Structural dissection of Ebola virus and its assembly determinants using cryo-electron tomography

Ebola virus is a highly pathogenic filovirus causing severe hemorrhagic fever with high mortality rates. It assembles heterogenous, filamentous, enveloped virus particles containing a negative-sense, single-stranded RNA genome packaged within a helical nucleocapsid (NC). We have used cryo-electron microscopy and tomography to visualize Ebola virus particles, as well as Ebola virus-like particles, in three dimensions in a near-native state. The NC within the virion forms a left-handed helix with an inner nucleoprotein layer decorated with protruding arms composed of VP24 and VP35. A comparison with the closely related Marburg virus shows that the N-terminal region of nucleoprotein defines the inner diameter of the Ebola virus NC, whereas the RNA genome defines its length. Binding of the nucleoprotein to RNA can assemble a loosely coiled NC-like structure; the loose coil can be condensed by binding of the viral matrix protein VP40 to the C terminus of the nucleoprotein, and rigidified by binding of VP24 and VP35 to alternate copies of the nucleoprotein. Four proteins (NP, VP24, VP35, and VP40) are necessary and sufficient to mediate assembly of an NC with structure, symmetry, variability, and flexibility indistinguishable from that in Ebola virus particles released from infected cells. Together these data provide a structural and architectural description of Ebola virus and define the roles of viral proteins in its structure and assembly

Cryo-electron tomography of Marburg Virus particles and their morphogenesis within infected cells

Several major human pathogens, including the filoviruses, paramyxoviruses, and rhabdoviruses, package their single-stranded RNA genomes within helical nucleocapsids, which bud through the plasma membrane of the infected cell to release enveloped virions. The virions are often heterogeneous in shape, which makes it difficult to study their structure and assembly mechanisms. We have applied cryo-electron tomography and sub-tomogram averaging methods to derive structures of Marburg virus, a highly pathogenic filovirus, both after release and during assembly within infected cells. The data demonstrate the potential of cryo-electron tomography methods to derive detailed structural information for intermediate steps in biological pathways within intact cells. We describe the location and arrangement of the viral proteins within the virion. We show that the N-terminal domain of the nucleoprotein contains the minimal assembly determinants for a helical nucleocapsid with variable number of proteins per turn. Lobes protruding from alternate interfaces between each nucleoprotein are formed by the C-terminal domain of the nucleoprotein, together with viral proteins VP24 and VP35. Each nucleoprotein packages six RNA bases. The nucleocapsid interacts in an unusual, flexible "Velcro-like" manner with the viral matrix protein VP40. Determination of the structures of assembly intermediates showed that the nucleocapsid has a defined orientation during transport and budding. Together the data show striking architectural homology between the nucleocapsid helix of rhabdoviruses and filoviruses, but unexpected, fundamental differences in the mechanisms by which the nucleocapsids are then assembled together with matrix proteins and initiate membrane envelopment to release infectious virions, suggesting that the viruses have evolved different solutions to these conserved assembly steps.

Analytical electron microscope investigation of boron carbide microstructures at elevated temperatures

The microstructures of hot-pressed B4C were monitored during in situ heating experiments from room temperature to 1000C by analytical electron microscopy (AEM). Variations in the microstructure of B4C were not observed. However, during heating, secondary phases formed in voids and on the surfaces of the specimen.

Vertical infrastructure inspection using a quadcopter and shared autonomy control

This paper presents a shared autonomy control scheme for a quadcopter that is suited for inspection of vertical infrastructure — tall man-made structures such as streetlights, electricity poles or the exterior surfaces of buildings. Current approaches to inspection of such structures is slow, expensive, and potentially hazardous. Low-cost aerial platforms with an ability to hover now have sufficient payload and endurance for this kind of task, but require significant human skill to fly. We develop a control architecture that enables synergy between the ground-based operator and the aerial inspection robot. An unskilled operator is assisted by onboard sensing and partial autonomy to safely fly the robot in close proximity to the structure. The operator uses their domain knowledge and problem solving skills to guide the robot in difficult to reach locations to inspect and assess the condition of the infrastructure. The operator commands the robot in a local task coordinate frame with limited degrees of freedom (DOF). For instance: up/down, left/right, toward/away with respect to the infrastructure. We therefore avoid problems of global mapping and navigation while providing an intuitive interface to the operator. We describe algorithms for pole detection, robot velocity estimation with respect to the pole, and position estimation in 3D space as well as the control algorithms and overall system architecture. We present initial results of shared autonomy of a quadrotor with respect to a vertical pole and robot performance is evaluated by comparing with motion capture data.

