Two Spam Filters 10 Times As Accurate As Humans

Nuclear Elephant writes "The authors of two spam filters, CRM114 and DSPAM, announced recently that their filters have achieved accuracy rates ten times better than a human is capable of. Based on a study by Bill Yerazunis of CRM114, the average human is only 99.84% accurate. Both filters are reporting to have reached accuracy levels between 99.983% and 99.984% (1 misclassification in 6250 messages) using completely different approaches (CRM114 touts Markovan, while DSPAM implements a Dolby-type noise reduction algorithm called Dobly). If you're looking for a way to rid spam from your inbox, roll on over to one of these authors' websites."

Outclassed...

I'm sorry, Dave... That Nigerian guy looks suspicious and I can't let you send him money.

Re:Help setting this up

Umm, Fetchmail + procmail on your local machine?

Not sure exactly why you need a pop3 proxy involved, just use Fetchmail to deliver locally, run things through procmail.

Set your local mailserver (sendmail/qmail/postfix/exim/whatever) to use your ISP's SMTP server as a smarthost, and it'll send everything it doesn't recognize as local off to them to handle.

It _can't_ know which pr0n I think is spam vs good

I signed up for lots of junk mail lists; some solicited, some not -- sometimes from the same organizations.

How would it know if I consider brunettes non-spam but blondes spam? I did opt-in for one of those email categories, but not the other.

Re:Help setting this up

ModernGeek,

I recommend you stick with hotmail. Dabbling in stuff like spamassasin is going to be just too much work for someone as lazy as you sound. Apple makes a good built-in spam filter on its Mail client app. Why don't you go there?

Huh? Aren't humans 100%?

How can a spam filter be more accurate than humans? Humans are always the last step in spam filtering.. i use popfile and it catches 99% but it still needs me.. because im the only one capable of identifying spam 100% of the time.

Re:Huh? Aren't humans 100%?

I haven't been 100% accurate.

I received an email from my sister-in-law from her work, and the address looked suspicious (one of those weird-looking "letter and number" jumbles.

I deleted it. It happens.

*slams head against wall*

I received an email from my sister-in-law from her work

Yeah, so did I. The subject line was "I want you so bad."

I deleted it. Turned out the message was genuine. I'll never forgive myself...

Re:*slams head against wall*

If you can't forgive yourself, I'll forgive you... as soon as I recieve your sister-in-law's email address.

Don't worry

Don't worry, I can forward you the one she sent me. Sounds like the same email.

Re:*slams head against wall*

If it was your sister-in-law sending you that subject line, you probably did the right thing and deleted it

Re:Huh? Aren't humans 100%?

That actually makes humans much more accurate. We can eliminate many of the messages just by looking at the subject.

The further question is, if humans aren't as accurate as the computer, how are they measuring the accuracy at all? That is, how do they know that the 1 in 6250 messages is wrong, if a human, known to be inaccurate, was testing for accuracy?

Re:Huh? Aren't humans 100%?

The further question is, if humans aren't as accurate as the computer, how are they measuring the accuracy at all? That is, how do they know that the 1 in 6250 messages is wrong, if a human, known to be inaccurate, was testing for accuracy?

I believe that humans can be 100% accurate (or thereabouts) if they read the *ENTIRE* message, however that's exactly the point - if you have to read an entire message to tell that it's spam, the spam has succeeded.

Their number probably concerns how people can tell without reading the entire message whether or not the message is spam. My brother accidentally deleted a few messages I had sent to him, however if he had read them fully he would have known they were legit.

Cheers,
Justin

Re:Huh? Aren't humans 100%?

But the computer reads the entire message, so it's not really a fair comparison, is it? How many more lines of information was the computer allowed to look at to create its superior result?

Re:Huh? Aren't humans 100%?

Computers are neither lazy nor pressed for time, and therefore can afford to read and evaluate every single line of every single message. Humans generally can't be bothered to be so diligent, and while they have the ability to get a 100% rate, in most cases they devote so little attention to the task of filtering email that the success rate drops.

When these factors are considered, I think it's quite possible to write software that in the long run has a higher success rate than a human who has better things to do than filter his mail all day.

Re:Huh? Aren't humans 100%?

