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by William Fleurant
13 Comments

739,033 unique computers running BitCoin.

It’s 2012, and epic 2011 was totally being epic 2011.

I recorded 739,033 unique computer IP addresses using the BitCoin Currency over a 3 month period. Plus, According to MTGOX:

49.9883/BTC (BitCoins) is trading@ $6.45978/USD.

That’s $323 for 50 BitCoins. Happy-Happy Joy-Joy.  The Google Maps KML file is also quite rich. If you want to check that one out (and have the GPU/CPU power) contact me:

Snippet of a side project of mine, introducing my independent findings on the Worldwide usage of BitCoin. Data collected on a machine -not- running BitCoin. Read the WiKi to find out how. But, I would start by grepping the source code.

If you enjoyed this choppy post, send some btc to the QR above.

BitCoin is a currency. This currency is so different because anybody can use an Internet connected computer to generate BitCoins. It can be exchanged for other currency, commodities, and a variety of services. Similarly, it can be withdrawn or exchanged like all other currencies. But instead of a leather wallet or plastic credit card, BitCoin uses an encrypted digital wallet. This protected wallet can conduct transactions from a smartphone [3], an ATM machine [4] and of course a personal computer.

This process of using ones computer to generate a BitCoin is in fact called mining. Mining for BitCoins independently is very competitive. It absolutely requires expensive hardware for the ability to gain a substantial return on investment. An initial investment of almost three thousand dollars should generate about 3½/BTC per day. [5]

Snippet of Hipster Data Collection section.

I chose to use GeoIP’s open source release. An additional program was needed to look-up each IP address or Hostname. I found a program called created by a marketing company MaxMind. [14]. I edited the code in GeoIP*/test/test-14.c file to output in a comma-separated valued format, rather than a tabular format.

— test-14.c.orig      2011-10-30 23:28:55.396216967 -0400

+++ test-14.c   2011-10-30 23:29:05.186203262 -0400

@@ -60,7 +60,7 @@

if (gir != NULL) {

ret = GeoIP_range_by_ip(gi, (const char *) host);

time_zone = GeoIP_time_zone_by_country_and_region(gir->country_code, gir->region);

–      printf(“%s\t%s\t%s\t%s\t%s\t%s\t%f\t%f\t%d\t%d\t%s\t%s\t%s\n”, host,

+      printf(“%s,%s,%s,%s,%s,%s,%f,%f,%d,%d,%s,%s,%s\n”, host,

_mk_NA(gir->country_code),

_mk_NA(gir->region),

_mk_NA(GeoIP_region_name_by_code(gir->country_code, gir->region)),

In addition to using the free city lookup database, I was also able to utilize a CPAN Perl module to plot waypoints of GPS via their GeoIP API.  Note that before running the code GeoIP city lookup provides, recompiling the source with an output according to their API is required for their bash wrapper (output to ./.libs/ with all other compiled C)

Start a WireShark filter to match ‘dst.port == 53’ and if on a Unix (Apple) or Linux computer the command ‘tcpdump –nqi eth0 udp port 53’ will suffice. Then, all of the captured DNS requests answered will be observed. In this 3 month case, there was a substantial number of IP Addresses which are read by the GeoIP application which in return are sent out for further resolution of origin via the computers default Domain Name Server and finally passed back through GeoIP for a database match and are attributed with such matching variables which are written in CSV format and saved to file.  The reversing of IP address to location took over 24 hours. I created a bash script to monitor this step.

#!/bin/bash

total=744893 ; scale=3 ; sleep=60

file=”/root/bitcoin_sorted04112011.csv”

while true ; do

clear

p=$(wc -l $file | awk ‘{print $1}’)

t=$((${total} – ${p}))

d=$(echo “scale=$scale; $total / $t” | bc)

f=$(tail -n2 $file | head -n1 | cut -d”,” -f 1,11)

s=$((${o}-${t}))

echo “Remaining : $t”

echo “Previous  : $o”

if [ $s -eq 0 ] ; then s=”SERVFAIL” ; fi

echo “Speed     : $s”

echo “Completion: $d%”

echo “Locaton   : $f”

o=$t

sleep $sleep

done

…snip

I recorded the data from the centralized server and logged all connecting, and disconnecting clients.  The data was recorded non-stop.  I used a variety of programming languages to capture, parse and manipulate the data. Ruby, Perl, Sed, Awk, PHP, GPSBabel, GEPLOT, Excel and Microsoft Word programs were utilized. I first used MySQL Database but that was not necessary with the programs and scripts I utilized and wrote afterwards.  It took 45 hours to produce this document with a total of 7,542,601 observations [20].

Thanks for your über focus. It’s Dangerous to go alone! Take this.