SERS substrate for detection of explosives

A novel gold coated femtosecond laser nanostructured sapphire surface – an “optical nose” - based on surface-enhanced Raman spectroscopy (SERS) for detecting vapours of explosive substances was investigated. Four different nitroaromatic vapours at room temperature were tested. Sensor responses were unambiguous and showed response in the range of 0.05 – 15 uM at 25 °C. The laser fabricated substrate nanostructures produced up to an eight-fold increase in Raman signal over that observed on the unstructured portions of the substrate. This work demonstrates a simple sensing system that is compatible with commercial manufacturing practices to detect taggants in explosives which can undertake as part of an integrated security or investigative mission.

SAIVT-QUT@TRECVid 2012 : interactive surveillance event detection

In this paper, we propose an approach which attempts to solve the problem of surveillance event detection, assuming that we know the definition of the events. To facilitate the discussion, we first define two concepts. The event of interest refers to the event that the user requests the system to detect; and the background activities are any other events in the video corpus. This is an unsolved problem due to many factors as listed below: 1) Occlusions and clustering: The surveillance scenes which are of significant interest at locations such as airports, railway stations, shopping centers are often crowded, where occlusions and clustering of people are frequently encountered. This significantly affects the feature extraction step, and for instance, trajectories generated by object tracking algorithms are usually not robust under such a situation. 2) The requirement for real time detection: The system should process the video fast enough in both of the feature extraction and the detection step to facilitate real time operation. 3) Massive size of the training data set: Suppose there is an event that lasts for 1 minute in a video with a frame rate of 25fps, the number of frames for this events is 60X25 = 1500. If we want to have a training data set with many positive instances of the event, the video is likely to be very large in size (i.e. hundreds of thousands of frames or more). How to handle such a large data set is a problem frequently encountered in this application. 4) Difficulty in separating the event of interest from background activities: The events of interest often co-exist with a set of background activities. Temporal groundtruth typically very ambiguous, as it does not distinguish the event of interest from a wide range of co-existing background activities. However, it is not practical to annotate the locations of the events in large amounts of video data. This problem becomes more serious in the detection of multi-agent interactions, since the location of these events can often not be constrained to within a bounding box. 5) Challenges in determining the temporal boundaries of the events: An event can occur at any arbitrary time with an arbitrary duration. The temporal segmentation of events is difficult and ambiguous, and also affected by other factors such as occlusions.

Analyzing the effectiveness of graph metrics for anomaly detection in online social networks

Online social networks can be modelled as graphs; in this paper, we analyze the use of graph metrics for identifying users with anomalous relationships to other users. A framework is proposed for analyzing the effectiveness of various graph theoretic properties such as the number of neighbouring nodes and edges, betweenness centrality, and community cohesiveness in detecting anomalous users. Experimental results on real-world data collected from online social networks show that the majority of users typically have friends who are friends themselves, whereas anomalous users’ graphs typically do not follow this common rule. Empirical analysis also shows that the relationship between average betweenness centrality and edges identifies anomalies more accurately than other approaches.

Static analysis of executables for collaborative malware detection on Android

Smartphones are getting increasingly popular and several malwares appeared targeting these devices. General countermeasures to smartphone malwares are currently limited to signature-based antivirus scanners which efficiently detect known malwares, but they have serious shortcomings with new and unknown malwares creating a window of opportunity for attackers. As smartphones become host for sensitive data and applications, extended malware detection mechanisms are necessary complying with the corresponding resource constraints. The contribution of this paper is twofold. First, we perform static analysis on the executables to extract their function calls in Android environment using the command readelf. Function call lists are compared with malware executables for classifying them with PART, Prism and Nearest Neighbor Algorithms. Second, we present a collaborative malware detection approach to extend these results. Corresponding simulation results are presented.

