1,226 Works

Port Mirroring

External Data Source
A package that sends copies of network packets from your OpenWrt router to another device on your network or beyond, giving you the ability to monitor and analyze network traffic without additional hardware. Intrusion detection systems, network application debugging, and network performance monitoring are common use cases. This is a continuation of the work started by Bruce Geng at https://code.google.com/p/port-mirroring/

libcrafter

External Data Source
Libcrafter is a high level library for C++ designed to create and decode network packets. It is able to craft or decode packets of most common networks protocols, send them on the wire, capture them and match requests and replies. It enables the creation of networking tools in a few lines with a interface very similar to Scapy. A packet is described as layers that you stack one upon the other. Fields of each layer...

EKFiddle

External Data Source

internet_outage_adaptive_a34n-20181001 (2018-10-01 to 2019-01-01)

University Of Southern California-Information Sciences Institute
To collect this data, all allocated and responsive Internet IP address blocks were pinged by sending ICMP ECHO_REQUEST (PING) packet. The block status was recorded in this data set. Probe was repeated every 11 minutes, and more quickly when uncertain about block status. In all, approximately 3.5M /24 subnets were periodically probed.

internet_outage_adaptive_a34all-20181001 (2018-10-01 to 2019-01-01)

University Of Southern California-Information Sciences Institute
Combined reachability information for over 3.5M /24 subnets; this dataset is created by post-processing data from datasets internet_outage_adaptive_a34c-20181001 internet_outage_adaptive_a34e-20181001 internet_outage_adaptive_a34g-20181001 internet_outage_adaptive_a34j-20181001 internet_outage_adaptive_a34n-20181001 internet_outage_adaptive_a34w-20181001

internet_outage_adaptive_a34w-20181001 (2018-10-01 to 2019-01-01)

University Of Southern California-Information Sciences Institute
To collect this data, all allocated and responsive Internet IP address blocks were pinged by sending ICMP ECHO_REQUEST (PING) packet. The block status was recorded in this data set. Probe was repeated every 11 minutes, and more quickly when uncertain about block status. In all, approximately 3.5M /24 subnets were periodically probed.

internet_outage_adaptive_a34g-20181001 (2018-10-01 to 2019-01-01)

University Of Southern California-Information Sciences Institute
To collect this data, all allocated and responsive Internet IP address blocks were pinged by sending ICMP ECHO_REQUEST (PING) packet. The block status was recorded in this data set. Probe was repeated every 11 minutes, and more quickly when uncertain about block status. In all, approximately 3.5M /24 subnets were periodically probed.

internet_outage_adaptive_a34e-20181001 (2018-10-01 to 2019-01-01)

University Of Southern California-Information Sciences Institute
To collect this data, all allocated and responsive Internet IP address blocks were pinged by sending ICMP ECHO_REQUEST (PING) packet. The block status was recorded in this data set. Probe was repeated every 11 minutes, and more quickly when uncertain about block status. In all, approximately 3.5M /24 subnets were periodically probed.

internet_outage_adaptive_a34c-20181001 (2018-10-01 to 2019-01-01)

University Of Southern California-Information Sciences Institute
To collect this data, all allocated and responsive Internet IP address blocks were pinged by sending ICMP ECHO_REQUEST (PING) packet. The block status was recorded in this data set. Probe was repeated every 11 minutes, and more quickly when uncertain about block status. In all, approximately 3.5M /24 subnets were periodically probed.

internet_outage_adaptive_a34j-20181001 (2018-10-01 to 2019-01-01)

University Of Southern California-Information Sciences Institute
To collect this data, all allocated and responsive Internet IP address blocks were pinged by sending ICMP ECHO_REQUEST (PING) packet. The block status was recorded in this data set. Probe was repeated every 11 minutes, and more quickly when uncertain about block status. In all, approximately 3.5M /24 subnets were periodically probed.

ddosflowgen (2017-09-01)

Inc. Galois
ddosflowgen is a tool that models a DDoS attack and generates synthetic traffic datasets from multiple views. You can define the number of attacking networks and adjust parameters such as the attack vectors present, the amplification factor, and the number of attack sources per network. Our tool includes non-attack traffic in the output by rewriting IP addresses from a reference noise dataset. Unlike packet-based simulations, which are not feasible at terabit scales, ddosflowgen simulates traffic...

Real Data Corpus - Naval Postgraduate School (2006-01-01 to 2014-12-31)

Naval Postgraduate School
Real Data Corpus The Real Data Corpus (RDC) is a collection of disk images extracted from secondary storage devices that were acquired from second-hand markets around the world. In total, the RDC currently consists of 58 TiB of data contained in 3,127 disk images from 29 countries. A variety of devices are represented, including magnetic media and solid state storage from laptops, desktops, mobile phones, USB memory sticks, and other media. The dataset is hosted...

Dream, Traderoute, Berlusconi and Valhalla marketplaces, 2017-2018: Non-anonymized datasets (2017-07-15 to 2018-08-22)

Carnegie Mellon University
Non-anonymized database pertaining to the Dream, Berlusconi, Traderoute, and Valhalla marketplaces. This data was used in the paper "Adversarial Matching of Dark Net Market Vendor Accounts" (Tai et al., 2019), and in an upcoming EMCDDA report. In this dataset, textual information (item name, description, or feedback text) and handles have *not* been anonymized and are thus available. We don't expect any private identifiers or other PII to be present in the data, which was collected...

