Table of Content

15 December 2015, Volume 1 Issue 3

Previous Issue    Next Issue

Big Data Theme Introduction

Zhang Xiaosong

2015, 1(3):  203-204. 

Asbtract ( )   PDF (703KB) ( )  

Related Articles | Metrics

The Core Security in Big Data Industrialization

陈瑞东

2015, 1(3):  205-210. 

Asbtract ( )   PDF (2889KB) ( )  

References | Related Articles | Metrics

Development of cloud applications and mass multisource heterogeneous data access technology brought about big data process platforms. Also, many other industrial applications derived from optimized knowledge discovery algorithms, such as the Internet finance, ecommerce recommendation, public opinion analysis and forecasting. Big data has become of both management and decision making tool for financial institutions, energy and even government agencies. Whereas relevant security threats continue to emerge. Research shows that Big Data Industrialization process does not only require traditional network information security, but also take several innate characteristics of data into consideration. The core elements are data property ownership in transaction process, and conflicts between data usage and data leakage in processing. From aspects of big data development, integrated with knowledge and attitudes of big data security. This paper summarizes the development of big data industry in recent years. We also describe typical solutions for a sound start of big data era.

Research on the Architecture of Big Data Security Assurance System Improved

Lv Xin

2015, 1(3):  211-216. 

Asbtract ( )   PDF (7192KB) ( )  

References | Related Articles | Metrics

In the outline for action to promote the development of big data, appeal was made by the state council of the Peoples Republic of China that the research in the cyber security issues and the cyber security technology should be strengthened under the big data environment and that big data security assurance system should be improved. Based on the analysis of big data security environment and big data security threats and challenges, this paper proposes a multi dimension space model of big data security and privacy assurance system based on the system engineering theory, constructs the architecture model of big data security and privacy assurance system by using the model abstract method, and designs the technical proposal of big data security and privacy assurance in the perspective of strategic planning, security operation management, and security technology. In addition, this paper studies the process model of big data security and privacy assurance, and provides a technical reference for the sustainable ability establishment of big data security and privacy.

Secure Big Data Search and Sharing

2015, 1(3):  217-223. 

Asbtract ( )   PDF (6949KB) ( )  

References | Related Articles | Metrics

A great mount of sensitive data is stored in the cyber network. These sensitive data can be shared by the corporations to reduce the cost for serving the clients, which can improve the datas value. However, data searching and sharing is a challenging problem nowadays. In order to preserve the clients privacy, we review the techniques for ciphertext search. We reviewed the research of security model, the search expression and data updating in singleuser searchable encryption and multiuser searchable encryption. Then we present the scientific and research points of secure big data search and sharing in cyber networks, including data updating, fast response, verifiability, search individualism and the search right changing.

Differential Privacy and Applications

2015, 1(3):  224-229. 

Asbtract ( )   PDF (5750KB) ( )  

References | Related Articles | Metrics

As the emergence and development of application requirements such as data analysis and data publication, a challenge to those applications is to protect private data and prevent sensitive information from disclosure. With the highspeed development of information and network, big data has become a hot topic in both the academic and industrial research, which is regarded as a new revolution in the field of information technology. However, it brings about not only significant economic and social benefits, but also great risks and challenges to individuals` privacy protection and data security. People on the Internet leave many data footprint with cumulatively and relevance. Personal privacy information can be found by gathering data footprint in together.Malicious people use this information for fraud. It brings many trouble or economic loss to personal life.Privacy preserving, especially in data release and data mining, is a hot topic in the information security field. Differential privacy has grown rapidly recently due to its rigid and provable privacy guarantee. We analyze the advantage of differential privacy model relative to the traditional ones, and review other applications of differential privacy in various fields and discuss the future research directions. Following the comprehensive comparison and analysis of existing works, future research directions are put forward.

An APT Defensive Approach Based on Big Data Analysis

2015, 1(3):  230-237. 

Asbtract ( )   PDF (7888KB) ( )  

References | Related Articles | Metrics

In the age of big data, the introduction of big data analytics technology to advance persistent threat defense system is inevitable. Based on big data analysis technology, the paper proposed a reference framework for protection of advanced persistent threat, fully considering the requirement of advanced persistent threat protection framework, all the possible attack mode and protection methods. Through deep correlation analyzing the monitoring data by big data technology, we could not only obtain a comprehensive analysis about if the target system in the risk of being attacked to achieve prewarning, but also detect the ongoing attacks and understand the intent more accurately to achieve realtime blocking. Meantime, according to track the data path to reproduce the historical status and evolutionary process , post audit traceability is realized.

Research of Cryptography Technologies for Big Data Security

Zhang Xiaosong

2015, 1(3):  238-244. 

Asbtract ( )   PDF (7091KB) ( )  

References | Related Articles | Metrics

The most important significance of big data is on the analysis of massive data sets, so as to mine new knowledge and create new value. Hence, the essence of big data technology is the data mining and analysis algorithm, just with the 3V characteristics: Volume, Variety, Velocity. Furthermore, if big data security is assured, new mined knowledge will be convinced, and people may be eager to share their data for big data analytics. Therefore, for big data security, cryptography technologies should have the following two features: 1) cryptography algorithms can achieve good scalability and efficiency to handle big data; 2) the cryptography technology can meet the needs of security analysis of big data: it can not only analyze and mine big data, but also protect big data security and user privacy.

