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866 results for “attack”
Linked collectors and determiners for: Cryptic biodiversity of tropical hesperiid caterpillar-attacking parasitoid wasps: three new species of Creagrura Townes (Hymenoptera, Ichneumonidae, Cremastinae) from Costa Rica and Perú.
Natural history specimen data linked to collectors and determiners held within, "Cryptic biodiversity of tropical hesperiid caterpillar-attacking parasitoid wasps: three new species of Creagrura Townes (Hymenoptera, Ichneumonidae, Cremastinae) from Costa Rica and Perú". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/01014af1-0a18-413a-a9df-636469c183fa">https://bionomia.net/dataset/01014af1-0a18-413a-a9df-636469c183fa</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/01014af1-0a18-413a-a9df-636469c183fa">https://gbif.org/dataset/01014af1-0a18-413a-a9df-636469c183fa</a>. Formatted as a Frictionless Data package.
Figure 3. A male attacker waiting beside a in ''Riding'' behaviour by males of Conops quadrifasciata (Diptera: Conopidae): Do females set up ''riders'' as targets for takeovers by larger males?
Figure 3. A male attacker waiting beside a rider who is engaged in a repeat copulation. Both males are about the same size.
Figures 1–9 in A new species of Aphidius Nees, 1818 (Hymenoptera, Braconidae, Aphidiinae) attacking Uroleucon aphids (Homoptera, Aphididae) from Iran and Iraq
Figures 1–9. Aphidius persicus sp. n. (1–8) Paratype female. (1) Head and mouthparts. (2) First and apical antennal flagellomeres. (3) Mesonotum. (4) Fore wing. (5) Propodeum. (6) Tergum 1, dorsal view. (7) Tergum 1, lateral view. (8) Genitalia. (9) Paratype male: aedeagus.
Dataset related to article "ANTIHYPERTENSIVE DRUGS FOR SECONDARY PREVENTION AFTER ISCHEMIC STROKE OR TRANSIENT ISCHEMIC ATTACK"
<p>we performed a systematic review and meta-analysis in order to summarize the current evidence on blood pressure (BP)-lowering drugs for secondary prevention in patients with ischemic stroke or transient ischemic attack. We searched MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials up to January 31, 2020. We included randomized controlled trials comparing any specific BP-lowering drug, as monotherapy or combination, with either a control or another BP-lowering drug. Eight studies that enrolled 33 774 patients with ischemic stroke or transient ischemic attack were included in the meta-analysis. Primary outcomes were all-cause mortality and the proportion of patients who developed a stroke following BP-lowering drug use, irrespective of its nature (ischemic or hemorrhagic) and severity. Secondary outcomes included the proportion of patients who developed an ischemic stroke; an ischemic stroke or TIA irrespective of severity; a hemorrhagic stroke, defined as an acute extravasation of blood into and around the brain parenchyma (subdural hematoma and epidural hematoma were excluded); a cardiovascular event defined as any sudden death, fatal or nonfatal acute coronary syndrome, stroke, intracranial hemorrhage, or pulmonary embolism; a fatal cardiovascular event defined as any death due to any vascular cause, including unexplained sudden death; and serious adverse events of hypotension, syncope, injurious falls, electrolyte abnormalities, bradycardia, or acute renal failure. We recorded the outcomes at the longest available follow-up for all analyses. We considered the following potential sources of heterogeneity (effect modifiers): inclusion limited to hypertensive patients (normotensive and hypertensive patients versus hypertensive patients only) or noncardioembolic ischemic strokes (all ischemic strokes versus noncardioembolic ischemic strokes only), time from the index ischemic event to randomization (acute patients treated within the first week versus stabilized patients treated after the first week), and trial risk of bias.</p>
SSH Username Enumeration Attack Detection Dataset
