DeltaPhish: Detecting Phishing Webpages in Compromised Websites

The large-scale deployment of modern phishing attacks relies on the automatic exploitation of vulnerable websites in the wild, to maximize profit while hindering attack traceability, detection and blacklisting. To the best of our knowledge, this is the first work that specifically leverages this adversarial behavior for detection purposes. We show that phishing webpages can be accurately detected by highlighting HTML code and visual differences with respect to other (legitimate) pages hosted within a compromised website. Our system, named DeltaPhish, can be installed as part of a web application firewall, to detect the presence of anomalous content on a website after compromise, and eventually prevent access to it. DeltaPhish is also robust against adversarial attempts in which the HTML code of the phishing page is carefully manipulated to evade detection. We empirically evaluate it on more than 5,500 webpages collected in the wild from compromised websites, showing that it is capable of detecting more than 99% of phishing webpages, while only misclassifying less than 1% of legitimate pages. We further show that the detection rate remains higher than 70% even under very sophisticated attacks carefully designed to evade our system.Comment: Preprint version of the work accepted at ESORICS 201

Electrostatic Repulsion of Positively Charged Vesicles and Negatively Charged Objects

A positively charged, mixed bilayer vesicle in the presence of negatively charged surfaces (for example, colloidal particles) can spontaneously partition into an adhesion zone of definite area, and another zone that repels additional negative objects. Although the membrane itself has nonnegative charge in the repulsive zone, negative counterions on the interior of the vesicle spontaneously aggregate there, and present a net negative charge to the exterior. Beyond the fundamental result that oppositely charged objects can repel, our mechanism helps explain recent experiments on surfactant vesicles.Comment: Latex using epsfig and afterpage; pdf available at http://www.physics.upenn.edu/~nelson/Mss/repel.pd

Rotational perturbations in Neveu-Schwarz–Neveu-Schwarz string cosmology

First order rotational perturbations of the flat Friedmann-Robertson-Walker metric are considered in the framework of four dimensional Neveu-Schwarz–Neveu-Schwarz string cosmological models coupled with dilaton and axion fields. For the H field we use the solitonic ansatz, assuming that it is a function of time only. The decay rate of rotation depends mainly upon the dilaton field potential U. The equation for rotation imposes strong limitations upon the functional form of U, restricting the allowed potentials to two: the trivial case U=0 and a generalized exponential type potential. In these two models the metric rotation function can be obtained in an exact analytic form in both Einstein and string frames. In the potential-free case the decay of rotational perturbations is governed by an arbitrary function of time while in the presence of a potential the rotation tends rapidly to zero in both Einstein and string frames.published_or_final_versio

Acceleration of Levenberg-Marquardt Training of Neural Networks with Variable Decay Rate

In the application of the standard Levenherg-Marquardt training process of neural networks, error oscillations are frequently observed and they usually aggravate on approaching the required accuracy. In this paper, a modified Levenberg-Marquardt method based on variable decay rate in each iteration is proposed in order to reduce such error oscillations. Through a certain variation of the decay rate, the time required for training of neural networks is cut down to less than half of that required in the standard Levenberg-Marquardt method. Several numerical examples are given to show the effectiveness of the proposed method.published_or_final_versio

DNA barcoding reveals the coral “laboratory-rat”, Stylophora pistillata encompasses multiple identities

Stylophora pistillata is a widely used coral “lab-rat” species with highly variable morphology and a broad biogeographic range (Red Sea to western central Pacific). Here we show, by analysing Cytochorme Oxidase I sequences, from 241 samples across this range, that this taxon in fact comprises four deeply divergent clades corresponding to the Pacific-Western Australia, Chagos-Madagascar-South Africa, Gulf of Aden-Zanzibar-Madagascar, and Red Sea-Persian/Arabian Gulf-Kenya. On the basis of the fossil record of Stylophora, these four clades diverged from one another 51.5-29.6 Mya, i.e., long before the closure of the Tethyan connection between the tropical Indo-West Pacific and Atlantic in the early Miocene (16–24 Mya) and should be recognised as four distinct species. These findings have implications for comparative ecological and/or physiological studies carried out using Stylophora pistillata as a model species, and highlight the fact that phenotypic plasticity, thought to be common in scleractinian corals, can mask significant genetic variation

