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734 results for “IP”
Dataset: Advanced Similarity Metrics for IP Flow Data Analytics
<p>Analysis of encrypted traffic in computer networks is intricate due to reduced visibility in transmitted content. Machine-learning techniques applied to data representing characteristics of traffic flows provide powerful tools for network monitoring or intrusion detection. Since real-world datasets are scarce, we present a novel traffic classification dataset with TLS traffic. The dataset contains three days (19-08-2022 -- 21-08-2022) of anonymized communication on CESNET3 ISP network, which is used by approximately half a million users daily.</p> <p><strong>Ethic statement </strong>The privacy of the CESNET network users is a fundamental concern in our work, leading us to conduct our research with careful consideration. The indisputable advantages of real traffic generated by hundreds of thousands of people come with understandable privacy concerns. Thus, we used only automatic data processing with immediate data anonymization. With this, we declare that we did not analyze or manually process non-anonymized data or perform any procedures that could allow us to track users or reveal their identities. </p> <p><strong>Data description</strong> The dataset consists of network flows describing encrypted TLS communications. Flows are extended with packet sequences, histograms, and fields extracted from the TLS ClientHello message, which is transmitted in the first packet of the TLS connection handshake. The most important extracted handshake field is the SNI domain, which is used for ground-truth labeling. </p> <p><strong>Packet Sequences</strong> Sequences of packet sizes, directions, and inter-packet times are standard data input for traffic analysis. For packet sizes, we consider the payload size after transport headers (TCP headers for the TLS case). We omit packets with no TCP payload, for example ACKs, because zero-payload packets are related to the transport layer internals rather than services’ behavior. Packet directions are encoded as ±1, where +1 means a packet sent from client to server, and -1 is a packet from server to client. Packet timing depends on the location of communicating hosts, their distance, and on the network conditions on the path. However, it is still possible to extract relevant information that correlates with user interactions and, for example, with the time required for an API/server/database to process the received data and generate a response. Packet sequences have a maximum length of 30, which is the default setting of the used flow exporter. We also derive three fields from each packet sequence: its length, time-stamps, and TCP flags. </p> <p><strong>Flow statistics</strong> Each data record also includes standard flow statistics, representing aggregated information about the entire bidirectional connection. The fields are the number of transmitted bytes and packets in both directions, the duration of the flow, and packet histograms. The packet histograms include binned counts (not limited to the first 30 packets) of packet sizes and inter-packet times in both directions. There are eight bins with a logarithmic scale; the intervals are 0-15, 16-31, 32-63, 64-127, 128-255, 256-511, 512-1024, >1024 [ms or B]. The units are milliseconds for inter-packet times and bytes for packet sizes (More information in the <a href="https://github.com/CESNET/ipfixprobe/tree/master#phists">PHISTS plugin documentation).</a> </p> <p><strong>Dataset structure</strong> The dataset is organized per individual days and hours. The flows are delivered in compressed CSV files. CSV files contain one flow per row; data columns are summarized in the provided list below. The following list describes flow data fields in CSV files:</p> <ul> <li><strong>TCP_FLAGS: </strong>Logical OR of all TCP flags transmitted from client to server</li> <li><strong>TCP_FLAGS_REV: </strong>Logical OR of all TCP flags transmitted from server to client</li> <li><strong>TLS_SNI:</strong> Server Name Indication domain</li> <li><strong>TIME_FIRST:</strong> Timestamp of the first packet in format YYYY-MM-DDTHH-MM-SS.ffffff</li> <li><strong>TIME_LAST:</strong> Timestamp of the last packet in format YYYY-MM-DDTHH-MM-SS.ffffff</li> <li><strong>DURATION:</strong> Duration of the flow in seconds</li> <li><strong>BYTES:</strong> Number of transmitted bytes from client to server</li> <li><strong>BYTES_REV:</strong> Number of transmitted bytes from server to client</li> <li><strong>PACKETS:</strong> Number of packets transmitted from client to server</li> <li><strong>PACKETS_REV:</strong> Number of packets transmitted from server to client</li> <li><strong>PPI_PKT_DIRECTIONS:</strong> Direction of PPI sequence </li> <li><strong>PPI_PKT_FLAGS:</strong> TCP flags of PPI sequence</li> <li><strong>PPI_PKT_TIMES:</strong> Timestamps of individual packets in PPI sequence</li> <li><strong>PPI_PKT_LENGTHS:</strong> Lengths of individual packets in PPI sequence</li> <li><strong>S_PHISTS_SIZES:</strong> Histogram of packet sizes from client to server</li> <li><strong>D_PHISTS_SIZES: </strong>Histogram of packet sizes from server to client</li> <li><strong>S_PHISTS_IPT: </strong>Histogram of inter-packet times from client to server</li> <li><strong>D_PHISTS_IPT:</strong> Histogram of inter-packet times from server to client</li> </ul> <p> </p> <p>The dataset also contains a service map in the form of a CSV file. The service map can be used to extract high-level labels from SNI domain names. </p> <p> </p> <p>The directory tree of the dataset is:</p> <pre><code>. ├── 20220819 │ ├── flows.202208190000.csv │ ├── flows.202208190100.csv | ├── ... │ └── flows.202208192300.csv ├── 20220820 │ ├── flows.202208200000.csv │ ├── flows.202208200100.csv | ├── ... │ └── flows.202208202300.csv └── 20220821 ├── flows.202208210000.csv ├── flows.202208210100.csv ├── ... └── flows.202208212300.csv<br></code></pre>
Figure 1 from: Chen R, Yu Y (2016) Induced pluripotent stem (iPS) cells and somatic cardiac regeneration — An exploratory bioinformatic analysis. Research Ideas and Outcomes 2: e8801. https://doi.org/10.3897/rio.2.e8801
Figure 1 - Nucleostemin (GNL3) and iPS (SOX2-OCT4-NANOG) subcellular interaction network
IP women seats
Realized within the project of the sourced-based reconstruction of the New Synagogue in Wroclaw/Breslau (Poland). Link to the 3D model documentation: http://www.vfu-oppler.hs-mainz.de/en/wisski/navigate/6336/view. Supported by »The German Federal Government Commissioner for Culture and the Media « (02/2018-11/2019) and »The Foundation for Polish-German Cooperation« (05/2018). Magnified by https://architekturinstitut.hs-mainz.de/. Published under CC-BY-NC-SA 4.0. Source: Objaverse 1.0 / Sketchfab
iPS Cells of Patients for Models of Retinal Dystrophies
ClinicalTrials.gov study NCT03853252. IPD Sharing: NO. Countries: 1. Publications: 0.