<p>The dataset is collected from a closed-environment network using network monitoring tools installed in the data collection point. The dataset generation was achieved through the use of common vulnerabilities and exposures (CVE) with the identification number CVE-2018-15473 retrieved from the public exploits database and pcap file of normal traffic obtained from public training repository. A total of 36,273 instances were collected with two classes <em>“username enumeration attack”</em> and “<em>non-username enumeration</em>”. We chose the terms <em>“username enumeration attack”</em> and “<em>non-username enumeration</em>” instead of the traditional <em>“attack”</em> and <em>“normal”</em> label notations since <em>“</em>normal<em>”</em> traffic data could contain attacks other than username enumeration attack.</p> <p>The username enumeration attack corresponds to the attack traffic while non-username enumeration traffic corresponds to the normal traffic. This traffic reflects different services including emails, DNS, HTTP, web, few to mention. Several data preprocessing techniques were carried out including categorical encoding. Both label encoding and one hot encoding techniques were used to transform categorical feature values into numerical feature values. Hence, two types of datasets were generated. </p>
Application of hyperbolic geometry of multiplex networks under layer link-based attacks
<p>As real multilayer networks, we consider four networks. The multilayer networks are converted to multiplex networks by assuming that all layers have the same number of nodes (the maximum number of nodes of all layers). Explanation of these networks is as follow:</p> <ol> <li><em>CS-Aarhus_multiplex [1]</em> : The first network used in this study is a 5-layer multiplex network, named CS-Aarhus_multiplex, which has 61 nodes and 620 edges. The multiplex social network consists of five kinds of online and offline relationships (Facebook, Leisure, Work, Co-authorship, Lunch) between the employees of the Computer Science department at Aarhus.</li> <li><em>Data_malaria_PLOSCompBiology_2013 [2]</em>: The second network is a 9-layer multiplex network, which consists of 307 nodes and 35306 edges. Networks of recombinant antigen genes from the human malaria parasite P. falciparum. Each of the 9 networks shares the same set of vertices but has different edges, corresponding to the 9 highly variable regions (HVRs) in the DBLa domain of the var protein. Nodes are var genes, and two genes are connected if they share a substring whose length is statistically significant.</li> <li>VICKERS CHAN 7th-GRADERS [3] : The third network is a 3-layer multiplex network, called VICKERS CHAN 7th-GRADERS, which includes 29 nodes and 740 edges. The data were collected by Vickers from 29 seventh-grade students in a school in Victoria, Australia. Students were asked to nominate their classmates on several relations including the three layers.</li> </ol> <p> 4. FAO MULTIPLEX TRADE NETWORK [4]: The fourth network is a 364-layer multiplex network, which contains 214 nodes and 318346 edges. We consider different types of trade relationships among countries, obtained from FAO (Food and Agriculture Organization of the United Nations)</p>
Dataset for the paper "Website Fingerprinting: Attacking Popular Privacy Enhancing Technologies with the Multinomial Naïve-Bayes Classifier"
<p>This dataset contains website fingerprints of 775 websites analyzed in the paper "Website Fingerprinting: Attacking Popular Privacy Enhancing Technologies with the Multinomial Naïve-Bayes Classifier" published in the Proceedings of the 2009 ACM workshop on Cloud computing security (CCSW 2009, DOI: 10.1145/1655008.1655013).</p>
CTU-AIP-Attacks-2022