I dunno. I'm running CRM114 now, and it's taking something like 1.5 seconds to identify emails. I am on a slow machine though, which used to do SpamAssassin at around 4 seconds, and inaccurately to boot. CRM114 is a big improvement, and if it trains well after the first fortnight I'll kiss TMDA goodbye.

Re:Huh? Aren't humans 100%?

There goes my bussines idea. I wanted to start a bussines that puts humans in an eastern europe contry to sort corporate e-mail.

Now I have to think again about putting humans to decorticate sunflower seeds, it's cheper than all those machines.

Re:Huh? Aren't humans 100%?

I suppose it depends how you're defining spam. Perhaps the ultimate spam messages that don't get past them are capable of passing a turing test... hence fooling those gullible human recipients into thinking that it isn't even spam!

Fortunately, soon we will all be able to use the superhuman spam-detection capabilities of these filters to save us from ourselves. Imagine all of those pesky e-mails from your 'friends' getting caught by your spam filter before they even impinge upon your consciousness.

It'd be a wonderful world.

Re:Huh? Aren't humans 100%?

If you read the post, it quotes a study and says humans are only accurate 99.84% of the time.

Kinda makes you wonder how they can know the filters are right though. :)

(please don't reply telling me how)

Re:Huh? Aren't humans 100%?

Presumably they must use a superhuman who has 100.00% accuracy.

Re:Huh? Aren't humans 100%?

No, humans aren't 100% and yes, you can test for that. Try a thought experiment: fill a bin with 50,000 red balls and 50,000 blue balls. Ask a human to sort them all. The result probably won't be 100%, but you can still check the result and figure out how accurate the human is without relying on a superhuman ability to tell the balls apart. Same thing for spam: if you start with a known training set, you can test humans to see how well the spam is identified by manual sorting.

Re:Huh? Aren't humans 100%?

How do you know your training set is correct?

Good question! We're working on this problem, among other things, at the PSAM [pdx.edu] project. We have a project to produce high-quality benchmark corpora for spam filter testing. Watch that space for ongoing work, or e-mail us an offer to pitch in and help---we could use it!

Re:Huh? Aren't humans 100%?

fill a bin with 50,000 red balls and 50,000 blue balls. Ask a human to sort them all.

Not comparable. The job of a junk mail filter is to drop things I don't want to read. It is trying ot match my evaluation, not to match a semi-objective criterion like red or blue.

If I read 1000 messages and say which I wish I hadn't read, then I am 100% accurate by definition.

Of course, if they are really talking about a pure spam filter -- ie one which identifies unsolicited commercial email -- then they can be more accurate than me, but at an uninteresting, perhaps even counter-productive, task:

I may get unsilicited commercial email I do want to read one day. Almost happened once (I had inadvertantly signed up for it, so it was not really unsolicited, and I didn't actually buy the piece of kit they had on special offer that week, but was tempted). I also get stuff I don't want which isn't spam (notably email from virus infected machines).

The referenced study seems to be a very sloppy job from this POV. They don't define what their criterion of sucess is, and to the extent they put in a hand waving attempt it is clearly nonsense:

Because spam (sometimes termed ?unsolicited commercial email? or ?marketing messages?) is neither expected nor desired[...]

`Unsolicited' does not imply `not desired'. If they don't tease those two apart, they can't get interesting results for real world applications. Eg, someone mailing my work address with a commercial proposition may well be a very welcome unsolicited commercial email.

Re:Huh? Aren't humans 100%?

The post quotes "a study" which gives the 99.84% figure. In fact, the 99.84% figure is mentioned in the one paper as "the human author's measured accuracy as an antispam filter...on the first pass". This is what we who understand statistics call "nonsense". An individual human had an estimated accuracy of 99.84% when looking at one particular sample set of data, once. This is not a meaningful number, and it sure as heck ain't "a study".

Re:Huh? Aren't humans 100%?

Obviously you've never seen someone new to the internet sit in front of their computer. Lots of people don't know what popups are. Lots of people read some spam not knowing what it is. To these people, a computer is merely an interesting string of sensations.

Re:Huh? Aren't humans 100%?

I work with some people who use their computer every single day. Have had an email address for years, who still buys what they read in an email. Photoshop for $50...sure! Herbal viagra...why not?

Well, she always has a big smile on her face, maybe there's something to this spam thing.

Re:Huh? Aren't humans 100%?

Well, she always has a big smile on her face, maybe there's something to this spam thing.

