A new genus and new species of fan worms (Polychaeta: Sabellidae) from Atlantic and Pacific Oceans-the formal treatment of taxon names as explanatory hypotheses

Members of Parasabella minuta Treadwell, 1941, subsequently moved to Perkinsiana, were collected during a survey of rocky intertidal polychaetes along the state of Sao Paulo, Brazil. Additional specimens, which are referred to two new species, were also found in similar habitats from the Bocas del Toro Archipelago, Caribbean Panama, and Oahu Island, Hawaii. A phylogenetic analysis of Sabellinae, including members of P. minuta and the two new species, provided justification for establishing a new generic hypothesis, Sabellomma gen. nov., for these individuals. Formal definitions are also provided for Sabellomma minuta gen. nov., comb. nov., S. collinae gen. nov., spec. nov., and S. harrisae gen. nov., spec. nov., along with descriptions of individuals to which these hypotheses apply. The generic name Aracia nom. nov., is provided to replace Kirkia Nogueira, Lopez and Rossi, 2004, pre-occupied by a mollusk.

Detection of citrus canker in citrus plants using laser induced fluorescence spectroscopy

Citrus canker is a serious disease caused by Xanthomonas citri subsp. citri bacteria, which infects citrus plants (Citrus spp.) leading to a large economic loss in citrus production worldwide. In Brazil citrus canker control is done by an official eradication campaign, therefore early detection of such disease is important to prevent greater economic losses. However, detection is difficult and so far it has been done by visual inspection of each tree. Suspicious leaves from citrus plants in the field are sent to the laboratory to confirm the infection by laboratory analysis, which is a time consuming. Our goal was to develop a new optical technique to detect and diagnose citrus canker in citrus plants with a portable field spectrometer unit. In this paper, we review two experiments on laser induced fluorescence spectroscopy (LIF) applied to detect citrus canker. We also present new data to show that the length of time a leaf has been detached is an important variable in our studies. Our results show that LIF has the potential to be applied to citrus plants.

Protein variation in blood-dwelling schistosome worms generated by differential splicing of micro-exon gene transcripts

Schistosoma mansoni is a well-adapted blood-dwelling parasitic helminth, persisting for decades in its human host despite being continually exposed to potential immune attack. Here, we describe in detail micro-exon genes (MEG) in S. mansoni, some present in multiple copies, which represent a novel molecular system for creating protein variation through the alternate splicing of short (<= 36 bp) symmetric exons organized in tandem. Analysis of three closely related copies of one MEG family allowed us to trace several evolutionary events and propose a mechanism for micro-exon generation and diversification. Microarray experiments show that the majority of MEGs are up-regulated in life cycle stages associated with establishment in the mammalian host after skin penetration. Sequencing of RT-PCR products allowed the description of several alternate splice forms of micro-exon genes, highlighting the potential use of these transcripts to generate a complex pool of protein variants. We obtained direct evidence for the existence of such pools by proteomic analysis of secretions from migrating schistosomula and mature eggs. Whole-mount in situ hybridization and immunolocalization showed that MEG transcripts and proteins were restricted to glands or epithelia exposed to the external environment. The ability of schistosomes to produce a complex pool of variant proteins aligns them with the other major groups of blood parasites, but using a completely different mechanism. We believe that our data open a new chapter in the study of immune evasion by schistosomes, and their ability to generate variant proteins could represent a significant obstacle to vaccine development.

User perceptions and acceptance of benevolent worms - a matter of fear?

Worms and other forms of malware have been considered by IT Security firms and large companies for many years as one of the leading threats to the integrity of their data and security. However, several researchers over recent years have been working on creating worms which, instead of causing harm to machines which they infect, or the networks on which the machines reside, actually aid the network and systems administrators. Several uses of these worms have been proposed by these researchers, including, but not limited to, rapid remote patching of machines, network and system administration through use of their unique discovery and propagation methods, actively hunting, and defending against, other forms of malware such as "malevolent" worms, viruses, spyware, as well as increasing reliable communication of nodes in distributed computing. However, there has been no hint of commercial adoption of these worms, which one researcher has described as being due to a fear factor'. This paper concentrates on assessing and delivering the findings of user attitudes towards these worms in an attempt to find out how users feel about these worms, and to try and define and overcome the factors which might contribute to the fear factor'.

Modeling the propagation of peer-to-peer worms

Propagation of Peer-to-Peer (P2P) worms in the Internet is posing a serious challenge to network security research because of P2P worms' increasing complexity and sophistication. Due to the complexity of the problem, no existing work has solved the problem of modeling the propagation of P2P worms, especially when quarantine of peers is enforced. This paper presents a study on modeling the propagation of P2P worms. It also presents our applications of the proposed approach in worm propagation research.

Motivated by our aspiration to invent an easy-to-employ instrument for worm propagation research, the proposed approach models the propagation processes of P2P worms by difference equations of a logic matrix, which are essentially discrete-time deterministic propagation models of P2P worms. To the best of our knowledge, we are the first using a logic matrix in network security research in general and worm propagation modeling in particular.

