Ligang Cong

Anomaly Detection for Application Layer User Browsing Behavior Based on Attributes and Features

Application layer distributed denial of service (App-DDoS) attacks has posed a great threat to the security of the Internet. Since these attacks occur in the application layer, they can easily evade traditional network layer and transport layer detection methods. In this paper, we extract a group of user behavior attributes from our intercept program instead of web server logs and construct a behavior feature matrix based on nine user behavior features to characterize user behavior. Subsequently, principal component analysis (PCA) is applied to profile the user browsing behavior pattern in the feature matrix and outliers from the pattern are used to recognize normal users and attackers. Experiment results show that the proposed method is good to distinguish normal users and attackers. Finally, we implement three machine learning algorithms (K-means, DBSCAN and SVM) to further validate the effectiveness of the proposed attributes and features.

An Auction-Gaming Based Routing Model for LEO Satellite Networks

Characteristics of LEO satellite networks, like dynamically changed topological structures, limited on-board resources, and longer communication delay, have brought new challenges to the construction of satellite networks. By analyzing existing routing models for satellite networks, this paper proposes an auction-gaming-based routing model for LEO satellite networks, based on the DTN protocol and against such characteristics. By making use of an auction model, it takes space propagation loss, residual storage space of a node, and routing hop counts as important bases for routing selection. Analysis shows that besides the routing function, this model also plays an active role in avoiding “selfish” satellite nodes, as well as in relieving network congestion.

Research on the Routing Algorithm of LEO-Satellite DTN Network Based on Multi-Attribute Decision Making

Space information network is an important development direction of future information network, and LEO-satellite DTN network is an important part of space information network. As LEO (low earth orbit) satellite network is characterized by big delay, frequent interruption and highly variable topological structure, the issue of routing has become the bottleneck constraint to the development of this network. To facilitate the solving of routing issue, this paper proposes a routing algorithm based on multiple-attribute decision making (MADM), which uses five important indicators, namely satellite network link bandwidth, link establishment delay, free storage space at nodes, network BER (bit error ratio) and data forwarding rate at nodes, as the basis of routing, and decides on the data-forwarding route in accordance with the calculated attribute proportions to realize the DTN routing. Meanwhile, through the adjustment of attribute preference, this algorithm can optimize the paths of various service networks so as to adapt to the multi-service needs of space information network. The result of simulation experiment shows that, compared with Epidemic and PROPHET routing algorithm, this algorithm is significantly advantageous in terms of data transmission success rate and average network delay.

A semi-symmetric image encryption scheme based on the function projective synchronization of two hyperchaotic systems

Both symmetric and asymmetric color image encryption have advantages and disadvantages. In order to combine their advantages and try to overcome their disadvantages, chaos synchronization is used to avoid the key transmission for the proposed semi-symmetric image encryption scheme. Our scheme is a hybrid chaotic encryption algorithm, and it consists of a scrambling stage and a diffusion stage. The control law and the update rule of function projective synchronization between the 3-cell quantum cellular neural networks (QCNN) response system and the 6th-order cellular neural network (CNN) drive system are formulated. Since the function projective synchronization is used to synchronize the response system and drive system, Alice and Bob got the key by two different chaotic systems independently and avoid the key transmission by some extra security links, which prevents security key leakage during the transmission. Both numerical simulations and security analyses such as information entropy analysis, differential attack are conducted to verify the feasibility, security, and efficiency of the proposed scheme.

Response to Multiple Attack Behaviour Models in Cloud Computing

User behaviour models have been widely used to simulate attack behaviour in the security domain. In this paper, we introduce one perfect rational and three bounded rational behaviour models to simulate attack behaviour of attack-defense game in cloud computing, and then discuss defender’s response to attacks. We assume cloud provider as the role of defender is intelligent to collect attack-related information so that it can predict attack behaviour model, thus the attack behaviour model is known to defender, we therefore build a single-objective optimization game model to find the optimal virtual machine (VM) monitoring strategy against attacker. Finally, through numerical analysis, we prove that when the attack behavior model is known, the corresponding single-objective optimization game solution is better than the other three solutions.

Optimal backup strategy in cloud disaster tolerance

Cloud disaster tolerance has been widely used as a data security mechanism in which multiple replicas of disaster tolerance data are stored in different backup nodes for reliability. In this paper, we deeply study the optimal data backup strategy that backup nodes set the resources prices and source nodes determine the resources quantities that they want to rent. Firstly, we apply a Stackelberg game framework to simulate the interaction among source nodes and backup nodes whose objective is to gain the maximum payoff of every source node and the maximum total payoff of all the backup nodes by adjusting strategies interactively. And then we propose an algorithm to compute the equilibrium price strategy for backup nodes and equilibrium price strategy for source nodes. Finally, we validate this optimal backup strategy through numerical analysis.