Two Spam Filters 10 Times As Accurate As Humans 487
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."
Comment removed (Score:5, Insightful)
wait, WTF? (Score:5, Insightful)
SPAM definition (Score:2, Insightful)
Re:Huh? Aren't humans 100%? (Score:2, Insightful)
If I say it is spam, I'm not reading it... and I am deleting it.
Any software that tries to stop me is removed via because it is faulty.
Re:Huh? Aren't humans 100%? (Score:5, Insightful)
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%? (Score:5, Insightful)
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%? (Score:5, Insightful)
I'm sure they're great, but... (Score:5, Insightful)
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.
Re:Huh? Aren't humans 100%? (Score:5, Insightful)
Adaptive adversaries (Score:5, Insightful)
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.
Re:Huh? Aren't humans 100%? (Score:5, Insightful)
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.
This is just carp. (Score:3, Insightful)
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:Huh? Aren't humans 100%? (Score:3, Insightful)
The true test of a spam filter... (Score:5, Insightful)
Re:Bleh. (Score:2, Insightful)
More accurate than what..? (Score:2, Insightful)
Let's get this straight people! (Score:4, Insightful)
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.
Re:Huh? (Score:1, Insightful)
Re:This is just carp. (Score:5, Insightful)
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.
Re:Huh? (Score:2, Insightful)
economics of spam (Score:1, Insightful)
Re:Huh? Aren't humans 100%? (Score:2, Insightful)
I wonder if it would be possible to sue these spammers for interfering with a business transaction. Granted, the amount in question here is minimal, but just the possibility that a spammer could be found liable for this might deter some of them.
If that doesn't work we should sign up every megacorp CEO on every spammer list possible, and hope s/he misses an important memo costing megacorp millions. Then megacorp could sue spammer into oblivion.
One number not enough (Score:5, Insightful)
How not to evaluate filters (Score:5, Insightful)
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.
Re:Huh? (Score:2, Insightful)
That's an easy one. The computer is 10 times better at recognizing what it has decided is spam. We humans are lucky to even be in the same league.
Now that you understand that, you're one step close to being "computer literate".
Do we buy viagra 0.16% of the time (Score:3, Insightful)
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.
They're trying to sell you something (Score:3, Insightful)
Re:knowspam.net (Score:3, Insightful)
Re:Huh? Aren't humans 100%? (Score:4, Insightful)
Human accuracy doesn't scale linearly (Score:5, Insightful)
Re:I'm sure they're great, but... (Score:3, Insightful)
Re:2+2=3 (Score:5, Insightful)
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
Re:Huh? Aren't humans 100%? (Score:1, Insightful)
Re:Huh? Aren't humans 100%? (Score:5, Insightful)
Re:Huh? (Score:2, Insightful)
Re:Huh? Aren't humans 100%? (Score:5, Insightful)
Re:Huh? Aren't humans 100%? (Score:1, Insightful)
Lots of people don't know what popups are.
Yes, we call those people "surfers who don't use Internet Explorer" (seeing as pretty much every other browser has options to kill them).
SCNR
Digital signatures and a public key infrastructure (Score:3, Insightful)
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...
Re:2+2=3 (Score:3, Insightful)
I totally buggered that whole section, but it was just so funny I let it stand with the errata note that I had buggered it.
Ironically people know I "eat healthy," so I'm frequently asked where they should go to buy healthy food, to which I almost always reply:
"For God's sake man, whatever you do, don't go in the health food store!
"Well. . . where do I go then?"
"They've got these things now called "Supermarkets." Look, over here, brown rice, dried beans and lentils. Over here, the produce aisle. You need frickin' binoculars to see the end of the thing. Broccoli, Bok Choy, squash, potatoes to the ceiling, it's the middle of February and there are crates of oranges that were hanging on the tree a few days ago. Why go anywhere else?"
"But, but . . . what about organic?"
"Here, take my binoculars, look down there. No, to the right a little, yeah, see? A whole organic section if you want. Supermarkets today aren't the supermarkets of 20 years ago. They're catering to customer demand. Go figure.
But really, if you want my advice? Save your money. Only buy organic if the price is the same. If you eat the "normal" stuff there's a 99.84% chance it won't kill you. If you eat the organic there's a 99.984% chance it won't kill you, and they got those numbers by taking a phone survey, or from the I Ching, or something like that."
KFG
Not the best idea (Score:5, Insightful)
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
Re:Case study in linguistics (Score:3, Insightful)
The language module does invoke other parts of the brain, such as general knowledge; however, there's nothing in the process that depends on it being in a human brain. Given that cognition is a physical process, one could postulate a computer program that could achieve the same results, even if drawing on a very large database of cultural information. The suggestion that language is "innately human" sounds a bit too much like carbon chauvinism, the belief that intelligence is an exclusive property of carbon-based life.
Re:Huh? Aren't humans 100%? (Score:2, Insightful)
Re:Help setting this up (Score:5, Insightful)
Sample (Score:2, Insightful)
A human doesn't have to determine if it's spam simply by the title.
The human should have all the advantages these filters have body / header / ip
Cheers
Well (Score:3, Insightful)
DRACO-
Re:No, no, no, not quite (Score:1, Insightful)
lies, damned lies, and... (Score:2, Insightful)
statistics.
This headline is misleading. I refuse to RTFA, because I imagine the "10 times as effective" figure comes from the article itself.
Come on, folks. The figures do, in fact, show a 10 times increase in effectiveness between humans and these filters. But what the heck does that mean? I have to question the studies. How did they come up with this 99.84% figure? Does it mean that one person will mis-classify about 16 emails in 10000 (a small number indeed)? Or did one or two outliers taint the data?
The important thing here is that we're comparing three averages. Were the conditions between the trials the same? Were the humans given time limits? Were the accounting methods accurate? Were the spam messages the same?
It's quite possible that these averages were bounded by possible error quantities (they should have been!) and that these were tossed when reporting the numbers to us. This was so that a startling result (10 times as effective as a human) could be shown in a headline. It's all about coming up with a flashy "fact".
It's very easy to make numbers say what you want them to say, so I'd be a little wary of running around to your friends "citing" this 10x improvement figure without doing some deep delving into the processes involved in arriving at the number.
Re:Adaptive adversaries (Score:3, Insightful)
But my old university, that has 40000 users, this has completely defeated their Bayesian filters. They say that the disk and CPU needed to have per-user bayesian training is prohibetively expensive, and they found that training for all users were doing more harm than good.
So, we definately need more approaches to the problem.
Re:Huh? Aren't humans 100%? (Score:5, Insightful)
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:
`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:Not the best idea (Score:3, Insightful)
I've gotten exactly one spam message in my inbox. That's an excellent percentage.
Excellent *for you* that is. How many unwanted emails have you sent out to joe-job victims? Here's my basic problem - after black/white list weeding, you're always left with a body of messages that you need to decide what to do with. Rather than taking on that burden yourself, you lay it off on others. That's just plain rude, and little different than the MO of a spammer - "let other people bear the costs of my own selfish actions"