Category Archives: IIAR

How to leverage botnet takedowns

What is to be done when botnet takedowns don’t produce lasting benefits?

At the Telecommunications Policy and Research Conference in Arlington, VA in September, I gave a paper about Rustock Botnet and ASNs. Most of the paper is about effects of a specific takedown (March 2011) and a specific slowdown (December 2010) on specific botnets (Rustock, Lethic, Maazben, etc.) and specific ASNs (Korea Telecom’s AS 4766, India’s National Internet Backbone’s AS 9829, and many others).

The detailed drilldowns also motivate a higher level policy discussion.

Knock one down, two more pop up: Whack-a-mole is fun, but not a solution. Need many more takedowns, oor many more organizations playing. How do we get orgs to do that? …
There is extensive theoretical literature that indicates Continue reading →

The Big Drop: medical to zero in SpamRankings.net

A surprise in the July SpamRankings.net rankings: US medical rankings all went to zero by 14 July. World medical rankings went from hundreds and thousands to near zero between 17 and 24 July.

That’s in rankings from CBL data. PSBL shows much less data for medical organizations, yet nonetheless the same effect in both world and U.S. medical rankings.

No other rankings showed such a drop.

Did medical organizations actually clean up their act? Or did they just manage to whitelist their netblocks at CBL and PSBL?

Either way, it looks like they noticed SpamRankings.net.

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Transparency in Rome

Here’s my presentation, Transparency as Incentive for Internet Security: Organizational Layers for Reputation, from RIPE 61 in Rome. This presentation summarizes the two previous RIPE Labs papers about proposed new organizational layers and outbound spam ranking experiments.

RIPE-NCC is the oldest of the Regional Internet Registries (RIRs), and RIPE is the deliberately unorganized association of interested parties that meets twice a year and holds discussions online in between. It’s a mix of operations, research, and socializing. Topics range from obscure details of deploying IPv6 to organizational proposals such as what I was talking about. 430 people attended the meeting in Rome, which was quite a few more than the dozen or two of the first RIPE meeting I went to many years ago.

Interesting questions were asked. I may blog some of them.

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Outbound Spam Ranking Experiments

Should Uganda Telecom be counted as a Belgian ISP for outbound spam rankings?

Which matters most: history, topology, business headquarters location, or some other criterion?

These are some questions that come up in designing experiments in rolling out a reputation system for outbound spam. More on this in the RIPE Labs article (8 Nov 2010), Internet Reputation Experiments for Better Security.

Such experiments can draw on fifty years of social science research and literature, first crystalized as Social Comparison Theory by Leon Festinger in 1954, that indicate that making personal reputation transparent changes personal behavior. More recent research indicates that the same applies to organizations. Using anti-spam blocklist data, it is possible to make E-Mail Service Provider (ESP) behavior (banks, stores, universities, etc., not just ISPs) in preventing or stopping outbound spam transparent, and this paper is about experiments to see how the resulting reputation actually changes ESP behavior.

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Organizing the Cloud Against Spam

In RIPE Labs, here’s a paper on Internet Cloud Layers for Economic Incentives for Internet Security by the IIAR Project (I’m the lead author). Anti-spam blocklists and law enforcement are some Internet organizational layers attempting to deal with the plague of spam, so far reaching a standoff where most users don’t see most spam, yet service providers spend large amounts of computing and people resources blocking it.
The root of the ecrime problem is not technology: it is money.
Continue reading →

Data, Reputation, and Certification Against Spam

I’m giving a talk today at the Internet2 workshop on Collaborative Data-Driven Security for High Performance Networks at WUSTL, St. Louis, MO. You can follow along with the PDF.

There may be some twittering on #DDCSW.

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FireEye’s Ozdok Botnet Takedown Observed

FireEye coordinated a takedown of botnet Ozdok or MegaD, on 5-6 Nov 2009, with cooperation by many ISPs and DNS registrars.

Good show! What effects did it have on spam? Not just spam from this botnet; spam in general.

Botnets and spam volume

This graph was presented at NANOG 48, Austin, TX, 24 Feb 2010, in FireEye’s Ozdok Botnet Takedown In Spam Blocklists and Volume Observed by IIAR Project, CREC, UT Austin. John S. Quarterman, Quarterman Creations, Prof. Andrew Whinston, PI CREC, UT Austin. That was a snapshot of an ongoing project, Incentives, Insurance and Audited Reputation: An Economic Approach to Controlling Spam (IIAR).

That presentation was enough to demonstrate the main point: takedowns are good, but we need a lot more of them and a lot more coordinated if we are to make a real dent in spam.

The IIAR project will keep drilling down in the data and building up models. One goal is to build a reputation system to show how effective takedowns and other anti-spam measures are, on which ASNs.

Thanks especially to CBL and to Team Cymru for very useful data, and to FireEye for a successful takedown.

We’re all ears for further takedowns to examine.

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3FN + FTC = Some Less Spam From Some ASNs

A research project I’m assisting at the University of Texas at Austin notes that:
On Tuesday 2 June 2009, the U.S. Federal Trade Commission (FTC) took legal steps that shut down the web hosting provider Triple Fiber network (3FN.net).
2009-06-01--cbl-2.png

Looking at Autonomous Systems (ASNs) listed in the spam blocklist CBL, Continue reading →

VZ Port 587: Good Try

Back in February, Verizon announced it would start requiring outbound mail go through port 587 instead of port 25 during the next few months. It seemed like a good idea to squelch spam. Most other major ISPs did it. People applauded Verizon for doing it.

Unfortunately, it seems that if it had any effect it was short-lived. Looking at anti-spam blocklists on a daily basis, a couple of Verizon Autonomous Systems (ASes), AS-19262 and AS-701, do show dips in blocklist listings on the blocklist PSBL in March. But they don’t last.

Spammers are very adaptable, partly because the botnets they use are adaptable. Good try, Verizon.

This information is from an NSF-funded academic research project at the University of Texas at Austin business school. Thanks to PSBL for the blocklist data.

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