An Android application sandbox system for suspicious software detection

Smartphones are steadily gaining popularity, creating new application areas as their capabilities increase in terms of computational power, sensors and communication. Emerging new features of mobile devices give opportunity to new threats. Android is one of the newer operating systems targeting smartphones. While being based on a Linux kernel, Android has unique properties and specific limitations due to its mobile nature. This makes it harder to detect and react upon malware attacks if using conventional techniques. In this paper, we propose an Android Application Sandbox (AASandbox) which is able to perform both static and dynamic analysis on Android programs to automatically detect suspicious applications. Static analysis scans the software for malicious patterns without installing it. Dynamic analysis executes the application in a fully isolated environment, i.e. sandbox, which intervenes and logs low-level interactions with the system for further analysis. Both the sandbox and the detection algorithms can be deployed in the cloud, providing a fast and distributed detection of suspicious software in a mobile software store akin to Google's Android Market. Additionally, AASandbox might be used to improve the efficiency of classical anti-virus applications available for the Android operating system.

Collaborative intrusion detection framework : characteristics, adversarial opportunities and countermeasures

Complex Internet attacks may come from multiple sources, and target multiple networks and technologies. Nevertheless, Collaborative Intrusion Detection Systems (CIDS) emerges as a promising solution by using information from multiple sources to gain a better understanding of objective and impact of complex Internet attacks. CIDS also help to cope with classical problems of Intrusion Detection Systems (IDS) such as zero-day attacks, high false alarm rates and architectural challenges, e. g., centralized designs exposing the Single-Point-of-Failure. Improved complexity on the other hand gives raise to new exploitation opportunities for adversaries. The contribution of this paper is twofold. We first investigate related research on CIDS to identify the common building blocks and to understand vulnerabilities of the Collaborative Intrusion Detection Framework (CIDF). Second, we focus on the problem of anonymity preservation in a decentralized intrusion detection related message exchange scheme. We use techniques from design theory to provide multi-path peer-to-peer communication scheme where the adversary can not perform better than guessing randomly the originator of an alert message.

Electron paramagnetic resonance, optical absorption and Raman spectral studies on a pyrite/chalcopyrite mineral

Pyrite and chalcopyrite mineral samples from Mangampet barite mine, Kadapa, Andhra Pradesh, India are used in the present study. XRD data indicate that the pyrite mineral has a face centered cubic lattice structure with lattice constant 5.4179 Å. Also it possesses an average particle size of 91.9 nm. An EPR study on the powdered samples confirms the presence of iron in pyrite and iron and Mn(II) in chalcopyrite. The optical absorption spectrum of chalcopyrite indicates presence of copper which is in a distorted octahedral environment. NIR results confirm the presence of water fundamentals and Raman spectrum reveals the presence of water and sulfate ions.

Framework for evaluating collaborative intrusion detection systems

Securing IT infrastructures of our modern lives is a challenging task because of their increasing complexity, scale and agile nature. Monolithic approaches such as using stand-alone firewalls and IDS devices for protecting the perimeter cannot cope with complex malwares and multistep attacks. Collaborative security emerges as a promising approach. But, research results in collaborative security are not mature, yet, and they require continuous evaluation and testing. In this work, we present CIDE, a Collaborative Intrusion Detection Extension for the network security simulation platform ( NeSSi 2 ). Built-in functionalities include dynamic group formation based on node preferences, group-internal communication, group management and an approach for handling the infection process for malware-based attacks. The CIDE simulation environment provides functionalities for easy implementation of collaborating nodes in large-scale setups. We evaluate the group communication mechanism on the one hand and provide a case study and evaluate our collaborative security evaluation platform in a signature exchange scenario on the other.