<p>The CTU-AIP-Attacks-2022 dataset aggregates network attacks of 27 bare-metal Internet of Things (IoT) honeypots. The IoT devices were located in the same physical location. The data were captured from January 1st, 2022, to December 31st, 2023.<br> <br> The raw network attacks were captured using Zeek [1], an open-source software network analysis framework. The raw network data was processed to aggregate network attacks. The network data was aggregated by the source IP address of the attacker per day. For each attacker, the following data were aggregated:</p> <ul> <li>date: Date of the aggregation, in YYYY-MM-DD format</li> <li>orig: IP address attacking the IoT honeypots</li> <li>flows: Sum of all network flows from the attacking IP address to the IoT honeypots, calculated as the number of times the same IP (id.orig_h) appears in the Zeek conn.log file.</li> <li>duration: Sum of the "duration" column [2] of the Zeek conn.log file for all the rows with the same IP in the column "id.orig_h". In Zeek, this column is the duration from the first packet to the last packet in the network flow.</li> <li>packets: Sum of the "orig_pkts" column [2] for all the rows with the same IP in the "id.orig_h" column. In Zeek, this column counts the number of packets sent by the originator, and not the total number of packets.</li> <li>bytes: Sum of the "orig_bytes" column [2] for all the rows with the same IP in the "id.orig_h" column. In Zeek, this column counts the number of bytes sent by the originator, and not the total number of bytes.</li> </ul> <p><br> Every connection initiated by any IP to the honeypots is, by definition, an attack. However, we use an active probe service to alert when a honeypot is down. We removed those IPs corresponding to the probes. The list of IPs removed can be found listed below.</p> <p>The resulting dataset is composed of one CSV file per day. The excerpt below shows a sample of one of the dataset files: </p> <pre><code>~ $ zcat attacks.2022-04-04.csv.gz | head -n20 # This file is part of the CTU-AIP-Attacks-2022 dataset # Version: 1.0 # Publication Date: 2023-03 # Authors: Joaquin Bogado, Veronica Valeros, Sebastian Garcia # Institution: Stratosphere Laboratory, AIC, FEL, Czech Technical University in Prague # DOI: 10.5281/zenodo.7684550 # Zenodo: https://zenodo.org/record/7684550/ # Source: https://mcfp.felk.cvut.cz/publicDatasets/CTU-AIP-Attacks-2022/ date,orig,flows,duration,packets,bytes 2022-04-04,1.0.234.65,1,5e-06,2,104 2022-04-04,1.10.172.211,1,0.0,1,52 2022-04-04,1.116.138.182,1,4.7e-05,2,80 2022-04-04,1.116.243.210,1,3e-06,2,80 2022-04-04,1.116.37.121,1,2e-06,2,80 2022-04-04,1.116.67.192,24,0.000173,48,1920 2022-04-04,1.116.73.236,22,0.000173,43,1720 2022-04-04,1.116.97.146,1,1e-06,2,120 2022-04-04,1.117.107.145,1,3e-06,2,126 2022-04-04,1.117.199.237,1,5e-06,2,80 2022-04-04,1.12.255.18,2,2e-05,4,160</code></pre> <p><br> <strong>Tools</strong><br> Zeek connection logs were processed using the [AIP](https://github.com/stratosphereips/AIP) tool to generate the aggregated data for this dataset. Zeek version 2.6-264 and AIP version 2.0 were used.<br> <br> <strong>Data cleaning</strong><br> The IPs removed from the dataset corresponding to the active probe service were:</p> <pre><code>104.131.107.63 122.248.234.23 128.199.195.156 138.197.150.151 139.59.173.249 146.185.143.14 159.203.30.41 159.89.8.111 165.227.83.148 167.99.209.234 178.62.52.237 18.221.56.27 216.245.221.83 216.245.221.91 34.233.66.117 46.101.250.135 46.137.190.132 52.60.129.180 54.64.67.106 54.67.10.127 54.79.28.129 54.94.142.218 63.143.42.242 63.143.42.251 69.162.124.237</code></pre> <p><br> <strong>Contact</strong><br> For information or questions about this dataset, contact us at stratosphere@aic.fel.cvut.cz with the subject: CTU-AIP-Attacks-2022.<br> <br> <strong>References</strong><br> [1] The Zeek Network Security Monitor, https://zeek.org/. Accessed on 03/03/2023. <br> [2] base/protocols/conn/main.zeek -- Book of Zeek (git/master), https://docs.zeek.org/en/master/scripts/base/protocols/conn/main.zeek.html. Accessed on 03/03/2023.<br> </p>
Towards Efficient Training in Deep Learning Side-Channel Attacks
<p>Datasets used to develop my Master's Thesis <em>Towards Efficient Training in Deep Learning Side-Channel Attacks</em> at Politecnico di Milano. </p> <p>The datasets contain power consumption measurements taken from multiple <em>Riscure Piñata </em>(STM32F4) boards (3) considering multiple keys (11) while executing AES-128.</p> <p>unprotected-AES.zip contains the traces related to the execution of a software unprotected implementation of AES-128.</p> <p>masked-AES.zip contains the traces related to the execution of a software masked implementation of AES-128.</p>
