Storytelling Security: User-Intention Based Traffic Sanitization

Malicious software (malware) with decentralized communication infrastructure, such as peer-to-peer botnets, is difficult to detect. In this paper, we describe a traffic-sanitization method for identifying malware-triggered outbound connections from a personal computer. Our solution correlates user activities with the content of outbound traffic. Our key observation is that user-initiated outbound traffic typically has corresponding human inputs, i.e., keystroke or mouse clicks. Our analysis on the causal relations between user inputs and packet payload enables the efficient enforcement of the inter-packet dependency at the application level. We formalize our approach within the framework of protocol-state machine. We define new application-level traffic-sanitization policies that enforce the inter-packet dependencies. The dependency is derived from the transitions among protocol states that involve both user actions and network events. We refer to our methodology as storytelling security. We demonstrate a concrete realization of our methodology in the context of peer-to-peer file-sharing application, describe its use in blocking traffic of P2P bots on a host. We implement and evaluate our prototype in Windows operating system in both online and offline deployment settings. Our experimental evaluation along with case studies of real-world P2P applications demonstrates the feasibility of verifying the inter-packet dependencies. Our deep packet inspection incurs overhead on the outbound network flow. Our solution can also be used as an offline collect-and-analyze tool

Fixed-time synchronization problem of coupled delayed discontinuous neural networks via indefinite derivative method

In this brief, we introduce a class of coupled delayed nonautonomous neural networks (CDNNs) with discontinuous activation function. Different from the conventional Lyapunov method, this brief uses the implementation of an indefinite derivative to deal with the nonautonomous system for the case that the topology between neurons is nonlinear coupling, and the system can achieve synchronization in fixed time by selecting the suitable control scheme. The settling time estimation of the system which can get rid of the dependence on the initial value is given. Finally, two examples are given to verify the correctness of the results in this paper

Extended Kalman filtering with stochastic nonlinearities and multiple missing measurements

Copyright @ 2012 ElsevierIn this paper, the extended Kalman filtering problem is investigated for a class of nonlinear systems with multiple missing measurements over a finite horizon. Both deterministic and stochastic nonlinearities are included in the system model, where the stochastic nonlinearities are described by statistical means that could reflect the multiplicative stochastic disturbances. The phenomenon of measurement missing occurs in a random way and the missing probability for each sensor is governed by an individual random variable satisfying a certain probability distribution over the interval [0,1]. Such a probability distribution is allowed to be any commonly used distribution over the interval [0,1] with known conditional probability. The aim of the addressed filtering problem is to design a filter such that, in the presence of both the stochastic nonlinearities and multiple missing measurements, there exists an upper bound for the filtering error covariance. Subsequently, such an upper bound is minimized by properly designing the filter gain at each sampling instant. It is shown that the desired filter can be obtained in terms of the solutions to two Riccati-like difference equations that are of a form suitable for recursive computation in online applications. An illustrative example is given to demonstrate the effectiveness of the proposed filter design scheme.This work was supported in part by the National 973 Project under Grant 2009CB320600, National Natural Science Foundation of China under Grants 61028008, 61134009 and 60825303, the State Key Laboratory of Integrated Automation for the Process Industry (Northeastern University) of China, the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. under Grant GR/S27658/01, the Royal Society of the U.K., and the Alexander von Humboldt Foundation of Germany

A deformation mechanism of hard metal surrounded by soft metal during roll forming

It is interesting to imagine what would happen when a mixture of soft-boiled eggs and stones is deformed together. A foil made of pure Ti is stronger than that made of Cu. When a composite Cu/Ti foil deforms, the harder Ti will penetrate into the softer Cu in the convex shapes according to previously reported results. In this paper, we describe the fabrication of multilayer Cu/Ti foils by the roll bonding technique and report our observations. The experimental results lead us to propose a new deformation mechanism for a hard metal surrounded by a soft metal during rolling of a laminated foil, particularly when the thickness of hard metal foil (Ti, 25 μm) is much less than that of the soft metal foil (Cu, 300 μm). Transmission Electron Microscope (TEM) imaging results show that the hard metal penetrates into the soft metal in the form of concave protrusions. Finite element simulations of the rolling process of a Cu/Ti/Cu composite foil are described. Finally, we focus on an analysis of the deformation mechanism of Ti foils and its effects on grain refinement, and propose a grain refinement mechanism from the inside to the outside of the laminates during rolling

The SNP rs961253 in 20p12.3 Is Associated with Colorectal Cancer Risk: A Case-Control Study and a Meta-Analysis of the Published Literature

Background: Colorectal cancer (CRC) is the third common cancer and the fourth leading cause of cancer death worldwide. A single nucleotide polymorphism (SNP), rs961253 located in 20p12, was firstly described to be associated with the increased risk of CRC in a genome-wide association study; however, more recent replication studies yielded controversial results. Methodology/Principal Findings: A hospital-based case-control study in a Chinese population was firstly performed, and then a meta-analysis combining the current and previously published studies were conducted to explore the real effect of rs961253 in CRC susceptibility. In the Chinese population including 641 cases and 1037 controls, per-A-allele conferred an OR of 1.60 (95 % CI = 1.26–2.02) under additive model. In the meta-analysis including 29859 cases and 29696 controls, per-Aallele have an OR of 1.13 (95 % CI = 1.09–1.18) under a random-effects model due to heterogeneity (P = 0.019). Nevertheless, the heterogeneity can be totally explained by ethnicity, with the tau 2 reduced to 0 after including ethnicity in metaregression model. In stratified analysis by ethnicity, per-A-allele had ORs of 1.34 (95 % CI = 1.20–1.50) and 1.11 (95% CI = 1.08–1.14) for Asian and European, respectively, without heterogeneity. Modest influence of each study was observed on overall estimate in sensitive analysis, and evident tendency to significant association was seen in cumulative analysis over time, together indicating the robust stability of the current results