You mean you've never noticed this before? Idiots are some of the happiest people I know.

Re:Huh? Aren't humans 100%?

Lots of people don't know what popups are.

Uh, sure they do. Popups - that's like those porn storms, isn't it? Some people say it only happens with IE and Windows, but I talked to my service provider and they told me 'just pull the power plug out of the wall when that happens'.

Easily fixed.

Re:Huh? Aren't humans 100%?

I talked to my service provider and they told me 'just pull the power plug out of the wall when that happens'.

Ok, now the screen dimmed a little and I heard the hard drive spin down, but the pop ups are still a comin! Oh, and something about "battery level at 98%" or something.

Re:Huh? Aren't humans 100%?

Perhaps they mean that Human A is reading email intended for Human B and attempting to classify the email as spam or not spam. I wouldnt be surprised if a computer could do a better job at that sort of task. Besides Im sure Human B wouldnt want Human A reading that cyber sex chat log.

Re:Huh? Aren't humans 100%?

Quite simple:
With 10 messages (after automatic spam detection) humans are 100% accurate.

With 1,000 messages, (before automatic spam detection)
humans are less than 100% accurate.

The experiment was done on 5849 messages.

Remember; one thing computers are good at is doing boring things repeatedly.

Re:Huh? Aren't humans 100%?

No, humans are not 100%.

If you see a strange name in your inbox with an odd title, that might be a Nigerian businessman, or it might be your long lost Nigerian brother.

I recently tried to order a t-shirt from this guy for a band he used to be in. I found his band because we have the same (semi-uncommon) name. So, he got an email From: himself. I had to send him two emails because he deleted the first one assuming it was spam.

I ordered some RAM for my dad a while back. He gets 200 spam emails a day (email addy in resume & web page), and he deleted the confirmation email from the RAM vendor. The RAM never shipped, and it took us a week to figure out that there was a problem.

People make mistakes all the time. Why is this an unexpected result? People are jackasses. This should be obvious.

Re:Huh? Aren't humans 100%?

Then megacorp could sue spammer into oblivion.

Or more likely, megacorp fires it's mail administrators for being incompetent and goes on about it's business.

Re:Huh? Aren't humans 100%?

I have never deleted an email I meant to keep

How could you possibly know? You deleted it!!

Re:Huh? Aren't humans 100%?

How can a spam filter be more accurate than humans? Humans are always the last step in spam filtering.. i use popfile and it catches 99% but it still needs me.. because im the only one capable of identifying spam 100% of the time.

And if the study posted about is accruate, of those 1% that are left, you will (if you're a perfectly average person) accidentally delete 0.16% of good messages. Surely you've deleted a valid message by accident before? I do it regularily, deleting 25 spam messages with a single good one embedded in it when I just woke up before I had my coffee is not a good thing ;)

At the very least, if you were given the same data as these tests, that would be true. Consider if you *didn't* use popfile - how many spams would you be deleting every day, and how many good messages would be accidentally deleted? I know that if I had to manually delete the two or three hundred spams interspersed with good messages, my false-positive rate (the percentage of good mail I accidentally deleted) would skyrocket.

So just be glad you've got popfile. Not only do you not have to go through as much spam, but you're also more accurate while going through the little you must.

Re:Huh? Aren't humans 100%?

Last week I ran a spam filter on all the email I recieved for the last several months. The filter came up with a dozen 'false positives' - messages that I had not flagged as spam when I manually classified them. 11 of them were clearly errors I made in my original classification. The 12th was a solicitation from the alumni association of my alma mater ....

Before I used a spam filter, I once missed a very important message whose subject line was something to the effect of "URGENT - DON't REBOOT THIS MORNING." That was a bad one to miss.

Of course humans make mistakes, and it is entirely possible for an automated or semi-automated system to be more accurate than a human alone.

IM Spam

Once Email Spam is eliminated, then IM spam will begin...

wait, WTF?

I presume they mean more accurate than a human that was only looking at the subject line? I fail to see how someone could misclassify an email after they'd already opened it unless it was some kind of marathon testing, which would be totally unrepresentative of any real life situation. Once you're getting 6,000 messages, it's time to reach for "Delete All" and change your address, methinks

Re:wait, WTF?

6000 over what period?

This represents 8 days worth of spam for me. Yes, ~800 per day.