Iron Aid IPS on Performance, Fatigue and Iron Levels During 12 Weeks of Supplementation and Aerobic Training
ClinicalTrials.gov study NCT03523455. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
A Study of the Safety and Biological Activity of Intraperitoneal (IP) EGEN-001 Administered Alone and in Combination With Standard Chemotherapy in Colorectal Peritoneal Carcinomatosis Patients
ClinicalTrials.gov study NCT01300858. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Study to Compare Irinotecan Combined With Cisplatin (IP) Versus Etoposide Combined With Cisplatin (EP) in Advanced and Metastatic Gastrointestinal Pancreatic and Esophageal Neuroendocrine Carcinoma
ClinicalTrials.gov study NCT03168594. IPD Sharing: NO. Countries: 1. Publications: 0.
The HEALiX™ Intubated Patient (IP) Pilot Study
ClinicalTrials.gov study NCT04759066. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Generation of Induced Pluripotent Stem (iPS) Cell Lines From Skin Fibroblast Cells of Participants With Age-Related Macular Degeneration
ClinicalTrials.gov study NCT03372746. IPD Sharing: Not stated. Countries: 1. Publications: 0.
IPS Differentiated Cardiomyocytes Vein Transplantation for Chronic Heart Failure
ClinicalTrials.gov study NCT03759405. IPD Sharing: NO. Countries: 1. Publications: 0.
Long-term Follow-up (LTFU) Study of Participants in Any iECURE Protocol Using an Investigational Product (IP)
ClinicalTrials.gov study NCT06805695. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
In Vitro Model of the Cystic Fibrosis Bronchial Epithelium Via iPS Technology
ClinicalTrials.gov study NCT03754088. IPD Sharing: Not stated. Countries: 1. Publications: 0.
A Study of TS-1 Plus Irinotecan and Cisplatin (IP) for Patients With Stage IIIB/IV Non Small Cell Lung Cancer (NSCLC)
ClinicalTrials.gov study NCT00874328. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Complete Cytoreduction Followed by IP and Systemic Chemotherapies for Gastric Cancer With Peritoneal Carcinomatosis
ClinicalTrials.gov study NCT04547725. IPD Sharing: NO. Countries: 1. Publications: 0.
Phase I Safety Study of Inhaled N-IP-00001 to Determine Tolerability and Safety in Healthy Volunteers.
ClinicalTrials.gov study NCT06662019. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Organoids Derived From Induced-Pluripotent Stem Cells (iPS) From Patients With High Grade Astrocytoma
ClinicalTrials.gov study NCT03971812. IPD Sharing: NO. Countries: 1. Publications: 0.
Efficacy and Safety Research of Cold Snare Polypectomy and Hot Snare Polypectomy in the Treatment of 4-9 mm Diameter Colorectal 0-Isp and 0-Ip Polyps: a Prospective, Multicenter, Randomized Controlled
ClinicalTrials.gov study NCT06658561. IPD Sharing: NO. Countries: 1. Publications: 0.
Transplantation of Human iPS Cell-derived Dopaminergic Progenitors (CT1-DAP001) for Parkinson's Disease (Phase I/II)
ClinicalTrials.gov study NCT06482268. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Dose Finding, Efficacy and Immunological Response of IP-001 Following MWA or IRE for CRLM
ClinicalTrials.gov study NCT06630624. IPD Sharing: NO. Countries: 1. Publications: 0.
Clinical Trial of Human (Allogeneic) iPS Cell-derived Cardiomyocytes Sheet for Ischemic Cardiomyopathy
ClinicalTrials.gov study NCT04696328. IPD Sharing: NO. Countries: 1. Publications: 0.
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