Influence of electrolyte cations on electron transport and electron transfer in dye-sensitized solar cells

The influence of different electrolyte cations ((Li+, Na+, Mg2+, tetrabutyl ammonium (TBA+)) on the TiO2 conduction band energy (Ec) the effective electron lifetime (τn), and the effective electron diffusion coefficient (Dn) in dye-sensitized solar cells (DSCs) was studied quantitatively. The separation between Ec and the redox Fermi level, EF,redox, was found to decrease as the charge/radius ratio of the cations increased. Ec in the Mg2+ electrolyte was found to be 170 meV lower than that in the Na+ electrolyte and 400 meV lower than that in the TBA+ electrolyte. Comparison of Dn and τn in the different electrolytes was carried out by using the trapped electron concentration as a measure of the energy difference between Ec and the quasi-Fermi level, nEF, under different illumination levels. Plots of Dn as a function of the trapped electron density, nt, were found to be relatively insensitive to the electrolyte cation, indicating that the density and energetic distribution of electron traps in TiO2 are similar in all of the electrolytes studied. By contrast, plots of τn versus nt for the different cations showed that the rate of electron back reaction is more than an order of magnitude faster in the TBA+ electrolyte compared with the Na+ and Li+ electrolytes. The electron diffusion lengths in the different electrolytes followed the sequence of Na+ > Li+ > Mg2+ > TBA+. The trends observed in the AM 1.5 current–voltage characteristics of the DSCs are rationalized on the basis of the conduction band shifts and changes in electron lifetime.

Detection of banana bunchy top virus in virus-infected plants using polymerase chain reaction

Polymerase chain reaction (PCR) was developed for the detection of Banana bunchy top virus (BBTV) at maximum after 210 min and at minimum after 90 min using Pc-1 and Pc-2, respectively. PCR detection of BBTV in crude sap indicated that the freezing of banana tissue in liquid nitrogen (LN2) before extraction was more effective than using sand as the extraction technique. BBTV was also detected using PCR assay in 69 healthy and diseased plants using Na-PO4 buffer containing 1 % SDS. PCR detection of BBTV in nucleic acid extracts using seven different extraction buffers to adapt the use of PCR in routine detection in the field was studied. Results proved that BBTV was detected with high sensitivity in nucleic acid extracts more than in infectious sap. The results also suggested the common aetiology for the BBTV by the PCR reactions of BBTV in nucleic acid extracts from Australia, Burundi, Egypt, France, Gabon, Philippines and Taiwan. Results also proved a positive relation between the Egyptian-BBTV isolate and abaca bunchy top isolate from the Philippines, but there no relation was found with the Cucumber mosaic cucumovirus (CMV) isolates from Egypt and Philippines and Banana bract mosaic virus (BBMV) were found.

Decentralized detector generation in cooperative intrusion detection system

We consider Cooperative Intrusion Detection System (CIDS) which is a distributed AIS-based (Artificial Immune System) IDS where nodes collaborate over a peer-to-peer overlay network. The AIS uses the negative selection algorithm for the selection of detectors (e.g., vectors of features such as CPU utilization, memory usage and network activity). For better detection performance, selection of all possible detectors for a node is desirable but it may not be feasible due to storage and computational overheads. Limiting the number of detectors on the other hand comes with the danger of missing attacks. We present a scheme for the controlled and decentralized division of detector sets where each IDS is assigned to a region of the feature space. We investigate the trade-off between scalability and robustness of detector sets. We address the problem of self-organization in CIDS so that each node generates a distinct set of the detectors to maximize the coverage of the feature space while pairs of nodes exchange their detector sets to provide a controlled level of redundancy. Our contribution is twofold. First, we use Symmetric Balanced Incomplete Block Design, Generalized Quadrangles and Ramanujan Expander Graph based deterministic techniques from combinatorial design theory and graph theory to decide how many and which detectors are exchanged between which pair of IDS nodes. Second, we use a classical epidemic model (SIR model) to show how properties from deterministic techniques can help us to reduce the attack spread rate.