My address has been valid for 10 years. Why should I change it? Bogofilter is currently letting 2-3 per day into my inbox. I generally check for false-positives, but as the training has progressed, I am finding none anymore.

I plan to implement a single-shot, one try notification sender. I.e., if the mail gets classified as spam: lookup the mx record for the envelope return address, if it's nonexistent, lookup the a record. Make a connection and try to deliver a message indicating their message (include subject reference) was identified as spam, include a way for them to reliably get a message through to me. If any of the smtp exchange or address lookup fails, just forget it, they're probably not real anyway.

Not the best idea

What you're planning has already been done, it's called TMDA, and it's not such a good idea. You're going to send out 800 "challenge" emails per day - have you given any thought to how many of those will be genuine addresses, but have nothing to do with the spam you receive because they just happen to be the joe-job victim? These kind of challenge/response systems may slighlty alleviate your own suffering through spam, but at a cost to all those unfortunate enough to have had their email addresses faked. And if the sheer impoliteness of such net behaviour doesn't put you off, note that you're using up more of your own bandwidth to send out such challenges

If any of the smtp exchange or address lookup fails, just forget it, they're probably not real anyway

It would make a lot more sense to make these kind of checks when you're receiving the email in the first place. Reject at the SMTP level - you never accept and process the spam in the first place

2+2=3

the average human is only 99.84% accurate. Both filters are reporting to have reached accuracy levels between 99.983% and 99.984%

Am I crazy or is that nowhere near "10 times better"?

Number of significant digits...

Human=99.84
New proggie=99.984

So the human misses .16% and the machine only missues .016% hence the machine is 10 times better.

Re:2+2=3

Congratulations, Mon Ami.

You have just unlocked the secret of virtually every news report that says "ten times more likely."

To get cancer. To have a heart attack. To suffer from the heartbreak of psoriasis. Whatever.

Yes, these numbers indicate "10 times better," and if you were to ask the reporter how likely am I to avoid cancer in both situations, these are the sorts of numbers he would show you.

Eat health food and your chance of having a heart attack is 99.984%. Eat too many donuts and your chance of having a heart attack is 99.983%, 10 times worse!

Always, always, always ask to see the raw numbers so that you know what "10 times worse" means.

Then ask if the numbers were collected by phone survey. If they were, throw them all away and have donut and a cup of coffee.

KFG

can it be used with SA?

can this be used with Spamassasin, or is a stand alone program? Does it need something like Amasis to run?

CB

Re:can it be used with SA? -yes

A CRM114 plugin for SA is available, thanks to Devin Nate:

http://bugzilla.spamassassin.org/show_bug.cgi?id =2 301

Who is sending that one?

If your email is indistuinguishable from spam by a human, perhaps the problem isn't the receiver. It's the sender.

Forgive me if I don't feel any pity that some moron's email gets filtered to the junk bin because I couldn't discern it from spam.

To get this new spam filter...

Just enter a valid email address, and hit submit!

Better

Well, it certainly sounds better than the pay-per-email "postage" idea. If postage hasn't stopped snail spam, why would it stop e-mail spam?

less thought for me...

...and only one locked pod bay door per 6250, I like those odds.

Hmmmm

Probably used those same people who open viruses as test subjects.

i tend to think...

that i'm 100% accurate.

maybe some of those people just dont know where their 'del' key is, or what it does...

Obligatory Q... When will mozilla/TB have them?

I reached the conclusion of "two filters better than humans" by using two sequential filters:
server side spamassassin, and a couple of simple procmail recipes. They have kept almost all the SPAM away.

However, it is good to see such good techniques becoming available and we can hope to see them as straight forward usable tools.

So, when will mozilla/TB (or your favourite server side or client side filter) get them?

S

actually

it's not that humans are not as accurate, it's that 1 in X times we really do want a mini camera or free porn. It is what seperates us from those cold, heartless machines.... mini cameras and porn....

News story Headline

My Machine outhinks me!!"

I've seen better stories in Highlights for Children

I'm sure they're great, but...

