2674 Slices
Medium 9781601323279

Fourier Transform as a Feature Extraction Method for Malware Classification

Kevin Daimi, Hamid R. Arabnia, Samiha Ayed, Michael R. Grimaila, Hanen Idoudi, George Markowsky, and Ashu M. G. Solo CSREA Press PDF

Int'l Conf. Security and Management | SAM'14 |


Fourier Transform as a Feature Extraction Method for Malware


Stanislav Ponomarev, Nathan Wallace, and Travis Atkison

Louisiana Tech University Ruston, LA, 71270

{spo013, nsw004, atkison}@latech.edu

Abstract— Research efforts to develop malicious application detection algorithms have been a priority ever since the discovery of the first “viruses”. In this research effort

Fourier transform is used to extract features from binary

files. Each byte in these files is treated as a value of a discrete function. Discrete Fourier Transform then transforms binary

files into frequency domain. Each frequency is the used as a feature for malware classification. These features are then reduced by random projection algorithm to create a set of low-dimensional features that are used to classify whether the application is malicious or not. A 99.6% accuracy was reached by Random Forest classifier, while processing various worms, trojan horses, viruses, and backdoors.

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Medium 9781601324139

E-business, E-Commerce, Enterprise Information Systems, Telework, and Related Issues

Hamid R. Arabnia, Azita Bahrami, Fernando G. Tinetti, Leonidas Deligiannidis, George Jandieri, Ashu M. G. Solo (Editors) CSREA Press PDF

Int'l Conf. e-Learning, e-Bus., EIS, and e-Gov. | EEE'15 |





Eyad Makki


Lin-Ching Chang changl@cua.edu

Department of Electrical Engineering and Computer Science, School of Engineering, The Catholic University of

America, Washington, DC, United States

Abstract - Despite the fast growing economy, the rapid increasing internet usage and the strong purchasing power in Saudi Arabia, the evolution of E-Commerce remains slow in the country. The growth rate of ECommerce in Saudi Arabia is inconsistent with the growth rate of its economy, mobile usage, social media activity and internet penetration. Previous studies have shown what factors motivate or inhabit the evolution of ECommerce in Saudi Arabia. This paper is conducted to investigate impacts of mobile usage and social media on the acceptance and implementation of E-Commerce in the country. A comprehensive web survey was designed and used to gather an in-depth understanding of the motivators and inhibitors of E-Commerce in Saudi

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Medium 9781601324191

Simulations, Numerical Methods, and Applications

Hamid R. Arabnia, Leonidas Deligiannidis, George Jandieri, Ashu M. G. Solo, Fernando G. Tinetti (Editors) CSREA Press PDF

Int'l Conf. Modeling, Sim. and Vis. Methods | MSV'15 |


Towards an Agent-Based Simulation of

Predators Developing a Search Image

Chris Scogings

Computer Science

Massey University - Albany Campus

North Shore 102-904, Auckland

New Zealand email: c.scogings@massey.ac.nz


Predators build a “search image” to rapidly detect common prey and exclude other possibilities. Prey respond with “apostatic selection” and produce mutations with previously unknown color variations. This process has been observed since the 1960s but is difficult to validate with real populations.

The use of agent-based simulations presents the opportunity to explore specific changes to predators and/or prey in a controlled environment using artificial animals. This article investigates the effects on predator and prey populations of specific changes in behaviour and finds that search images may actually be detrimental to predator success and that prey color mutation may benefit the overall predator population.

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Medium 9781601324023

Late Breaking Papers: Parallel and Distributed Processing Techniques and Applications

Edited by: Hamid R. Arabnia, Hiroshi Ishii, Kazuki Joe, Hiroaki Nishikawa, Hayaru Shouno, Lou D'Alotto, George A. Gravvanis, George Jandieri, Georgios Sirakoulis, Ashu M. G. Solo, William Spataro, Fernando G. Tinetti, Giuseppe A. Trunfio CSREA Press PDF
Medium 9781601323248

Preliminary study on the hand clapping action recognition based on the Leap Motion Controller

Hamid R. Arabnia, Leonidas Deligiannidis Joan Lu, Fernando G. Tinetti, Jane You, George Jandieri, Gerald Schaefer, and Ashu M.G. Solo CSREA Press PDF


Int'l Conf. IP, Comp. Vision, and Pattern Recognition | IPCV'14 |

Preliminary study on the hand clapping action recognition based on the Leap Motion Controller

Jin-Woo Jung1, Hyeseong Lee2 , Jung-Soo Park3 and Yong-One Cho4


Department of Computer Science and Engineering, Dongguk University, Seoul, Korea


Email : jwjung@dongguk.edu (corresponding author)

Abstract - In this paper, we propose a method of recognizing human hand clapping action based on the Leap Motion

Controller. Basic hand clapping is a kind of simple but somewhat fast periodic hand action. By the inevitable occlusion of two hands, fast speed of hand motion, and its neighboring noisy data, it is not easy to be recognized either by vision sensors or by sound sensors.

Leap Motion Controller (LMC) is one of the most advanced and low-priced devices which can be used to detect the detailed motion of multiple moving objects in some restricted range. By the fast and accurate hand trajectory data from

Leap Motion Controller, we can predict the relative position of two palms more accurately. And, by using the prior knowledge about basic hand clapping action sequence, LMCbased hand clapping recognizer has been developed. The average success ratio is 86.11% with the three different test users and 240 tests per each user.

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