Cryptanalysis of an identity based broadcast encryption scheme without random oracles

Identity based broadcast encryption allows a centralized transmitter to send encrypted messages to a set of identities S, so that only the users with identity in S can decrypt these ciphertexts using their respective private key. Recently [Information Processing Letters 109 (2009)], an identity-based broadcast encryption scheme was proposed (Ren and Gu, 2009) [1], and it was claimed to be fully chosen-ciphertext secure without random oracles. However, by giving a concrete attack, we indicate that this scheme is even not chosen-plaintext secure.     

一种基于物理的雨打树枝动态仿真方法

提出了一种应用物理学原理的树枝和雨滴交互作用的真实感动态仿真技术.树枝和叶柄被描述为一种方便由4种弹簧控制的三棱柱弹簧模型(extended three-prism spring model,简称ETPSM).树枝、树叶的运动源于树枝系统与雨滴相互之间能量的双向转换.二者之间的交互作用可以通过一种高效的技术很好地模拟.该技术被专门设计用来模拟液体在具有亲水性的非刚体表面上运动.当雨滴撞击树枝后,树枝会发生震动与转动;雨滴会沿着树叶表面流动,合并成一个更大的雨滴或者悬挂在叶片边缘;当雨滴从树叶边缘落下后,树枝会弹起并恢复到原来的位置.实验结果表明,该技术能够高效、真实地仿真雨滴撞击树枝系统后的相互作用效果,同时可以简单而有效地模拟杆状物体在外力作用下的弹性形变,诸如旋转、震动等.     

Multiobjective optimization immune algorithm in dynamic environments and its application to greenhouse control

A novel multiobjective optimization immune algorithm in dynamic environments, as associated with Pareto optimality and immune metaphors of germinal center in the immune system, is proposed to deal with a class of dynamic multiobjective optimization problems which the dimension of the objective space may change over time. Several immune operators, depending on both somatic maturation and T-cell regulation, are designed to adapt to the changing environment so that the algorithm can achieve a reasonable tradeoff between convergence and diversity of population, among which an environmental recognition rule related to the past environmental information is established to identify an appearing environment. Preliminary experiments show that the proposed algorithm cannot only obtain great superiority over two popular algorithms, but also continually track the time-varying environment. Comparative analysis and practical application illustrate its potential.     

Eigenclassifiers for combining correlated classifiers

In practice, classifiers in an ensemble are not independent. This paper is the continuation of our previous work on ensemble subset selection [A. Ula?, M. Semerci, O.T. Y?ld?z, E. Alpayd?n, Incremental construction of classifier and discriminant ensembles, Information Sciences, 179 (9) (2009) 1298–1318] and has two parts: first, we investigate the effect of four factors on correlation: (i) algorithms used for training, (ii) hyperparameters of the algorithms, (iii) resampled training sets, (iv) input feature subsets. Simulations using 14 classifiers on 38 data sets indicate that hyperparameters and overlapping training sets have higher effect on positive correlation than features and algorithms. Second, we propose postprocessing before fusing using principal component analysis (PCA) to form uncorrelated eigenclassifiers from a set of correlated experts. Combining the information from all classifiers may be better than subset selection where some base classifiers are pruned before combination, because using all allows redundancy.     

容错的网络声明式程序

介绍了基于递归规则的网络声明式语言Netlog的语法和分布式不动点语义,定义了强良好的程序,并证明了强良好的程序的计算结果对有限的消息丢失不敏感.     