I'm also sure that Yahoo's "SpamGuard" was great when they first introduced it. Now, It catches roughly half of all the spam I get. Why? Because people have figured out how it works and taken advantage of it. The same will happen with any content-recognition-based spam software. In the extreme case, even if a piece of software were 100% accurate at saying "This piece of e-mail looks like spam," then spammers would just make their e-mails look exactly like e-mail from one of your buddies. How could software ever tell the difference between:

Hey, dude, check out this website I found. There are some hot naked chicks and stuff. Sweet.
Signed,
Your Buddy

and

Hey, dude, check out this website I found. There are some hot naked chicks and stuff. Sweet.
Signed,
SpamKiddy

Even a human can't tell the difference. The only real difference is who they're from.

Here's the real test

I'm very happy with POPFile but there's one thing it just can't handle -- bounces from spam with my domain forged in the header when the original text isn't included. And how could it know? The response is the same whether it's to my mail or to spam. The domain is a clue, I guess, but otherwise it seems like an impossible task. I just let them be sorted into my inbox and delete them manually.

If these filters can hit 99.99% with those, I'd be quite impressed.

Adaptive adversaries

It's really easy to design an effective solution when the problem is purely mechanical or natural. As long as you're working with spammers who don't adapt, you can slice through their shitstorms very effectively.

But when a single solution becomes mainstream, spammers will adapt to it. Bayesian filters tend to work very well, but now spammers are adding sprawls of randomly generated green-light text to offset the filter's score.

Google found an excellent way to rank websites, but then it became widespread enough that webmasters began to game the system it had created. It's been playing catch-up ever since.

Once the adversary begins to adapt, we lapse into the same cat-and-mouse game of technological barriers and counter-barriers that we've seen so many times before.

Could somebody explain this to me...

I order all kinds of stuff online, wouldn't the receipt emails look like spam? My current spam solution is very simple:

1. display my email online as little as possible

2. use a number of addresses that all filter into one account, then filter by the sent-to address... this has turned up some VERY interesting results, for instance. I used [e-mail] for an order from Dell, and NEVER used it or even typed it anywhere again, and started get spam about 6 months later, and I mean the nasty stuff, no just innocent stuff from Dell resellers...

3. i built a rudementary filter that looks for viagra,free,debt,enlarge, etc... if the sender is not in my address book, and the email contains these words, it is sent to a "check these out" folder...

How might a spam filter help me out without zapping confirmation type emails?

Re:Could somebody explain this to me...

If you don't control the mail server to create aliases for yourself, you can also employ RFC-compiliant suffixes to your e-mail address. For example:
[e-mail].

Re:Could somebody explain this to me...

Unfortunately, even though it's RFC-compliant, I've found probably half the sites I have to give my email address to won't grok the [e-mail] syntax. It's convenient when it works, but it doesn't work enough to rely on. No, throw-away spam-bait email addresses that you use for 6 months at a time for all online ordering and the like, then eventually trash when they get too spam-ridden are the best solution I know of.

Re:Could somebody explain this to me...

[e-mail] should go to [e-mail] as per the RFC (the +filtername is carried but not used by servers, or at least it shouldn't be). Some email clients will allow you to use this for such things as folder sorting (i.e. username+foldername goes into foldername automatically). If this worked consistently, it would be good for people who don't have the ability to make more usernames.

AFAIK, username-filtername will still just go to username-filtername, i.e. you have to configure your mail server to handle username-filtername separately from username. This works great when you can specify as many usernames as you want (i.e. if you manage your own server or have a catch-all on your domain).

Maybe you are talking about something different than the original poster?

One reason why the - would work when the + does not is that the - can appear multiple times, so it just another valid character (like a letter, number, or underscore). The + can only appear once, so many servers can ignore it, drop it, or puke on it.

Interestingly enough, while the (optional) challenge/response system is what gets the press, the main purpose of TMDA is to create aliases like username-filter (and then filter based on them). Thus the name: *Tagged* Message Delivery Agent. The -filter is the tag of Tagged.

This is just carp.

Spam is what is defined by humans as Spam.

To determine the accuracy of a spam detector, it is necessary first to come up with a sample of what is or isn't Spam. (I'd assume a human would do this?) So the best result we can get be evaluating humans is how often they agree with the result of the initial label.

This figure probably won't be 100%. People have slightly different concepts of what mail is requested vs. unwanted, and what is advertising or useful information. So there is a valid possibility of disagreement.

That doesn't mean humans can't do the job accurataly. (After all, if they couldn't, then the initial human-made labels would themselves be wrong and any data based on them meaningless!)