L-TOWN simulated measurement without faults or cyber-attacks for scenarios with masking
<p>Additional resources for repository <a href="https://github.com/asztyber/wdn-simulation">asztyber/wdn-simulation</a></p> <p>Required to run scenarios with masking.</p>
Virtual prey with Lévy motion are preferentially attacked by predatory fish
<p>Of widespread interest in animal behaviour and ecology is how animals search their environment for resources, and whether these search strategies are optimal. However, movement also affects predation risk through effects on encounter rates, the conspicuousness of prey, and the success of attacks. Here we use predatory fish attacking a simulation of virtual prey to test whether predation risk is associated with movement behaviour. Despite often being demonstrated to be a more efficient strategy for finding resources such as food, we find that prey displaying Lévy motion are twice as likely to be targeted by predators than prey utilising Brownian motion. This can be explained by the predators, at the moment of the attack, preferentially targeting prey that were moving with straighter trajectories rather than prey that were turning more. Our results emphasise that costs of predation risk need to be considered alongside the foraging benefits when comparing different movement strategies.</p>
Figs 7–9 in Revision of Ceranisus and the related thrips-attacking entedonine genera (Hymenoptera: Eulophidae) of the world
Figs 7–9. Entedonomphale quasimodo sp. n., female (holotype): (7) body (habitus), (8) antenna, (9) forewing, Scale lines = 0.1 mm.
Figs 36–38 in Revision of Ceranisus and the related thrips-attacking entedonine genera (Hymenoptera: Eulophidae) of the world
Figs 36–38. Ceranisus barsoomensis sp. n., female (holotype): (36) antenna, (37) forewing, (38) ovipositor. Scale lines = 0.1 mm.
Figs 1–3 in Revision of Ceranisus and the related thrips-attacking entedonine genera (Hymenoptera: Eulophidae) of the world
Figs 1–3. Goetheana rabelaisi sp. n., male: (1, 2) holotype: (1) antenna, (2) forewing; (3) genitalia (paratype). Scale lines = 0.1 mm.
Figs 4–6 in Revision of Ceranisus and the related thrips-attacking entedonine genera (Hymenoptera: Eulophidae) of the world
Figs 4–6. Goetheana pushkini sp. n.: (4, 5) female (holotype): (4) antenna, (5) forewing; (6) scape, male (paratype); Seoul National University, Seoudun-dong, Suwon-si, Republic of Korea. Scale lines = 0.1 mm.
Figs 40, 41 in Revision of Ceranisus and the related thrips-attacking entedonine genera (Hymenoptera: Eulophidae) of the world
Figs 40, 41. Ceranisus udnamtak sp. n., female (holotype): (40) antenna, (41) forewing. Scale lines = 0.1 mm.
Figs 24, 25 in Revision of Ceranisus and the related thrips-attacking entedonine genera (Hymenoptera: Eulophidae) of the world
Figs 24, 25. Entedonomphale dei, female (holotype): (24) antenna, (25) forewing. Scale lines = 0.1 mm.
Figs 19–21 in Revision of Ceranisus and the related thrips-attacking entedonine genera (Hymenoptera: Eulophidae) of the world
Figs 19–21. Entedonomphale kaulbarsi, male (Ottawa Airport, Ontario, Canada): (19) antenna, (20) forewing, (21) genitalia. Scale lines = 0.1 mm.
Figs 10–12 in Revision of Ceranisus and the related thrips-attacking entedonine genera (Hymenoptera: Eulophidae) of the world
Figs 10–12. Entedonomphale boccaccioi sp. n., female (holotype): (10) antenna, (11) forewing, (12) hind wing. Scale lines = 0.1 mm.
Figs 42–45 in Revision of Ceranisus and the related thrips-attacking entedonine genera (Hymenoptera: Eulophidae) of the world
Figs 42–45. Ceranisus votetoda sp. n.: (42, 43) female (holotype): (42) antenna, (43) forewing; (44, 45) male (paratype): (44) antenna, (45) genitalia. Scale lines = 0.1 mm.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.