available solutions.