If the training data is labeled with the same criteria as the test data, it is obviously possible that a trained system can acheive results which more closely agree with the test data. They are being trained on similiar data. But that doesn't mean that the system is MORE accurate at detecting spam than humans. It means that the system agrees with a particular human (or set of humans) more than other people do in a labelling of spam/non-spam.

For all we know, the evaluators idea of spam is "wrong".

Re:This is just carp.

They are learning algorithms. For measuring their accuracy you have to assume that the data is correctly classified so you can see how they do.

The point is that humans also aren't perfect. Have a person classify 10000 emails and they will make a few mistakes. Point out those mistakes, and they will say "yes, I got that wrong it is an email from my wife reminding me to pick up milk and not a spam trying to sell me printer ink, I must have been day dreaming."

Just like if you give a person a document and say "find all the spelling errors" they will probably miss some. This is not because they have a different definition of how those words are spelt, it is because they made some mistakes.

For the training/testing data, some double checking needs to be done to find the mistakes the human classifying it almost certainly made.

It's a pretty normal situation in any machine learning application, you don't have to be perfect to be as good as a human - after all humans are only human.

The true test of a spam filter...

Results of new spam filters cannot help but to be bogus... The true test of a filter is how well it works *after* all the spammers know how it works and try to circumvent it.

Image Noise Reduction and Machine Learning

I find it interesting that an algorithm that was originally for image noise reduction [ee.ubc.ca] found it's way to Machine Learning through a company whose purpose is to impliment noise reduction in audio. From my Googling, I think this is the first time anyone has used Baysian Noise Reduction in Machine Learning. Does anyone know otherwise?

Let's get this straight people!

client/server-side filtering does NOT solve the problem!

The biggest problem with spam is the invasion of third party computers on the Internet. The ILLEGAL activity spammers perpetrate by breaking into machines, forging headers and hijacking servers.

Any filtering method does not address this most serious problem, and even if you do not see any spam in your inbox, you're still paying for the bandwidth and system resources these spammers steal.

Stop with the filtering algorhythms and take some of that energy and contact your local Attorney General, DA and FBI and demand that they prosecute these people who are BREAKING THE LAW.

One number not enough

Saying an algorithm is x% accurate is not sufficient, because there are two kinds of errors: false acceptance of spam, and false rejection of non-spam. Personally, I'd settle for 90% false acceptance if I knew the false reject rate was 100% rather than have a program that was 99% at both.

How not to evaluate filters

The study referenced is:

• On the author's mail (where all he does is probably talk about CRM114 and probably does not subscribe to many newsletters or non-technical mailing lists).
• A pre-trained filter. It can't be compared apples-to-apples with any filter that doesn't require training.
• Using his own filter on his own mail! Of course it does well.

... to mention a few of the problems. The statistics and methodology behind these claims are really questionable. I think both Consumer Reports and PC Magazine have both done better evaluations of spam filters (read that however you want).

Also, I wonder how many people have actually looked at CRM114 and tried to use it.

The really interesting thing about CRM114 is the windowed polynomial hashing technique used although there's some evidence that it can work just as well (if not better) on a much smaller window of only two tokens. I'm hoping someone will do a full exploration of the idea for SpamAssassin's Bayes module.

Do we buy viagra 0.16% of the time

If we humans are only 99.84% accurate, then 0.16% of the time we will incorrectly think the email is real and buy viagra ? I don't think so.
I read the email and delete it. Exactly the same as the spam filters do it, only MORE accuratly. I think the tests applied would have been between a human reading the header of an email and deciding whether to open it or not verses the spam filter making the decision for us. BUT the spam filter makes its decision by opening the email. Therefore to have a proper comparision I should be allowed to open the email as well before I make the decision. Therefore I am 100% accurate.

The CRM114?

I bet it allows messages from General Jack D Ripper [imdb.com] or any email that contains the secret phrase "purity of essence", "peace on earth" or "precious bodily fluids".