Towards name-based trust and security for content-centric network. In

Abstract-Trust and security have been considered as builtin properties for future Internet architecture. Leveraging the concept of named content in recently proposed information centric network, we propose a name-based trust and security protection mechanism. Our scheme is built with identity-based cryptography (IBC), where the identity of a user or device can act as a public key string. Uniquely, in named content network such as content-centric network (CCN), a content name or its prefixes can be used as public identities, with which content integrity and authenticity can be achieved with IBC algorithms. The trust of a content is seamlessly integrated with the verification of the content's integrity and authenticity with its name or prefix, instead of the public key certificate of its publisher. In addition, flexible confidentiality protection is enabled between content publishers and consumers. For scalable deployment purpose, we further propose to use a hybrid scheme combined with traditional public-key infrastructure (PKI) and IBC. We have implemented this scheme with CCNx open source project on Android

On multistability of delayed genetic regulatory networks with multivariable regulation functions

The official published version of the article can be found at the link below.Many genetic regulatory networks (GRNs) have the capacity to reach different stable states. This capacity is defined as multistability which is an important regulation mechanism. Multiple time delays and multivariable regulation functions are usually inevitable in such GRNs. In this paper, multistability of GRNs is analyzed by applying the control theory and mathematical tools. This study is to provide a theoretical tool to facilitate the design of synthetic gene circuit with multistability in the perspective of control theory. By transforming such GRNs into a new and uniform mathematical formulation, we put forward a general sector-like regulation function that is capable of quantifying the regulation effects in a more precise way. By resorting to up-to-date techniques, a novel Lyapunov–Krasovskii functional (LKF) is introduced for achieving delay dependence to ensure less conservatism. New conditions are then proposed to ensure the multistability of a GRN in the form of linear matrix inequalities (LMIs) that are dependent on the delays. Our multistability conditions are applicable to several frequently used regulation functions especially the multivariable ones. Two examples are employed to illustrate the applicability and usefulness of the developed theoretical results.This work was supported in part by the Biotechnology and Biological Sciences Research Council (BBSRC) of the UK under Grants BB/C506264/1 and 100/EGM17735, the Royal Society of the UK, the National Natural Science Foundation of China under Grant 61028008, and the International Science and Technology Cooperation Project of China under Grant 2009DFA32050

A variance-constrained approach to recursive state estimation for time-varying complex networks with missing measurements

In this paper, the recursive state estimation problem is investigated for an array of discrete timevarying coupled stochastic complex networks with missing measurements. A set of random variables satisfying certain probabilistic distributions is introduced to characterize the phenomenon of the missing measurements, where each sensor can have individual missing probability. The Taylor series expansion is employed to deal with the nonlinearities and the high-order terms of the linearization errors are estimated. The purpose of the addressed state estimation problem is to design a time-varying state estimator such that, in the presence of the missing measurements and the random disturbances, an upper bound of the estimation error covariance can be guaranteed and the explicit expression of the estimator parameters is given. By using the Riccati-like difference equations approach, the estimator parameter is characterized by the solutions to two Riccati-like difference equations. It is shown that the obtained upper bound is minimized by the designed estimator parameters and the proposed state estimation algorithm is of a recursive form suitable for online computation. Finally, an illustrative example is provided to demonstrate the feasibility and effectiveness of the developed state estimation scheme.National Natural Science Foundation of China under Grants 61329301, 61273156 61333012, 11301118 and 11271103, the Youth Science Foundation of Heilongjiang Province of China under Grant QC2015085, the China Postdoctoral Science Foundation under Grants 2015T80482 and 2014M560376, Jiangsu Planned Projects for Postdoctoral Research Funds under Grant 1402004A, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany

Enhancement of stress tolerance in transgenic tobacco plants constitutively expressing AtIpk2β, an inositol polyphosphate 6-/3-kinase from Arabidopsis thaliana

Inositol phosphates (IPs) and their turnover products have been implicated to play important roles in stress signaling in eukaryotic cells. In higher plants genes encoding inositol polyphosphate kinases have been identified previously, but their physiological functions have not been fully resolved. Here we expressed Arabidopsis inositol polyphosphate 6-/3-kinase (AtIpk2β) in two heterologous systems, i.e. the yeast Saccharomycescerevisiae and in tobacco (Nicotiana tabacum), and tested the effect on abiotic stress tolerance. Expression of AtIpk2β rescued the salt-, osmotic- and temperature-sensitive growth defects of a yeast mutant strain (arg82Δ) that lacks inositol polyphosphate multikinase activity encoded by the ARG82/IPK2 gene. Transgenic tobacco plants constitutively expressing AtIpk2β under the control of the Cauliflower Mosaic Virus 35S promoter were generated and found to exhibit improved tolerance to diverse abiotic stresses when compared to wild type plants. Expression patterns of various stress responsive genes were enhanced, and the activities of anti-oxidative enzymes were elevated in transgenic plants, suggesting a possible involvement of AtIpk2β in plant stress responses