2,053 research outputs found

    Analytic Provenance for Software Reverse Engineers

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    Reverse engineering is a time-consuming process essential to software-security tasks such as malware analysis and vulnerability discovery. During the process, an engineer will follow multiple leads to determine how the software functions. The combination of time and possible explanations makes it difficult for the engineers to maintain a context of their findings within the overall task. Analytic provenance tools have demonstrated value in similarly complex fields that require open-ended exploration and hypothesis vetting. However, they have not been explored in the reverse engineering domain. This dissertation presents SensorRE, the first analytic provenance tool designed to support software reverse engineers. A semi-structured interview with experts led to the design and implementation of the system. We describe the visual interfaces and their integration within an existing software analysis tool. SensorRE automatically captures user\u27s sense making actions and provides a graph and storyboard view to support further analysis. User study results with both experts and graduate students demonstrate that SensorRE is easy to use and that it improved the participants\u27 exploration process

    Covert Channels Within IRC

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    The exploration of advanced information hiding techniques is important to understand and defend against illicit data extractions over networks. Many techniques have been developed to covertly transmit data over networks, each differing in their capabilities, methods, and levels of complexity. This research introduces a new class of information hiding techniques for use over Internet Relay Chat (IRC), called the Variable Advanced Network IRC Stealth Handler (VANISH) system. Three methods for concealing information are developed under this framework to suit the needs of an attacker. These methods are referred to as the Throughput, Stealth, and Baseline scenarios. Each is designed for a specific purpose: to maximize channel capacity, minimize shape-based detectability, or provide a baseline for comparison using established techniques applied to IRC. The effectiveness of these scenarios is empirically tested using public IRC servers in Chicago, Illinois and Amsterdam, Netherlands. The Throughput method exfiltrates covert data at nearly 800 bits per second (bps) compared to 18 bps with the Baseline method and 0.13 bps for the Stealth method. The Stealth method uses Reed-Solomon forward error correction to reduce bit errors from 3.1% to nearly 0% with minimal additional overhead. The Stealth method also successfully evades shape-based detection tests but is vulnerable to regularity-based tests

    Meeting Report: Soybean Genomics Assessment and Strategy Workshop

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    http://www.soybiotechcenter.org/archives/?id=195&id2=12On July 19 - 20, 2005, approximately 50 researchers and administrators with expert knowledge of soybean genomics participated in a workshop in St.Louis, MO, which was hosted by the Soybean Genetics Executive Committee and supported by the United Soybean Board. The workshop began with a series of presentations by experts in the topics discussed below. Each presentation was designed to update the audience on the current status of soybean resources and related genomics technologies. Following the presentations the participants divided into discussion groups to assess the status of soybean genomics, identify needs, and identify milestones to achieve objectives. The discussion groups included the general areas of Functional Genomics A (Transcriptome and Proteome), Functional Genomic B (Reverse Genetics), Physical and Genetic Maps, and Bioinformatics. After each discussion section the entire group reconvened to hear group reports and to further discuss each topic. The following is the report from this Workshop. It represents a consensus of the participants of the Workshop and it is structured to integrate with a White Paper generated in 2003 so that progress can be better monitored over time. The results of this report are consistent with those of a National Science Foundation soybean genomics workshop held in 2004 (St. Louis, MO) and a Cross-Legume workshop also held in 2004 (Santa Fe, NM).National Science Foundatio

    Distribution of DDS-cerberus Authenticated Facial Recognition Streams

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    Successful missions in the field often rely upon communication technologies for tactics and coordination. One middleware used in securing these communication channels is Data Distribution Service (DDS) which employs a publish-subscribe model. However, researchers have found several security vulnerabilities in DDS implementations. DDS-Cerberus (DDS-C) is a security layer implemented into DDS to mitigate impersonation attacks using Kerberos authentication and ticketing. Even with the addition of DDS-C, the real-time message sending of DDS also needs to be upheld. This paper extends our previous work to analyze DDS-C’s impact on performance in a use case implementation. The use case covers an artificial intelligence (AI) scenario that connects edge sensors across a commercial network. Specifically, it characterizes how DDS-C performs between unmanned aerial vehicles (UAV), the cloud, and video streams for facial recognition. The experiments send a set number of video frames over the network using DDS to be processed by AI and displayed on a screen. An evaluation of network traffic using DDS-C revealed that it was not statistically significant compared to DDS for the majority of the configuration runs. The results demonstrate that DDS-C provides security benefits without significantly hindering the overall performance

    Quantifying DDS-cerberus Network Control Overhead

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    Securing distributed device communication is critical because the private industry and the military depend on these resources. One area that adversaries target is the middleware, which is the medium that connects different systems. This paper evaluates a novel security layer, DDS-Cerberus (DDS-C), that protects in-transit data and improves communication efficiency on data-first distribution systems. This research contributes a distributed robotics operating system testbed and designs a multifactorial performance-based experiment to evaluate DDS-C efficiency and security by assessing total packet traffic generated in a robotics network. The performance experiment follows a 2:1 publisher to subscriber node ratio, varying the number of subscribers and publisher nodes from three to eighteen. By categorizing the network traffic from these nodes into either data message, security, or discovery+ with Quality of Service (QoS) best effort and reliable, the mean security traffic from DDS-C has minimal impact to Data Distribution Service (DDS) operations compared to other network traffic. The results reveal that applying DDS-C to a representative distributed network robotics operating system network does not impact performance

    Genome based cell population heterogeneity promotes tumorigenicity: the evolutionary mechanism of cancer.

