Mal-Netminer: Malware Classification Approach based on Social Network Analysis of System Call Graph

As the security landscape evolves over time, where thousands of species of malicious codes are seen every day, antivirus vendors strive to detect and classify malware families for efficient and effective responses against malware campaigns. To enrich this effort, and by capitalizing on ideas from the social network analysis domain, we build a tool that can help classify malware families using features driven from the graph structure of their system calls. To achieve that, we first construct a system call graph that consists of system calls found in the execution of the individual malware families. To explore distinguishing features of various malware species, we study social network properties as applied to the call graph, including the degree distribution, degree centrality, average distance, clustering coefficient, network density, and component ratio. We utilize features driven from those properties to build a classifier for malware families. Our experimental results show that influence-based graph metrics such as the degree centrality are effective for classifying malware, whereas the general structural metrics of malware are less effective for classifying malware. Our experiments demonstrate that the proposed system performs well in detecting and classifying malware families within each malware class with accuracy greater than 96%.Comment: Mathematical Problems in Engineering, Vol 201

The Sylvester Theorem and the Rogers-Ramanujan Identities over Totally Real Number Fields

In this paper, we prove two identities on the partition of a totally positive algebraic integer over a totally real number field which are the generalization of the Sylvester Theorem and that of the Rogers-Ramanujan Identities. Additionally, we give an another version of generalized Rogers-Ramanujan Identities

The Euler-Glaisher Theorem over Totally Real Number Fields

In this paper, we study the partition theory over totally real number fields. Let $K$ be a totally real number field. A partition of a totally positive algebraic integer $\delta$ over $K$ is $\lambda=(\lambda_1,\lambda_2,\ldots,\lambda_r)$ for some totally positive integers $\lambda_i$ such that $\delta=\lambda_1+\lambda_2+\cdots+\lambda_r$. We find an identity to explain the number of partitions of $\delta$ whose parts do not belong to a given ideal $\mathfrak a$. We obtain a generalization of the Euler-Glaisher Theorem over totally real number fields as a corollary. We also prove that the number of solutions to the equation $\delta=x_1+2x_2+\cdots+nx_n$ with $x_i$ totally positive or $0$ is equal to that of chain partitions of $\delta$. A chain partition of $\delta$ is a partition $\lambda=(\lambda_1,\lambda_2,\ldots,\lambda_r)$ of $\delta$ such that $\lambda_{i+1}-\lambda_i$ is totally positive or $0$

Robustness of multiparty nonlocality to local decoherence

We investigate the robustness of multiparty nonlocality under local decoherence, acting independently and equally on each subsystems. To be specific, we consider an N-qubit GHZ state under depolarization, dephasing, or dissipation channel, and tested the nonlocality by violation of Mermin-Klyshko inequality, which is one of Bell's inequalities for multi-qubit systems. The results show that the robustness of nonlocality increases with the number of qubits, and that the nonlocality of an N-qubit GHZ state with even N is extremely persistent against dephasing.Comment: 5 pages, 4 figure

A Factor Analysis of Urban Railway Casualty Accidents and Establishment of Preventive Response Systems

AbstractSince the commencement of urban railways in 1974 and KTX service in 2014, the use of railways has been steadily increasing. The number of people using rail transportation has been steadily rising. As a result, this has also led to an increase in the number of passenger-related accidents that are occurring within railway stations. In an effort to prevent such accidents, much of the rail operation system is now automated. Nevertheless, the potential risks of railway accidents are very much present today. This study has utilized the railway accident databases of rail operators to allow for analysis of different types of railway accidents, age of accident victims, gender of accident victims, pedestrian facilities involved in accidents, passengers involved in accidents, and underlying causes of rail accidents. Based on these statistics and analyses, this paper proposes the development of a railway safety education program and the establishment of railway safety education centers as a means of preventing railway accidents