Ru Zhang

Steganalysis of the MP3 steganographic algorithm based on Huffman coding

Huffman codes replacement algorithm is a new steganographic method by replacing Huffman codes to hide information. The advantages are simple computation, large capacity, good imperceptibility, and so on. However there is no steganalytic method can be used for the new algorithm. A statistical model of the Huffman codes replacement is presented by steganalysising a MP3 algorithm and a steganalysis scheme was proposed which was implemented by using support vector machine (SVM) to classify the stego audio from clear audio.

A new authentication and key agreement protocol of 3G based on Diffie-Hellman Algorithm

Third Generation (3G) wireless networks are now increasingly being deployed throughout the world. Because of their complex signaling and relatively limited bandwidth, these 3G networks are generally more vulnerable than their wire-line counterparts, thus making them fertile ground for some new attacks. In this paper, we propose a novel AKA Protocol scheme of 3G, which is based on Diffie-Hellman Algorithm. This scheme improves the transmission security between ME, VLR and HLR, it also provides message freshness, forward secrecy, robust message confidentiality and message integrity. Man-in-the-middle attack and replay attack are also prevented. However, it cannot prevent the key compromise impersonation because of the shared key scheme.

Steganalysis of MSU Stego Video based on discontinuous coefficient

MSU(Moscow State University) Stego Video is a public video steganographic tool. It uses a specific data distribution mode to load secret data, so that the message can be extracted correctly even the stego video are compressed. In this paper, based on the analysis of the distribution characteristics of the embedded data, a detection algorithm against MSU embedding is proposed by utilizing the difference of block artifacts distribution between natural frames and stego frames. The algorithm can reliably detect the existence of hidden data. It is easy to implement and computationally efficient, and is suitable for real-time detection.

An attack pattern mining algorithm based on fuzzy logic and sequence pattern

How to get the correlation rules is one of the main challenges in alert correlation research fields. In this paper, we propose an attack pattern mining algorithm to solve this problem. Our method can be divided into two steps: Fast Fuzzy Cluster Analysis (FFCA) and Frequent Sequence Mining (FSM). FFCA can accurately describe the similarity among the alerts attributes accurately, while FSM can dig the correlation between alerts. In order to find the hidden attack patterns behind massive data efficiently and accurately, we combines the characteristics and advantages of them in our method. At first we design the similarity function for each attribute and separate the raw sequence into alert cluster sets through fuzzy cluster based on the similarity function. Then we dig the Frequent Sequences from these cluster sets. Finally we use experiment results to show the feasibility of our method.

Fast coding in digital steganography

Abstract Dynamical running coding was previously proposed as a method for construction of steganographic schemes in digital steganography. In this article, a new approach of fast coding is proposed to improve steganographic efficiency. Original embedding method is discussed in two cases of constructing different generating matrix; however, the proposed method generalizes the problem to only one case by changing the construction method from the original method. Therefore, the complexity of the proposed method is less than the original method. Meanwhile, both theoretical analysis and experiment results show better performance in terms of distortions and alterations of the cover objects when embedding the same amount of information data bits, which proves a better resistance against steganalysis.

An Android malware detection method based on AndroidManifest file

As one of the most developed intelligent operating systems on mobile devices, Android has taken the most part of the cell phone market. A rapid increase in the number of mobile applications make them more and more relevant to peoples daily lives than ever before. Due to Androids security mechanism and the validation lack of publishing Android apps, Android malware detection still remains to be a critical issue. To solve this problem, this paper found that the statistical information of Android components (mainly activity) from the Manifest file cannot be ignored, based on the traditional method of Android permission detection. In this paper, a new feature vector is extracted from the AndroidManifest file, which combines the permission information and the component information of the Android application. We combine the naive Bias classification algorithm, and propose a malicious application detection method based on AndroidManifest file information. The experimental results show that the new method performance better than that of the traditional permission detection.

Detecting False Information of Social Network in Big Data

With the rapid development of social network, the information announced by this platform attracts more and more attention, because of the great harm brought by the false information, researching the false information detection of social network has great significance. This paper presents a model of social network false information detection, which firstly converting the information announced by social network into a three-dimensional vector, then comparing this vector with the three-dimensional vector converted by Internet events and calculating the similarity between social network and Internet, detecting the consistency of social network event and Internet event afterwards, finally gathering statistics and analyzing then we can get the similarity between social network event and Internet event, according to this, we can judge that the social network information is false or not.

Defense Strategy of Network Security based on Dynamic Classification

In this paper, due to the network security defense is mainly static defense, a dynamic classification network security defense strategy model is proposed by analyzing the security situation of complex computer network. According to the network security impact parameters, eight security elements and classification standard are obtained. At the same time, the dynamic classification algorithm based on fuzzy theory is also presented. The experimental analysis results show that the proposed model and algorithm are feasible and effective. The model is a good way to solve a safety problem that the static defense cannot cope with tactics and lack of dynamic change.

Research on behavioral targeted advertising in mobile Internet

Abstract This paper designs and implements the advertising recommending system based on user behavior under mobile Internet. By analyzing the users online behavior, user profile that includes long-term interests and short-term interests can be obtained. In the end of this paper, the similarity between the behavior clusters and the advertisements is calculated, which is used to rank and select the most appropriate advertisements. The experiments show that the system can push the appropriate advertisements according to the users different interest

A digital watermarking algorithm for high capacity index image robust to format transformation

Based on the image edges non-changing characteristic in image format transformation, a new digital watermarking algorithm for huge index image is proposed. The watermarking information was embedded in edges by adjusting the edge pixels; therefore, the algorithm is robust against the lossless image format transformation. The experimental results show that the proposed algorithm has perfect Robustness against the lossless image format transformation and good transparency.