Code-injection attacks pose serious threat to today’s Internet. The existing code-injection attack defense methods have some deficiencies on performance overhead and effectiveness. To this end, we propose a method that uses system called randomization to counter code injection attacks based on instruction set randomization idea. System calls must be used when an injected code would perform its actions. By creating randomized system calls of the target process, an attacker who does not know the key to the randomization algorithm will inject code that isn’t randomized like as the target process and is invalid for the corresponding de-randomized module. The injected code would fail to execute without calling system calls correctly. Moreover, with extended complier, our method creates source code randomization during its compiling and implements binary executable files randomization by feature matching. Our experiments on built prototype show that our method can effectively counter variety code injection attacks with low-overhead.

Peer-to-peer (P2P) file-sharing systems have gained large interests among the internet users. However, wide-scale applications of P2P file-sharing technologies are constrained by the limitations associated with the sophisticated control mechanisms. Moreover, the decentralized and anonymous characteristics of P2P environments make it more difficult to control accesses on the shared resources, especially for using traditional access control methods. To overcome these limitations, we propose a role-based access control architecture for P2P file-sharing systems that supports autonomous decisions and centralized controls. The architecture integrates policies of credential, identity and role-based access control models to provide scalable, efficient and fault-tolerant access control services. Furthermore, we employ the primary-backup (PB) scheme to preserve P2P decentralized structure and peers’ autonomy property while enabling collaboration between peers. In particular, we propose a method for setting up interoperating relationships between domains by role mappings and resolve two kinds of interoperability conflicts while mapping roles from foreign domain to local domain without centralized authority. We believe that the proposed architecture is realistic, efficient and can provide controlled communications between peers.

A group signature scheme and a threshold group signature scheme based on Bilinear Paring are proposed, there are multiple security strategies in these two schemes. These schemes have forward security which minimizes the damage caused by the exposure of any group member's signing key, and does not affect the past signatures generated by this member; meanwhile, ahead signature generated by a group member before the joining date can be prevented via this strategy. Moreover, this scheme support the group member revocable function efficiently and further has no requirement for time period limits.

Analog circuits are of great importance in electronic system design. Analog circuit design consists of circuit topology design and component values design. These two aspects are both essential to computer aided analog circuit evolving. However, Traditional GA is not very efficient in evolving circuit component’s values. This paper proposed a hybrid algorithm HME-GA (GA with hyper-mutation and elitist strategies). The advantage of HME-GA is that, it not only concentrates on evolving circuit topology, but also pays attention to evolving circuit component’s values. Experimental results show that, the proposed algorithm performs much better than traditional GA. HME-GA is an efficient tool for analog circuit design. Evolutionary technology has been demonstrated to be very useful in computer aided analog circuit design. More potential of evolutionary methods on analog circuit design is waiting for exploring.

Individual Chinese characters are identified mainly by their skeleton structure instead of texture or color.In this paper, an approach based on skeleton similarity for Chinese calligraphic characters retrieval is proposed.By this approach,first,the skeleton of the binarized individual characters are acquired by an improved multi-level module analysis algorithm.Second,the first round of skeleton matching based on the invariant moment-descriptor guarantees the recall rate;the second round of skeleton matching based on the comprehensive characteristic difference in the polar coordinates system guarantees the retrieval precision.Finally,different styles of the same Chinese characters are ranked and displayed according to the two rounds of matching score.Besides,the efficiency of our approach is manifested by the preliminary experiment.

In this paper, an unsupervised multiresolution image segmentation algorithm is put forward, which combines interscale and intrascale Markov random field and fuzzy c-means clustering with spatial constraints. In the initial label determination of wavelet coefficient phase, the statistical distribution property of wavelet coefficients is characterized by Gaussian mixture model, the properties of intrascale clustering and interscale persistence of wavelet coefficients are captured by Markov prior probability model. According to maximum a posterior rule, the initial label of wavelet coefficient from coarse to fine scale is determined. In the image segmentation phase, in order to overcome the shortcomings of conventional fuzzy c-means clustering, such as being sensitive to noise and lacking of spatial constraints, we construct the novel fuzzy c-means objective function based on the property of intrascale clustering and interscale persistence of wavelet coefficients, taking advantage of Lagrange multipliers, the improved objective function with spatial constraints is optimized, the final label of wavelet coefficient is determined by iteratively updating the membership degree and cluster centers. The experimental results on real magnetic resonance image and peppers image with noise show that the proposed algorithm obtains much better segmentation results, such as accurately differentiating different regions and being immune to noise.