Human accuracy doesn't scale linearly

I'm not surprised a filter beat the human, considering the study used a sample of 5849 messages. As the sample size increases, the filter's accuray will increase, and the human's will decrease. Furthermore the higher the spam/real ration, the better the filter will do in comparison to a human trying to sort at a reasonable speed. The reason being humans tend to skim, and rairly actually read entire subjects, much less messages. Give a human 5000 messages and an hour and he will probably make some mistakes. On the other hand, in 10 messages, the human will probably be 100% correct. Most email filters rely on this already, as they tend to err on the side of caution. With the bulk of the spam taken out, it is not a burden to have the human check the iffy bits. Furthermore the type of email can mislead humans. A business-type email sent to someone's personal email is much more likely to be mistaken as spam, and vice versa. The main disadvantage of automated filtering is people generally have an idea of when a really important e-mail is going to come (the type that false positives are completely unacceptable) and who it will be from.

Spot the reference...

CRM114 was a piece of encryption gear in Major Kong's...err, my B-52 in the movie Dr. Strangelove [imdb.com]. It allowed only properly coded messages to be received by the crew. When the Soviet SAM detonated near the airframe, the CRM114 was damaged and the crew could not get the recall order.

Kong: (announcing through headset intercom )

This is your attack profile: to insure that the enemy cannot monitor voice transmission or plant false transmission, the CRM114 is to be switched into all the receiver circuits. Emergency phase code prefix is to be set on the dials of the CRM. This'll block any transmission other than those preceded by code prefix. Stand by to set code prefix.

ObKubrick: In 2001: A Space Odyssey, one of the pods was marked with the designation CRM-114. And in Clockwork Orange, Alex is injected with serum 114. I suppose CRM-114 is to Kubrick as THX1138 is to Lucas.

Dobly, on the other hand, is from This is Spinal Tap [imdb.com], a mispronounciation of "Dolby" by David St. Hubbins's girlfriend:

Jeanine Pettibone: You don't do heavy metal in Dobly, you know.

Not to mention that it probably avoids trademark infringement (though I wouldn't put it past Dolby Labs or Thomas Dolby to raise a stink).

Maj. Kong

Dolby-type noise reduction algorithm called Dobly?

Dolby noise reduction works by filtering a spectrum into a bunch of bands, each of which are compressed (in an audio sense, not in a digital sense), and recorded to tape. On playback, they go through an expander...how does that concept translate to spam filtering? It can't be "dolby-type", that doesn't make any sense...

Digital signatures and a public key infrastructure

...are still the only real solution to the issue of trust, reputation, and accountability on the Internet. We need it for so many other things in addition to guaranteeing email legitimacy.

If every user or at least every server had a key and we all signed each others keys creating a web of trust and only accepted signed and trusted mail the spam problem would be solved. I really dislike the way SSL certificates are handed out. A central CA is a very bad idea due to the cost and browser lock-in issues etc. With GPG and web of trust if you want to run a mail server you need to talk to a friend who is already running one and get them to sign your key. Perhaps we could even use DNS to propagate and cache the keys and sigs. If you sign a key that turns out to be a spammer you better revoke that signature fast before the person upstreeam from you revokes yours. Problem solved. Now if only we could get the big guys to go along with it...

Share the luxury

Having such a powerful statistical spam filter is definitely a luxury. I have no difficulty believing the accuracy values presented here. I have had experience with spamprobe, CRM114, bogofilter, spambayes, and spamassassin and all of these do an amazing job to the point where spam no longer exists (for you).

Which leads to me plug a little project called WPBL [pc9.org] that uses exactly these types of statistical spam filters to spot spam sources in a distributed fashion. Each project member uploads hourly the IPs they see relaying spam and non-spam, where the 'decision' is made by these extremely reliable filters. This effectively converts your regular mail account into an intelligent spam-trap that feeds a central blocklist.

The more members we get, the better we can identify active spam sources around the world. This information is then used by some sites for quite large-scale blocking [dnsbl.net.au]. Since you're doing all this filtering processing anyway, why not also share "what you learn" (the IPs that are spamming you)?

If this grabs your interest, read up on the reporting scripts [pc9.org] or alternatively, the open WPBL data upload protocol [pc9.org] if you want to code your own report generator. Bandwidth usage is minimal.

Well

Well if the human was given the chance to read the body text as well like the filters do, then they would be 100% able to delete their own spam.

DRACO-

Re:How can a human be wrong?

No matter what, in the end, the human CANT be wrong... right?

[*Bing* -- mail from VP of sales pops into my inbox. Subject: "Making money fast!"]

[*Bam* -- I hit delete, thinking "Stupid Spam!"]

Ahh, shit! Lookie, a human screwed up.

The filter would have actually examined the message and probably decided that it was legitimate.