IP Geolocation through Reverse DNS

Dan, Ovidiu; Parikh, Vaibhav; Davison, Brian D.

doi:10.48550/arxiv.1811.04288

Cited by 6 publications

(3 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [11], IP address geolocation studies were conducted using active signal delay measurements (GeoPing), DNS routing determination (GeoTrack), and the use of IP databases of commercial services (for example, IP2Location and MaxMind) for geolocation.…”

Section: Introductionmentioning

confidence: 99%

Complex Method of Determining the Location of Social Network Agents in the Interests of Information Operations

Herasymov,

Tkachov,

Bazarnyi

2024

A.I.S.

View full text Add to dashboard Cite

The researcher developed a method for determining the location of social network agents in the interest of conducting an information operation based on a comprehensive approach to data analysis of the information system. The relevance of the method is determined by the need to specify the enemy's target audience in the area of the information operation. Results. The author proposed a complex method for determining the location of social network agents, which is based on the combination of data from the analysis of the social connections of the specified agent, geotags and the time of registration of his friends in the social network, databases of IP addresses and geolocations of social network agents. The advantage of the developed method is the possibility of its application without direct access to the devices of agents of the social network that use the data of global positioning satellite systems. Conclusion. The application of the proposed complex method of determining the location of agents of social networks makes it possible to increase the effectiveness of information operations due to a more accurate definition of the enemy's target audience in the area of operations. The direction of improvement of the developed method can be its integration with complex information systems of psychological influence, as well as the use of machine learning methods and algorithms.

show abstract

Section: Introductionmentioning

confidence: 99%

Complex Method of Determining the Location of Social Network Agents in the Interests of Information Operations

Herasymov,

Tkachov,

Bazarnyi

2024

A.I.S.

View full text Add to dashboard Cite

show abstract

“…In some cases, the rules needed for parsing the names are manually generated, while in other cases the most probable locations are found by interpreting reverse DNS names through machine learning methods. Notable examples include undns [29], DRoP [30], and RDNS [31]. Another example is the use of crowdsourced data: users voluntarily provide the location of the IP addresses they manage to a central repository, so that locations can be subsequently retrieved by all interested users [32].…”

Section: Ip Geolocationmentioning

confidence: 99%

A worldwide study on the geographic locality of Internet routes

2021

View full text Add to dashboard Cite

“…Since a domain name can contain different granular descriptions of geographic location information, like the abbreviation of a city, state, or country, by mining this information, the geographic location of the target device can be inferred. Based on this idea, GeoTrack [24], DRoP [14], rDNS-Geo [8] and HLOC [27] mine location clues in domain names to estimate a location. Structon [13] uses regular expressions to extract address information from web pages.…”

Section: Ip Geolocationmentioning

confidence: 99%

XLBoost-Geo: An IP Geolocation System Based on Extreme Landmark Boosting

Wang,

Zhu,

Wang

et al. 2020

Preprint

View full text Add to dashboard Cite

IP geolocation aims at locating the geographical position of Internet devices, which plays an essential role in many Internet applications. In this field, a long-standing challenge is how to find a large number of highly-reliable landmarks, which is the key to improve the precision of IP geolocation. To this end, many efforts have been made, while many IP geolocation methods still suffer from unacceptable error distance because of the lack of landmarks. In this paper, we propose a novel IP geolocation system, named XLBoost-Geo, which focuses on enhancing the number and the density of highly reliable landmarks. The main idea is to extract locationindicating clues from web pages and locating the web servers based on the clues. Based on the landmarks, XLBoost-Geo is able to geolocate arbitrary IPs with little error distance. Specifically, we first design an entity extracting method based on a bidirectional LSTM neural network with a self-adaptive loss function (LSTM-Ada) to extract the location-indicating clues on web pages and then generate landmarks based on the clues. Then, by measurements on network latency and topology, we estimate the closest landmark and associate the coordinate of the landmark with the location of the target IP. The results of our experiments clearly validate the effectiveness and efficiency of the extracting method, the precision,

show abstract

IP Geolocation through Reverse DNS

Cited by 6 publications

References 23 publications

Complex Method of Determining the Location of Social Network Agents in the Interests of Information Operations

Complex Method of Determining the Location of Social Network Agents in the Interests of Information Operations

A worldwide study on the geographic locality of Internet routes

XLBoost-Geo: An IP Geolocation System Based on Extreme Landmark Boosting

Contact Info

Product

Resources

About