Dream, Traderoute, Berlusconi and Valhalla marketplaces, 2017-2018: Anonymized datasets (2017-07-15 to 2018-08-22)

Carnegie Mellon University
Anonymized data for the Dream, Traderoute, Berlusconi and Valhalla online anonymous marketplaces (2017-2018) Carnegie Mellon University Developed in-house web scrapers to collect data about marketplaces; subsequently fed into a parser, and eventually, an analysis engine, that produced this data.

Applying Ethical Principles to Information and Communication Technology Research: A Companion to the Menlo Report.

Dave Dittrich, Dave Dittrich, Erin Kenneally & Erin Kenneally

Valuing Cyber Security Research Datasets

Tyler Moore, Erin Kenneally, Tyler Moore, Erin Kenneally, Tyler Moore & Erin Kenneally

Cyber Threat Indicators CY18 (2018-01-01 to 2018-12-31)

DHS Cybersecurity And Infrastructure Security Agency
AIS STIX Profile (https://www.us-cert.gov/sites/default/files/ais_files/AIS_Submission_Guidance_Appendix_A.pdf).

Cyber Threat Indicators (2016-01-01 to 2018-12-31)

DHS Cybersecurity And Infrastructure Security Agency
In 2016 DHS began the Automated Indicator Sharing (AIS) initiative. Through AIS, DHS enables the exchange of cyber threat indicators in a machine-readable (XML) format between the Federal Government and the private sector. Threat indicators are pieces of information like malicious IP addresses or the sender address of a phishing email (although they can also be much more complicated). Organizations sharing indicators use the Traffic Light Protocol (TLP) (https://www.us-cert.gov/tlp) to mark the indicators for sensitivity...

internet_outage_adaptive_a35e-20190101 (2019-01-01 to 2019-04-01)

University Of Southern California-Information Sciences Institute
To collect this data, all allocated and responsive Internet IP address blocks were pinged by sending ICMP ECHO_REQUEST (PING) packet. The block status was recorded in this data set. Probe was repeated every 11 minutes, and more quickly when uncertain about block status. In all, approximately 3.5M /24 subnets were periodically probed.

internet_outage_adaptive_a35g-20190101 (2019-01-01 to 2019-04-01)

University Of Southern California-Information Sciences Institute
To collect this data, all allocated and responsive Internet IP address blocks were pinged by sending ICMP ECHO_REQUEST (PING) packet. The block status was recorded in this data set. Probe was repeated every 11 minutes, and more quickly when uncertain about block status. In all, approximately 3.5M /24 subnets were periodically probed.

internet_outage_adaptive_a35n-20190101 (2019-01-01 to 2019-04-01)

University Of Southern California-Information Sciences Institute
To collect this data, all allocated and responsive Internet IP address blocks were pinged by sending ICMP ECHO_REQUEST (PING) packet. The block status was recorded in this data set. Probe was repeated every 11 minutes, and more quickly when uncertain about block status. In all, approximately 3.5M /24 subnets were periodically probed.

internet_outage_adaptive_a35all-20190101 (2019-01-01 to 2019-04-01)

University Of Southern California-Information Sciences Institute
Combined reachability information for over 3.5M /24 subnets; this dataset is created by post-processing data from datasets internet_outage_adaptive_a35c-20190101 internet_outage_adaptive_a35e-20190101 internet_outage_adaptive_a35g-20190101 internet_outage_adaptive_a35j-20190101 internet_outage_adaptive_a35n-20190101 internet_outage_adaptive_a35w-20190101

internet_outage_adaptive_a35w-20190101 (2019-01-01 to 2019-04-01)

University Of Southern California-Information Sciences Institute
To collect this data, all allocated and responsive Internet IP address blocks were pinged by sending ICMP ECHO_REQUEST (PING) packet. The block status was recorded in this data set. Probe was repeated every 11 minutes, and more quickly when uncertain about block status. In all, approximately 3.5M /24 subnets were periodically probed.

internet_outage_adaptive_a35c-20190101 (2019-01-01 to 2019-04-01)

University Of Southern California-Information Sciences Institute
To collect this data, all allocated and responsive Internet IP address blocks were pinged by sending ICMP ECHO_REQUEST (PING) packet. The block status was recorded in this data set. Probe was repeated every 11 minutes, and more quickly when uncertain about block status. In all, approximately 3.5M /24 subnets were periodically probed.

internet_outage_adaptive_a35j-20190101 (2019-01-01 to 2019-04-01)

University Of Southern California-Information Sciences Institute
To collect this data, all allocated and responsive Internet IP address blocks were pinged by sending ICMP ECHO_REQUEST (PING) packet. The block status was recorded in this data set. Probe was repeated every 11 minutes, and more quickly when uncertain about block status. In all, approximately 3.5M /24 subnets were periodically probed.

Registration Year

  • 2017
    791
  • 2018
    319
  • 2019
    116

Resource Types

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