MIXIN COMPOSITION SYNTHESIS BASED ON INTERSECTION TYPES

We present a method for synthesizing compositions of mixins using type inhabitation in intersection types. First, recursively defined classes and mixins, which are functions over classes, are expressed as terms in a lambda calculus with records. Intersection types with records and record-merge are used to assign meaningful types to these terms without resorting to recursive types. Second, typed terms are translated to a repository of typed combinators. We show a relation between record types with record-merge and intersection types with constructors. This relation is used to prove soundness and partial completeness of the translation with respect to mixin composition synthesis. Furthermore, we demonstrate how a translated repository and goal type can be used as input to an existing framework for composition synthesis in bounded combinatory logic via type inhabitation. The computed result is a class typed by the goal type and generated by a mixin composition applied to an existing class

Game Theory of Social Distancing in Response to an Epidemic

Social distancing practices are changes in behavior that prevent disease transmission by reducing contact rates between susceptible individuals and infected individuals who may transmit the disease. Social distancing practices can reduce the severity of an epidemic, but the benefits of social distancing depend on the extent to which it is used by individuals. Individuals are sometimes reluctant to pay the costs inherent in social distancing, and this can limit its effectiveness as a control measure. This paper formulates a differential-game to identify how individuals would best use social distancing and related self-protective behaviors during an epidemic. The epidemic is described by a simple, well-mixed ordinary differential equation model. We use the differential game to study potential value of social distancing as a mitigation measure by calculating the equilibrium behaviors under a variety of cost-functions. Numerical methods are used to calculate the total costs of an epidemic under equilibrium behaviors as a function of the time to mass vaccination, following epidemic identification. The key parameters in the analysis are the basic reproduction number and the baseline efficiency of social distancing. The results show that social distancing is most beneficial to individuals for basic reproduction numbers around 2. In the absence of vaccination or other intervention measures, optimal social distancing never recovers more than 30% of the cost of infection. We also show how the window of opportunity for vaccine development lengthens as the efficiency of social distancing and detection improve

Emergence of Carbapenem-Resistant Acinetobacter baumannii in Nursing Homes With High Background Rates of MRSA Colonization

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Involvement of reactive oxygen species and caspase-dependent pathway in berberine-induced cell cycle arrest and apoptosis in C6 rat glioma cells

[[abstract]]The cytotoxicity of berberine on C6 rat glioma cells indicated that berberine induced morphological changes and caused cell death through G2/M arrest and apoptosis. While undergoing apoptosis, there was a remarkable accumulation of G2/M cells with the upregulatoin of Weel but it also inhibited cyclin B, CDK1 and Cdc25c that led to G2/M arrest. Along with cytotoxicity in C6 cells, several apoptotic events including mitochondrial cytochrome c release, activation of caspase-9, -3 and -8 and DNA fragmentation were induced. Berberine increased the levels of GADD153 and GRP 78 in C6 cells based on the examination of Western blotting and this is a major hallmark of endoplasmic reticulum (ER) stress. We also found that berberine promoted the production of reactive oxygen species and Ca2+ in C6 cells. Western blotting assay also showed that berberine inhibited the levels of anti-apoptotic protein Bcl-2 but increased the levels of pro-apoptotic protein Bax before leading to a decrease in the levels of mitochondrial membrane potential (Delta psi(m)) followed by cytochrome c release that caused the activations of capase-9 and -3 for apoptotic occurrence. The caspase-8, -9 and -3 were activated by berberine in C6 cells based on the substrate solution (PhiPhiLux-G(1)D(1), CaspaLux 8-L1D2, CaspaLux 9-M1D2 for caspase-3, -8 and -9, respectively) and analyzed by flow cytometer and each inhibitor of caspase-8, -9 and -3 led to increase the percentage of viable C6 cells after exposure to berberine. This finding was also confirmed by Western blot assay which showed that berberine promoted the active form of caspase-8, -9 and -3. These results demonstrate that the cytotoxicity of berberine in C6 rat glioma cells is attributable to apoptosis mainly through induced G2/M-arrested cells, in an ER-dependent manner, via a mitochondria-dependent caspase pathway regulated by Bax and Bcl-2

Clustering based active learning for evolving data streams

Data labeling is an expensive and time-consuming task. Choosing which labels to use is increasingly becoming important. In the active learning setting, a classifier is trained by asking for labels for only a small fraction of all instances. While many works exist that deal with this issue in non-streaming scenarios, few works exist in the data stream setting. In this paper we propose a new active learning approach for evolving data streams based on a pre-clustering step, for selecting the most informative instances for labeling. We consider a batch incremental setting: when a new batch arrives, first we cluster the examples, and then, we select the best instances to train the learner. The clustering approach allows to cover the whole data space avoiding to oversample examples from only few areas. We compare our method w.r.t. state of the art active learning strategies over real datasets. The results highlight the improvement in performance of our proposal. Experiments on parameter sensitivity are also reported