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    Cancer progression represents an evolutionary process where overall genome level changes reflect system instability and serve as a driving force for evolving new systems. To illustrate this principle it must be demonstrated that karyotypic heterogeneity (population diversity) directly contributes to tumorigenicity. Five well characterized in vitro tumor progression models representing various types of cancers were selected for such an analysis. The tumorigenicity of each model has been linked to different molecular pathways, and there is no common molecular mechanism shared among them. According to our hypothesis that genome level heterogeneity is a key to cancer evolution, we expect to reveal that the common link of tumorigenicity between these diverse models is elevated genome diversity. Spectral karyotyping (SKY) was used to compare the degree of karyotypic heterogeneity displayed in various sublines of these five models. The cell population diversity was determined by scoring type and frequencies of clonal and non-clonal chromosome aberrations (CCAs and NCCAs). The tumorigenicity of these models has been separately analyzed. As expected, the highest level of NCCAs was detected coupled with the strongest tumorigenicity among all models analyzed. The karyotypic heterogeneity of both benign hyperplastic lesions and premalignant dysplastic tissues were further analyzed to support this conclusion. This common link between elevated NCCAs and increased tumorigenicity suggests an evolutionary causative relationship between system instability, population diversity, and cancer evolution. This study reconciles the difference between evolutionary and molecular mechanisms of cancer and suggests that NCCAs can serve as a biomarker to monitor the probability of cancer progression

    Crystal structure of rhodopsin bound to arrestin by femtosecond X-ray laser.

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    G-protein-coupled receptors (GPCRs) signal primarily through G proteins or arrestins. Arrestin binding to GPCRs blocks G protein interaction and redirects signalling to numerous G-protein-independent pathways. Here we report the crystal structure of a constitutively active form of human rhodopsin bound to a pre-activated form of the mouse visual arrestin, determined by serial femtosecond X-ray laser crystallography. Together with extensive biochemical and mutagenesis data, the structure reveals an overall architecture of the rhodopsin-arrestin assembly in which rhodopsin uses distinct structural elements, including transmembrane helix 7 and helix 8, to recruit arrestin. Correspondingly, arrestin adopts the pre-activated conformation, with a ∼20° rotation between the amino and carboxy domains, which opens up a cleft in arrestin to accommodate a short helix formed by the second intracellular loop of rhodopsin. This structure provides a basis for understanding GPCR-mediated arrestin-biased signalling and demonstrates the power of X-ray lasers for advancing the frontiers of structural biology

    Alcohol-related brain damage in humans

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    Chronic excessive alcohol intoxications evoke cumulative damage to tissues and organs. We examined prefrontal cortex (Brodmann’s area (BA) 9) from 20 human alcoholics and 20 age, gender, and postmortem delay matched control subjects. H & E staining and light microscopy of prefrontal cortex tissue revealed a reduction in the levels of cytoskeleton surrounding the nuclei of cortical and subcortical neurons, and a disruption of subcortical neuron patterning in alcoholic subjects. BA 9 tissue homogenisation and one dimensional polyacrylamide gel electrophoresis (PAGE) proteomics of cytosolic proteins identified dramatic reductions in the protein levels of spectrin β II, and α- and β-tubulins in alcoholics, and these were validated and quantitated by Western blotting. We detected a significant increase in α-tubulin acetylation in alcoholics, a non-significant increase in isoaspartate protein damage, but a significant increase in protein isoaspartyl methyltransferase protein levels, the enzyme that triggers isoaspartate damage repair in vivo. There was also a significant reduction in proteasome activity in alcoholics. One dimensional PAGE of membrane-enriched fractions detected a reduction in β-spectrin protein levels, and a significant increase in transmembranous α3 (catalytic) subunit of the Na+,K+-ATPase in alcoholic subjects. However, control subjects retained stable oligomeric forms of α-subunit that were diminished in alcoholics. In alcoholics, significant loss of cytosolic α- and β-tubulins were also seen in caudate nucleus, hippocampus and cerebellum, but to different levels, indicative of brain regional susceptibility to alcohol-related damage. Collectively, these protein changes provide a molecular basis for some of the neuronal and behavioural abnormalities attributed to alcoholics
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