A Study of Secure Deduplication Systems and Key Technologies

2015, 1(3):  245-252. 

Asbtract ( )   PDF (7871KB) ( )  

References | Related Articles | Metrics

In the age of big data, the dramatic growth of data in enterprises poses a critical challenge to storage and management. Data deduplication technique recognizes the redundancies in data streams, and just transfers and stores the unique data objects, thereby effectively reducing costs. From a security standpoint, this paper focuses on the advances of secure deduplication systems. We describe the deduplication architecture as well as its security requirements. Then, we introduce contentbased encryption, which is the core methodology of building secure deduplication systems, and analyze the principles and limitations of the stateoftheart technologies. Finally, we summarize existing works about secure data deduplication systems, and discuss future research directions.

Research on the Telecom Fundamental Network Information Security Awareness Based on Big Data Analyzation

2015, 1(3):  253-260. 

Asbtract ( )   PDF (7321KB) ( )  

References | Related Articles | Metrics

The telecom fundamental network as the infrastructure of the national economy, information security assurance of it plays an important strategic role in the informatization process of whole national economy. As telecom fundamental network carrying more and more businesses, the number of daily safety incidents comes to be huge, traditional analysis pattern and technique are not able to evaluate and prediction the security situation awareness of telecom fundamental network. The author provides a telecom fundamental network security awareness evaluation framework based on the big data analyzation and related algorithms, therefore it enhances the quick and correct evaluation capability of telecom fundamental network.

DDoS Detection Framework based on Hadoop

2015, 1(3):  261-266. 

Asbtract ( )   PDF (5465KB) ( )  

References | Related Articles | Metrics

Distributed Denial of Service (DDoS) attack is one of the most powerful attacks and it is very difficult to prevent and mitigate. This paper expounds a DDoS detection framework based on Hadoop. The framework utilizes the MapReduce and HDFS to deal with the analysis of DDoS attacks. This framework is composed of two main servers. One is used for capture traffic; another is used as detection server analyzing traffic and generating the results. Detection server manages a Hadoop cluster, it starts MapReduce-based DDoS detection jobs on the cluster nodes. The proposed framework implements Counter-Based algorithm to detect major DDoS flooding attacks. Ultimately, we perform experiments to evaluate the detection performance of the framework, and our proposed method shows its promising performances.

Study of Malware Detection based on Distribution of Assembly Instruction

2015, 1(3):  267-271. 

Asbtract ( )  

References | Related Articles | Metrics

Nowadays, there are more and more various malicious code which cause a huge threat to the computer. In this paper, a variety of assembly instructions are well classified into three categories. And a novel algorithm is presented. In consideration of the relationship between instructions, this paper turn this relationship into probability distributions as the signature of the program. Then, using a large amount of samples to train. The experiment shows that the method proposed in this paper has a significant effect and high accuracy on detecting unknown and metamorphic programs.

Research on short text classification in security attack tracking and analysis

2015, 1(3):  272-277. 

Asbtract ( )   PDF (5304KB) ( )  

References | Related Articles | Metrics

In recent years, with the rapid development of information technology in the era of big data, information security research has also been rapid development, more and more network information security attacks continue to occur and are reported. In order to protect the information security of the network, it is very important to establish the network information security attack and tracking system. Network information security attack and tracking analysis system is based on network attacks, which can leave a large amount of network attack traces, and the advantages of large data analysis platform for multi-source massive data analysis, multi dimension and multi angle analysis. Which is a very important technology in the network information security attack and tracking analysis system based on large data. This paper chooses Naive Bayesian as a text classification algorithm, because the characteristics of the Naive Bayesian classification algorithm is generally very difficult to meet in the reality, in order to relax the assumption in a certain degree, this paper proposes a classification method based on feature items improved weight Naive Bayesian, which is based on the improved chi square statistical feature selection method and weighted Naive Bayesian classification algorithm. The experimental results show that the classification method based on the feature of the improved weight of the Naive Bayesian classification method has a certain improvement compared with the classification results.

Design and Implementation of Multi-interface Safe High-speed Optical Fiber One-way Transmission System

2015, 1(3):  278-282. 

Asbtract ( )   PDF (4769KB) ( )  

References | Related Articles | Metrics

Focused on the issue of importing data to secret-associated network, and avoid the risk of revealing the confidential data, A Multi-interface Safe High-speed Optical Fiber One-way Transmission System was proposed. This paper explains the detail implementation about hardware and software of unidirectional transmission. Computer high speed transmission interface and optical fiber communication technology was used to improve high-speed data transmission reliability. Forward error correction code was used in physical layer for controlling transmission errors. High reliable connectionless transfer layer was designed to improve the reliability of the system. Plug and play multi-interface technology was use to improve the ease for use. The theoretical analysis and simulation results show that the high-speed transmission can be provided by using the unidirectional data import system, and better performance in transmission efficiency and accuracy.

Cybersecurity Law (Draft) from a Comprehensive Perspective

2015, 1(3):  283. 

Asbtract ( )   PDF (2733KB) ( )  

References | Related Articles | Metrics