Malware clustering using suffix trees

Clustering is an important problem in malware research, as the number of malicious samples that appear every day makes manual analysis impractical. Although these samples belong to a limited number of malware families, it is difficult to categorize them automatically as obfuscation is involved. By extracting relevant features we can apply clustering algorithms, then only analyze a couple of representatives from each cluster. However, classic clustering algorithms that compute the similarity between each pair of samples are slow when a large collection is involved. In this paper, the features will be strings of operation codes extracted from the binary code of each sample. With a modified suffix tree data structure we can find long enough substrings that correspond to portions of a program’s code. These substrings must be filtered against a database of known substrings so that common library code will be ignored. The items that have common substrings above a certain threshold will be grouped into the same cluster. Our algorithm was tested with data extracted from real-world malware and constructed quality clusters.     

Image retrieval based on non-uniform bins of color histogram and dual tree complex wavelet transform

Multimedia Tools and Applications - Traditional Content-Based Image Retrieval (CBIR) systems were developed for retrieving similar kinds of images from a whole image database based on the given...     

A Voltage Phasor Based Fault-classification Method for Phasor Measurement Unit Only State Estimator Output

Abstract—This article presents a fault-classification method for transmission lines based on voltage phasors using classification and regression trees. The proposed method is intended to aid system operators in understanding the outputs of a phasor measurement unit only state estimator. Faults are classified into four categories when the estimator is positive sequence and into ten categories when the estimator is three phase. The fault data are generated in PowerWorld® (PowerWorld Corporation, Champaign, IL, USA) and DSA Tools® (Powertech Labs Inc., Surrey, British Columbia, Canada). The pre-fault state consists of a variety of operating conditions and loading angles of faulted lines. The fault condition comprises different fault types, fault locations, fault impedances, and fault incidence angles. Fault classification is done using MATLAB® (The MathWorks, Natick, Massachusetts, USA).The approach is successfully tested on the IEEE-118 bus system. The results demonstrate that the technique developed here is effective and robust, irrespective of the pre-fault and fault conditions.     

Dielectric and conducting behavior of pyrene functionalized PANI/P(VDF‐co‐HFP) blend

Herein, we present the dielectric and electrical conductivity properties of the partially miscible polymer blend prepared using pyrene functionalized polyaniline (pf‐PANI) and poly(vinylidene fluoride‐co‐hexafluoro propylene) (PVDF‐co‐HFP). The blend mostly retains the fluorescent nature of pf‐PANI as well as can be moldable and possesses good damping property. The dielectric properties have been investigated as a function of temperature at three different frequencies and the plausible origin of polarization responsible for dielectric behavior in this blend has been identified. The experimental results of dielectric measurements are compared with theoretical models and discussed. The surface morphology of the samples has been examined with a scanning electron microscope. The electrical conductivity has also been studied as a function of temperature and explained in terms of hopping of charge carriers/interconnected networks. The combined dielectric and conductivity results together with scanning electron microscope micrographs, reveal that there is hindrance to achieve percolation threshold even after pf‐PANI addition of 57 vol % and subsequent thermal treatment. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 44077.