The CAIDA Randomly and Uniformly Spoofed Denial-of-Service (RSDoS) Attack Metadata

This dataset contains meta-data of the randomly spoofed denial-of-service attacks inferred from the backscatter packets collected by the UCSD Network Telescope between March 1, 2015 and February 28, 2017. It is aggregated from the raw Telescope data using the criteria described in the paper Inferring Internet Denial-of-Service Activity (2006) by Moore et al. Analysis of this dataset was published in Millions of Targets Under Attack: a Macroscopic Characterization of the DoS Ecosystem (2017) by Jonker et al.

Data Description

The UCSD Network Telescope consists of a globally routed, but lightly utilized /9 and /10 network prefix, that is, 1/256th of the whole IPv4 address space. It contains few legitimate hosts; inbound traffic to non-existent machines - so called Internet Background Radiation (IBR) - is unsolicited and results from a wide range of events, including misconfiguration (e.g. mistyping an IP address), scanning of address space by attackers or malware looking for vulnerable targets, backscatter from randomly spoofed denial-of-service attacks, and the automated spread of malware. CAIDA continously captures this anomalous traffic discarding the legitimate traffic packets destined to the few reachable IP addresses in this prefix. We archive and aggregate these data, and provide this valuable resource to network security researchers.

To generate this RSDoS Metadata dataset, we processed 5-minute intervals of the raw telescope data extracting the response packets sent by victims of randomly and uniformly spoofed Denial-of-Service attacks ("backscatter" packets). Activity that related to the same victim was summarized in an 'attack vector', following the definitions and methodology described by Moore et al. (2006). We continued to update the attack vectors as long as related activity was still observed.

Once an attack 'completed', we recorded the accumulated statistics. We also geolocated the targeted IP address using NetAcuity Edge Premium Edition data and determined its origin AS using Routeviews Prefix-to-AS mappings ( pfx2as) data.

For each day within the two-year period from March 1, 2015 to February 28, 2017, the RSDoS dataset has a single compressed CSV file of attack vectors. Each attack vector is uniquely identified by the target IP address and the attack start timestamp. Each record contains the following fields:

  • The IP address of the attack victim (target_ip)
  • The number of distinct attacker IPs in the attack
  • The number of distinct attacker ports
  • The number of distinct target ports
  • The cumulative total number of packets observed in the attack
  • The cumulative total number of bytes seen for the attack
  • The maximum packet rate (of backscatter packets) seen in the attack, as a moving average per minute
  • The timestamp of the first observed packet of the attack
  • The timestamp of the last observed packet of the attack
  • The autonomous system number of target_ip at the time of the attack
  • Country geolocation of target_ip, at the time of the attack
  • Continent geolocation of target_ip, at the time of the attack
  • The IP protocol value of target-destined packets
  • The first observed attacker port
  • The first observed target port
  • The first-observed ICMP type for the attack vector
  • The first-observed ICMP code for the attack vector
  • A bit flag indicating if an attack is definitely multi IP protocol

Data Access

Request access to the CAIDA RSDoS Attack Metadata.

Referencing this Dataset

When referencing this data (as required by the AUA), please use:

CAIDA UCSD Randomly and Uniformly Spoofed Denial-of-Service (RSDoS) Metadata dataset - <dates used>,
https://www.caida.org/catalog/datasets/rsdos-targets/
Please consider referencing the associated papers:
Jonker, M., King, A., Krupp, J., Rossow, C., Sperotto, A. and Dainotti, A., 2017. Millions of targets under attack: a macroscopic characterization of the DoS ecosystem. In Proceedings of the ACM 2017 Internet Measurement Conference (pp. 100-113), doi:10.1145/3131365.3131383 Moore, D., Shannon, C., Brown, D.J., Voelker, G.M. and Savage, S., 2006. Inferring internet denial-of-service activity. ACM Transactions on Computer Systems (TOCS), 24(2), pp.115-139.
Also, please report your publication using this dataset to CAIDA.

UCSD Network Telescope Datasets

Related Objects

See https://catalog.caida.org/dataset/2017_imc_rsdos_targets to explore related objects to this document in the CAIDA Resource Catalog.
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