Our major contributions in this paper are firstly, we propose a novel logic matrix approach to modeling the propagation of P2P worms under three different conditions; secondly, we find the impacts of two different topologies on a P2P worm's attack performance; thirdly, we find the impacts of the network-related characteristics on a P2P worm's attack performance in structured P2P networks; and fourthly, we find the impacts of the two different quarantine tactics on the propagation characteristics of P2P worms in unstructured P2P networks. The approach's ease of employment, which is demonstrated by its applications in our simulation experiments, makes it an attractive instrument to conduct worm propagation research.

Modeling worms propagation on probability

There are the two common means for propagating worms: scanning vulnerable computers in the network and sending out malicious email attachments. Modeling the propagation of worms can help us understand how worms spread and devise effective defence strategies. Most traditional models simulate the overall scale of infected network in each time tick, making them invalid for examining deep inside the propagation procedure among individual nodes. For this reason, this paper proposes a novel probability matrix to model the propagation mechanism of the two main classes of worms (scanning and email worms) by concentrating on the propagation probability. The objective of this paper is to access the spreading and work out an effective scheme against the worms. In order to evaluate the effects of each major component in our probability model, we implement a series of experiments for both worms. From the results, the network administrators can make decision on how to reduce the number of vulnerable nodes to a certain threshold for scanning worms, and how to immunize the highly-connected node for preventing worm's propagation for email worms.

Locating defense positions for thwarting the propagation of topological worms

A common view for the preferable positions of thwarting worm propagation is at the highly connected nodes. However, in certain conditions, such as when some popular users (highly connected nodes in the network) have more vigilance on the malicious codes, this may not always be the truth. In this letter, we propose a measure of betweenness and closeness to locate the most suitable positions for slowing down the worm propagation. This work provides practical values to the defense of topological worms.

Modeling and defense against propagation of worms in networks

Worms are widely believed to be one of the most serious challenges in network security research. In order to prevent worms from propagating, we present a microcosmic model, which can benefit the security industry by allowing them to save significant money in the deployment of their security patching schemes.

An analytical model on the propagation of modern email worms

Email worms propagate across networks by taking advantage of email relationships. Modeling the propagation of email worms can help predict their potential damages and develop countermeasures. We propose a novel analytical model on the propagation process of modern reinfection email worms. It relies on probabilistic analysis, and thus can provide a steady and reliable assessment on the propagation dynamics. Additionally, by introducing virtual users to represent the repetitious spreading process, the proposed model overcomes the computational challenge caused by reinfection processes. To demonstrate the benefits of our model, we conduct a series of experimental evaluation. The results show that our novel approach achieves a greater accuracy and is more suitable for modeling modern email worms than previous models.

Modeling propagation dynamics of social network worms

Social network worms, such as email worms and facebook worms, pose a critical security threat to the Internet. Modeling their propagation dynamics is essential to predict their potential damages and develop countermeasures. Although several analytical models have been proposed for modeling propagation dynamics of social network worms, there are two critical problems unsolved: temporal dynamics and spatial dependence. First, previous models have not taken into account the different time periods of Internet users checking emails or social messages, namely, temporal dynamics. Second, the problem of spatial dependence results from the improper assumption that the states of neighboring nodes are independent. These two problems seriously affect the accuracy of the previous analytical models. To address these two problems, we propose a novel analytical model. This model implements a spatial-temporal synchronization process, which is able to capture the temporal dynamics. Additionally, we find the essence of spatial dependence is the spreading cycles. By eliminating the effect of these cycles, our model overcomes the computational challenge of spatial dependence and provides a stronger approximation to the propagation dynamics. To evaluate our susceptible-infectious-immunized (SII) model, we conduct both theoretical analysis and extensive simulations. Compared with previous epidemic models and the spatial-temporal model, the experimental results show our SII model achieves a greater accuracy. We also compare our model with the susceptible-infectious-susceptible and susceptible-infectious- recovered models. The results show that our model is more suitable for modeling the propagation of social network worms.

A data mining approach for detection of self-propagating worms

In this paper we demonstrate our signature based detector for self-propagating worms. We use a set of worm and benign traffic traces of several endpoints to build benign and worm profiles. These profiles were arranged into separate n-ary trees. We also demonstrate our anomaly detector that was used to deal with tied matches between worm and benign trees. We analyzed the performance of each detector and also with their integration. Results show that our signature based detector can detect very high true positive. Meanwhile, the anomaly detector did not achieve high true positive. Both detectors, when used independently, suffer high false positive. However, when both detectors were integrated they maintained a high detection rate of true positive and minimized the false positive

Opening up a can of worms: how do decision-makers decide when witnesses are telling the truth?

Correctly determining witness credibility is integral to a fair trial. Assessments of credibility made by the triers of fact are made, amongst other things, by reference to behavioural stereotypes that are commonly thought to be associated with lying and truth-telling. These stereotypes are worthless but pervasive. In this study, potential jurors were given information such as would be given by way of judicial direction and/or expert testimony on those behavioural indicia that are useful in detecting deception. Major changes in perceptions of what does and does not work were found. This has significant implications for the conduct of criminal trials. Recommendations are presented which, it is argued, can be of real, practical, assistance in enabling decision-makers to assess the credibility of witnesses. © 2013 The Australian and New Zealand Association of Psychiatry, Psychology and Law.