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Journal of Cyber Security and Mobility

Editors-in-Chief:
Ashutosh Dutta, Johns Hopkins University, USA
Ruby Lee, Princeton University, USA
Neeli R. Prasad, International Technological University, San Jose, USA
Wojciech Mazurczyk, Warsaw University of Technology, Poland


ISSN: 2245-1439 (Print Version),

ISSN: 2245-4578 (Online Version)
Vol: 7   Issue: 4

Published In:   October 2018

Publication Frequency: Quarterly


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Malware Characterization Using Windows API Call Sequences

doi: https://doi.org/10.13052/jcsm2245-1439.741
Sanchit Gupta1, Harshit Sharma2 and Sarvjeet Kaur1

1SAG, DRDO, Delhi, India
2NIIT University, Neemrana, India

Abstract: [+]    |    Download File [ 735KB ]    |   Read Article Online

Abstract: In this research we have used Windows API (Win-API) call sequences to capture the behaviour of malicious applications. Detours library by Microsoft has been used to hook the Win-APIs call sequences. To have a higher level of abstraction, related Win-APIs have been mapped to a single category. A total set of 534 important Win-APIs have been hooked and mapped to 26 categories (A. . . Z). Behaviour of any malicious application is captured through sequence of these 26 categories of APIs. In our study, five classes of malware have been analyzed: Worm, Trojan-Downloader, Trojan-Spy, Trojan-Dropper and Backdoor. 400 samples for each of these classes have been taken for experimentation. So a total of 2000 samples were taken as training set and their API call sequences were analyzed. For testing, 120 samples were taken for each class. Fuzzy hashing algorithm ssdeep was applied to generate fuzzy hash based signature. These signatures were matched to quantify the API call sequence homologies between test samples and training samples. Encouraging results have been obtained in classification of these samples to the above mentioned 5 categories. Further, N-gram analysis has also been done to extract different API call sequence patterns specific to each of the 5 categories of malware.

Keywords: Win-API, API hooking, malware, fuzzy hashing.

A Hybrid Approach of Secret Sharing with Fragmentation and Encryption in Cloud Environment for Securing Outsourced Medical Database: A Revolutionary Approach

doi: https://doi.org/10.13052/jcsm2245-1439.742
Dac-Nhuong Le1, Bijeta Seth2 and Surjeet Dalal2

1Faculty of Information Technology, Haiphong University, Haiphong, Vietnam
2Department of Computer Science & Engineering, SRM University, Sonepat, Haryana, India

Abstract: [+]    |    Download File [ 1545KB ]    |   Read Article Online

Abstract: Cloud Computing is observed as the greatest paradigm change in Information technology. Data outsourcing is an inventive representation with the intention of trustworthy storage and proficient query execution to customers. Data stored on the cloud is showing great attention. However, the security issues allied with data storage over the cloud is a chief daunting cause for potential adopters. Hence the focus is to find techniques that will offer more security. Many diseases fighting organizations are working together io implement cloud as a data sharing vehicle. It is obligatory to build up innovative solutions with the intention of amalgamate diverse approaches in order to generate flexible and adaptable systems, particularly for achieving elevated levels of utilization of developed algorithms. In this document, we suggest an innovative model based on fragmentation, secret sharing and encryption for medical databases which will divide the data amongst several cloud service providers. We develop a systematic structure exploiting the sensitive nature of information and results in enhanced security level. A database for medical system is represented as Entity association and Relational model. A cloud based model is proposed to offer secure patient centric right to access PHR in a competent way. The simulation results implemented in NetBeans Java for performance evaluation of existing cryptographic techniques are shown. Our security model is evaluated using CrypTool 1.4.30 considering the entropy of algorithms. The future work includes development of a computerized system retrieving, storing and maintaining data efficiently and quickly.

Keywords: Cloud Computing, Healthcare, Database Outsourcing, Secret Sharing, Fragmentation, Encryption

Enhanced Matrix Chain Multiplication

doi: https://doi.org/10.13052/jcsm2245-1439.743
B. Suvarna and T. Maruthi Padmaja

Vignan’s Foundation for Science Technology and Research, AP, India

Abstract: [+]    |    Download File [ 266KB ]    |   Read Article Online

Abstract: Let A1, A2,....An be the given sequence of n matrices, generally matrix chain multiplication algorithm is used to obtain its-product with minimum cost(lowest cost). However the matrix chain multiplication is a dynamic programming paradigm and takes O(n3) computational complexity. Here we present improved algorithm for matrix chain multiplication with minimum space and time complexities. The viability of this new algorithm is demonstrated using few examples and the performance is computationally verified. This algorithm does not take O(n3) if any two of the S values are not same and O(n3) when the two values of S are same in the worst case.

Keywords: Matrix multiplication, Matrix Chain Multiplication, Dynamic Programming, Optimal ordering of matrices.

River Publishers: Journal of Cyber Security and Mobility