基于启发式搜索的IP数据流分类方法的研究

基于应用层载荷特征的IP流分类技术的准确性较高,但是,当特征库庞大时遍历匹配特征库需要消耗大量的时间.鉴于此,提出一种将应用层载荷特征和启发式搜索相结合的IP数据流分类方法.通过从各种应用产生的数据包之间提取共同特征并以此共同特征建立启发式规则,根据启发式规则将特征库划分为多个特征子集,在数据包匹配过程中只需要根据启发式规则搜索匹配特定的特征子集,从而大大减少了对无关特征的匹配过程,使待匹配的特征子集具有更强的针对性、使得时间性能得到提高.对于部分应用采用以DNS为引导的方法来对数据包进行分类,该方法部分消除了基于载荷无法对加密数据进行识别的弊端.本文用C语言实现了该算法,并与开源软件l7-filter算法进行了对比实验.实验结果表明:在离线状态下,本文提出的方法的分类速度是l7-filter分类速度的6-10倍,总体识别准确性达到98%以上.     

基于横向局部性的多核计算模型

片内多核已成为延长摩尔定律的方式,并行算法设计、编程模型、编译器和运行时系统都需要利用计算模型进行分析。现有多核模型对线程间共享缓存等资源的竞争已有较精确的模型,但是对于线程间数据共享考虑较少。提出线程间共享缓存的横向局部性和任务共享率概念,基于此扩展串行存储层次模型RAM(h),提出考虑任务共享率的多核并行计算模型MRAM(h)。     

高效软硬件划分算法及其提升技术

软硬件划分是软硬件协同设计的关键环节,它决定系统中哪些组件由软件实现,哪些由硬件实现。软硬件划分问题已被证明是NP完全问题。将一类软硬件划分问题看作变异的0-1背包问题,在求解背包问题的算法基础上构造出软硬件划分问题的优质启发解。此外,采用禁忌搜索(Tabu Search)算法对求得的启发解进行改进,在软件开销和通信开销满足一定约束的条件下,使得硬件开销尽可能小。实验结果证明,所提算法对当前最新算法的改进最大可达到28%。     

A noun-based approach to feature location using time-aware term-weighting

ContextFeature location aims to identify the source code location corresponding to the implementation of a software feature. Many existing feature location methods apply text retrieval to determine the relevancy of the features to the text data extracted from the software repositories. One of the preprocessing activities in text retrieval is term-weighting, which is used to adjust the importance of a term within a document or corpus. Common term-weighting techniques may not be optimal to deal with text data from software repositories due to the origin of term-weighting techniques from a natural language context.ObjectiveThis paper describes how the consideration of when the terms were used in the repositories, under the condition of weighting only the noun terms, can improve a feature location approach.MethodWe propose a feature location approach using a new term-weighting technique that takes into account how recently a term has been used in the repositories. In this approach, only the noun terms are weighted to reduce the dataset volume and avoid dealing with dimensionality reduction.ResultsAn empirical evaluation of the approach on four open-source projects reveals improvements to the accuracy, effectiveness and performance up to 50%, 17%, and 13%, respectively, when compared to the commonly-used Vector Space Model approach. The comparison of the proposed term-weighting technique with the Term Frequency-Inverse Document Frequency technique shows accuracy, effectiveness, and performance improvements as much as 15%, 10%, and 40%, respectively. The investigation of using only noun terms, instead of using all terms, in the proposed approach also indicates improvements up to 28%, 21%, and 58% on accuracy, effectiveness, and performance, respectively.ConclusionIn general, the use of time in the weighting of terms, along with the use of only the noun terms, makes significant improvements to a feature location approach that relies on textual information.     

Evaluation of the absolute affinity of neuraminidase inhibitor using steered molecular dynamics simulations

The absolute free energy difference of binding (ΔG) between neuraminidase and its inhibitor was evaluated using fast pulling of ligand (FPL) method over steered molecular dynamics (SMD) simulations. The metric was computed through linear interaction approximation. Binding nature was described by free energy differences of electrostatic and van der Waals (vdW) interactions. The finding indicates that vdW metric is dominant over electrostatics in binding process. The computed values are in good agreement with experimental data with a correlation coefficient of R = 0.82 and error of σΔG_exp = 2.2 kcal/mol. The results were observed using Amber99SB-ILDN force field in comparison with CHARMM27 and GROMOS96 43a1 force fields. Obtained results may stimulate the search for an Influenza therapy.