[Fig 3.] Plot of 739,033 unique BitCoin Instances. Map created with and Map software Image-WorldMap [18] (Author of software: Leon Brocard) Licensed as Free Software (GNU GPLv2)


 

 

Results

See Supplementary Material at http://is.gd/onxXil for raw data obtained from this study. (Note: IP_ADDRESS field has been censored for privacy, but is available upon request)

Declaration of Testable Hypotheses

  • BitCoin popularity originating from countries where there are physical hardware limitations due to high import tax or other fiscal and or availability issues will be among least reported.
    • False – 195 countries were documented.

 

  • BitCoin will be popular at Universities.
    • True – 385 U.S. Colleges are participating in BitCoin. Based on an estimated 1,735 institutions of higher education [15], I conclude more than ¼ of the Universities in the U.S.A. are actively mining for BitCoin.

 

  • BitCoin participants in countries with high-censorship laws will be unable to participate.
    • True. Among the 56 countries that were unaccounted for were

Libya, Turkmenistan and North Korea.

ANTARCTICA	BONAIRE	BOUVET ISLAND	BRITISH INDIAN OCEAN TERRITORY	CENTRAL AFRICAN REPUBLIC
COOK ISLANDS	DJIBOUTI	EQUATORIAL GUINEA	ERITREA	FALKLAND ISLANDS (MALVINAS)
NORTH KOREA	LESOTHO	LIBERIA	LIBYA MARSHALL ISLANDS
NIGER	NORFOLK ISLAND	PALAU	PITCAIRN	SAINT BARTHÉLEMY
SIERRA LEONE	SINT MAARTEN (DUTCH PART)	SOLOMON ISLANDS	SOMALIA	SOUTH GEORGIA AND THE SOUTH SANDWICH ISLANDS
TOKELAU	TURKMENISTAN TUVALU	WALLIS AND FUTUNA	WESTERN SAHARA
CHAD	CHRISTMAS ISLAND	COCOS (KEELING) ISLANDS	COMOROS	CONGO
FRENCH SOUTHERN TERRITORIES	GUINEA-BISSAU	HEARD ISLAND AND MCDONALD ISLANDS	HOLY SEE (VATICAN CITY STATE)	KIRIBATI
MAURITANIA	MICRONESIA	MONTSERRAT	MYANMAR	NAURU
SAINT HELENA	SAINT MARTIN (FRENCH PART)	SAINT PIERRE AND MIQUELON	SAMOA	SAO TOME AND PRINCIPE
SOUTH SUDAN	SVALBARD AND JAN MAYEN	SWAZILAND	TIMOR-LESTE

[fig.4] List of countries not using BitCoin.

 

  • BitCoin usage in the USA will be more popular on east and west coast due to many new technologies emerging from these coastal areas such as Massachusetts, New York and California.
    • Inconclusive: The graphed data indicates various “Popular” states, which predicted to in fact be 4 of the 10 top in this list. Arguable hypothesis, immature reasoning for anticipated results.

 

  • BitCoin data once collected will show serious implications on publishing IP Addresses.
    • Releasing any information in regards to government networks is beyond this discourse.  There are additional implications due to recent targeted BitCoin attacks on computer networks which essentially steal wallet-Addresses. [28]
More BitCoin propaganda :)


by William Fleurant
3 Comments

Anatomy of a Subway Hack

Anatomy of a Subway Hack 2008

August 10, 2008

Documentation for Boston T subway system. The file, created in June, 2008 using PowerPoint by Russell Ryan, Zach Anderson, Alessandro Chiesa, demonstrates lax security, failed security, and no security in an area of public transportation that the most people would consider "safe". The 87 page document shows the relative ease one can gain entry to the system and exploit it to gain relatively free access for subway use. Sabotage of the system is, along with exploitation, an easy task due to the poor security. In early August, the authors were prevented from giving a scheduled presentation [1] at DEFCON by a federal judge in a injunction filed by the Massachusetts Bay Transit Authority (MBTA). The Electronic Frontier Foundation (EFF) defended the students who had made an effort to contact the MBTA prior to their scheduled Defcon appearance. The temporary restraining order against the authors did not stop MIT’s student newspaper from posting a copy of the presentation that had been included on a Defcon CD that had been distributed.

The File Details How To:

  • Generate stored-value fare cards
  • Reverse engineer magstripes
  • Hack RFID cards
  • Use software radio to sniff
  • Use FPGAs to brute force
  • Tap into the fare vending network
  • Social engineer
  • Warcart

ZACK ANDERSON, RJ RYAN, ALESSANDRO CHIESA, and the MASSACHUSETTS INSTITUTE OF TECHNOLOGY. "Anatomy of a Subway Hack 2008 – Wikileaks." Wikileaks – Wikileaks. 10 Aug. 2008. 14 Jan. 2009 <http://wikileaks.org/wiki/Anatomy_of_a_Subway_Hack_2008>.

 

www-tech.mit.edu/V128/N30/subway/Defcon_Presentation.pdf

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