Bandelet Union Optimal Matrix Norms Constructing Lossless Watermarking
A multi-frequency lossless watermarking algorithm is proposed in this paper. Bandelet and optimal matrix norms are used to draw the geometric feature and the statistic feature. The bandelet transform is applied to the image, and the texture and edge traced by using the geometric flow via feature of the image to build the high frequency lossless watermarking. A low frequency watermarking scheme is also achieved, by selecting optimal matrix norm to process the low frequency part of wavelets coefficients. The experiments show the offered watermarking system is evaluated against standard watermarking attacks.

title: Solving P2P Traffic Identification Problems Via Optimized Support Vector Machines
abstract: Since the emergence of peer-to-peer (P2P) networking in the last 90s, P2P traffic has become one of the most significant portions of the network traffic. Accurate identification of P2P traffic makes great sense for efficient network management and reasonable utility of network resources. Application level classification of P2P traffic, especially without payload feature detection, is still a challenging problem. This paper proposes a new method for P2P traffic identification and application level classification, which merely uses transport layer information. The method uses support vector machines which have been optimized for performing large learning tasks, rendering that this method become more suitable for large network traffic. The experimental results show that this method achieved high efficiency and is suitable for real-time identification. And carefully tuning the parameters could make the method achieve high accuracy.

title: Privacy-preserving genomic computation through program specialization
abstract: In this paper, we present a new approach to performing important classes of genomic computations (e.g., search for homologous genes) that makes a significant step towards privacy protection in this domain. Our approach leverages a key property of the human genome, namely that the vast majority of it is shared across humans (and hence public), and consequently relatively little of it is sensitive. Based on this observation, we propose a privacy-protection framework that partitions a genomic computation, distributing the part on sensitive data to the data provider and the part on the pubic data to the user of the data. Such a partition is achieved through program specialization that enables a biocomputing program to perform a concrete execution on public data and a symbolic execution on sensitive data. As a result, the program is simplified into an efficient query program that takes only sensitive genetic data as inputs. We prove the effectiveness of our techniques on a set of dynamic programming algorithms common in genomic computing. We develop a program transformation tool that automatically instruments a legacy program for specialization operations. We also demonstrate that our techniques can greatly facilitate secure multi-party computations on large biocomputing problems.

title: Towards automatic reverse engineering of software security configurations
abstract: The specifications of an application's security configuration are crucial for understanding its security policies, which can be very helpful in security-related contexts such as misconfiguration detection. Such specifications, however, are often ill-documented, or even close because of the increasing use of graphic user interfaces to set program options. In this paper, we propose ConfigRE, a new technique for automatic reverse engineering of an application's access-control configurations. Our approach first partitions a configuration input into fields, and then identifies the semantic relations among these fields and the roles they play in enforcing an access control policy. Based upon such knowledge, ConfigRE automatically generates a specification language to describe the syntactic relations of these fields. The language can be converted into a scanner using standard parser generators for scanning configuration files and discovering the security policies specified in an application. We implemented ConfigRE in our research and evaluated it against real applications. The experiment results demonstrate the efficacy of our approach.

title: Side-Channel Leaks in Web Applications: A Reality Today, a Challenge Tomorrow
abstract: With software-as-a-service becoming mainstream, more and more applications are delivered to the client through the Web. Unlike a desktop application, a web application is split into browser-side and server-side components. A subset of the application’s internal information flows are inevitably exposed on the network. We show that despite encryption, such a side-channel information leak is a realistic and serious threat to user privacy. Specifically, we found that surprisingly detailed sensitive information is being leaked out from a number of high-profile, top-of-the-line web applications in healthcare, taxation, investment and web search: an eavesdropper can infer the illnesses/medications/surgeries of the user, her family income and investment secrets, despite HTTPS protection; a stranger on the street can glean enterprise employees' web search queries, despite WPA/WPA2 Wi-Fi encryption. More importantly, the root causes of the problem are some fundamental characteristics of web applications: stateful communication, low entropy input for better interaction, and significant traffic distinctions. As a result, the scope of the problem seems industry-wide. We further present a concrete analysis to demonstrate the challenges of mitigating such a threat, which points to the necessity of a disciplined engineering practice for side-channel mitigations in future web application developments.

title: Panalyst: Privacy-Aware Remote Error Analysis on Commodity Software
abstract: Remote error analysis aims at timely detection and remedy of software vulnerabilities through analyzing run-time errors that occur on the client. This objective can only be achieved by offering users effective protection of their private information and minimizing the performance impact of the analysis on their systems without undermining the amount of information the server can access for understanding errors. To this end, we propose in the paper a new technique for privacy-aware remote analysis, called Panalyst. Panalyst includes a client component and a server component. Once a runtime exception happens to an application, Panalyst client sends the server an initial error report that includes only public information regarding the error, such as the length of the packet that triggers the exception. Using an input built from the report, Panalyst server performs a taint analysis and symbolic execution on the application, and adjusts the input by querying the client about the information upon which the execution of the application depends. The client agrees to answer only when the reply does not give away too much user information. In this way, an input that reproduces the error can be gradually built on the server under the client's consent. Our experimental study of this technique demonstrates that it exposes a very small amount of user information, introduces negligible overheads to the client and enables the server to effectively analyze an error.

title: Research on Modified Structure of Turbo-Blast System
abstract: In this paper, a new MIMO system named turbo-BLAST which utilizes the turbo principle is investigated. Meanwhile, we propose the idea of using advanced channel codes in the system , such as turbo code and TCM (trellis code modulation) code. New algorithm of detector is deducted in order to fit for non-constant envelope modulation. There new structures are proposed: a modified structure named selective feedback are proposed to reduce the time-delay of turbo-BLAST for high-order modulation, the decoding algorithm of trellis code modulation is modified to provide the detector with extrinsic information, and the new decoder structure of turbo code is also given. The simulation results show that selective feedback can achieve better performance, and the structure using turbo code can achieve better performance and faster convergence rate in high-order modulation