Internet Content Filtering

Learn How to Protect Your Family from the Worst of the Web!

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The Internet is magnificent in its resources for families. Educational resources abound. Kids can easily find help for their homework blues without venturing to the library. Kids can chat with friends from far away for free; friends who, probably just a few years ago, they would never hear from again. And, of course, there s plenty of entertainment to satisfy the whole family once the chores and homework are complete.

However, the Internet can often be an inappropriate place for kids to surf unsupervised. Plenty of content is only appropriate for mature audiences. And, sadly, there are bad seeds , those who the children never should talk to.

Help keep your children away from these unsuitable materials. Many search engines and directories have filters and options that only return pages that have passed a particular profanity or kid-safe filter. These types of filters vary from web site to web site, but may do one of the following:

* Only allow you to search a selection of links picked by the site s editors to be kid-safe or free of profanity.

* Not show links containing profane words, these being words designated by a site to be profane. This list may not contain all possible profane words or combinations.

* Show links containing profane words but block out the profane words with asterisks, dollar signs, or other symbols. Again, the blocked-out words are those the site deems profane and might not include all such words.

Unfortunately, no filter can be 100% accurate.

Here are some search engines that have filters you can enable to try to weed out inappropriate content.

AltaVista
http://www.altavista.com/

Above and to the right of the search query box you can find the link labeled Family Filter . Turn on this filter to cause AltaVista to filter out inappropriate content. Be sure to read the linked-to FAQ (Frequently Asked Questions) before using this filter. Again, no family filter is 100% accurate, but it s better than nothing.

Ask Jeeves For Kids
http://www.ajkids.com/

You can provide kids with their very own search butler. Ask Jeeves for Kids is a special version of the popular Ask Jeeves web site geared towards the younger set. It is used the same way as the normal Ask Jeeves just ask a question and click the Ask button.

You will notice the site design is quite different from the main Ask Jeeves. The page is colorful and includes fonts more suited for kids. There are links to games, study tools, news resources, and message boards. Be sure to check out Jeeves hat as you move your mouse over each resource

According to the Parents page, Ask Jeeves For Kids only searches for G-Rated information. However, they do warn that since web sites change, there is no guarantee that adult content cannot slip through the cracks. Still, they do a good job at trying to filter out information, so if you have children surfing the net, you may want to point them over to this popular resource.

Google
http://www.google.com/

Visit the Advanced Search link and take a look at the SafeSearch section. Click the Filter using SafeSearch radio button to cause Google to only returns sites that match Google s SafeSearch filter. This filter attempts to remove material containing pornography or sexual content, but it is not and cannot be 100% accurate. Click the link SafeSearch on this page for more information about this filter.

You can also click the Preferences link from the front page to set preferences on how you want Google to search through documents. From here you can enable the SafeSearch setting by default. These preferences are placed in the form of a cookie stored on your browser, so if you disable cookies your preference choices will not stick. Be sure to press the Save Preferences button when you are done with your choices or they will not stick.

Lycos
http://www.lycos.com/

Click on the Parental Controls link on the front page (located under the search bar), or turn on the Adult Filter from the advanced search page to enable the Lycos SearchGuard . This feature attempts to filter out sites containing inappropriate or offensive material such as adult, violent, hate and weapons-related content . Note that while no filter can be 100% effective this is a good start.

You may also want to visit the following family and kid-friendly Lycos sites:

Lycos Family Zone
http://familyzone.lycos.com/

Lycos Zone (For Kids)
http://lycoszone.lycos.com/

No matter which site you use, realize that no filter can be 100% accurate. All it takes is a little web browser knowledge to defeat cookie-based filters. Inappropriate sites can and sometimes will slip through the cracks . Thus, I recommend that you always supervise your kids Internet usage whenever possible. These filters, however, may make your supervision easier and your entire family s Internet experience more enjoyable without any surprises.

About the Author

This article was written by and copyright 2002 Andrew Malek, Internet Search Guru and author of Find Stuff On the Net, an e-book that can show even beginning computer users how to navigate the Internet without fear. Catch-up with your kids knowledge when it comes to using the net. For further information and free snippets of the book, visit http://www.findstuffonthenet.com/

Learn How to Protect Your Family from the Worst of the Web!

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So What Makes a Good Spam Filter Anyway?
By Alan Hearnshaw

Spam Filters. Most of us know we need one. Some of know we need a better one, but how many stop to think what actually makes a good spam filter in the first place?

This is not just a rhetorical question. It is a question that many users and many developers - do not ask, and consequently, goes unanswered.

Maybe this could be better answered by defining here the qualities of the perfect spam filter. We ll call our perfect spam filter the SpamSplatter 3000 . Here are some of the defining qualities of SpamSplatter 3000

1. It requires zero interaction from the user.
2. It produces zero false positives (good messages identified as bad) and zero false negatives (bad messages identified as good).
3. It is transparent that is, you only ever see good messages and never need even be aware that spam exists.

That s it. Not much of a shopping list is it?
Of course, SpamSplatter 3000 hasn t been invented yet (and if it does, I want a piece of the action), but it does give us a frame of reference when looking for the best filter we can find.

Let s take each point in turn:

It requires zero interaction from the user
There are two kinds of filters that come near to this ideal currently: Bayesian Filters and Community Filters.
Bayesian filters strip messages down to small word bites , or tokens and maintain a database containing lists of good and bad tokens. When a new message is encountered, the filter strips this message down to tokens, compares it to the database, and applies a formula based on the British scientist Alan Bayes formula for probability calculation.
Over time, the Bayesian filter learns the characteristics of spam messages.

Community Filters simply work on a voting system whereby every user that receives a spam message votes it as spam. This information is stored on a central server and when enough votes are received the message is banned from all users in the community.

As can be seen, the user interaction from these types of filters is mainly limited to two button operation correcting wrongly identified messages and the more accurate the filter, the less those buttons are used.

OK, so that s pretty good. Not exactly zero interaction, but if the filter is accurate enough, then it should be pretty near. That brings us to point two:

It produces zero false positives or negatives
This is the area in which most spam filter development is concentrating and things are getting pretty good nowadays. It is not at all unusual to see an efficient modern filter achieve accuracy of 96% or better. It is, of course, far better to have a false negative than a false positive if you are ever going to tear yourself away from the killed mail folder!

Of course, by definition, community filters cannot reach 100% accuracy as someone has to be getting the spam to be voting it as such!
Theoretically, a Bayesian filter may be able to eventually get quite close to 100% accuracy, so at least there is hope there.
Content based filters (those that look for certain words, phrases or other indicators in a message to identify it as spam), will almost certainly not get much higher accuracy figures than the best of them can achieve today. Adapting to changing spam requires new filters to be created on an ongoing basis.

And finally, we come to the holy grail of spam filtering:

It is transparent
Strangely enough, not enough work seems to be done in trying to achieve this goal. Some of the best filters on the market today identify spam with impressive accuracy and then simply place them in a killed mail folder for your later perusal.
Now, forgive me if I m missing something here, but isn t the point to save you having to wade through the junk mail? Isn t that what you bought the filter for? With the SpamSplatter 3000 , you don t need to do that.

As we haven t achieved 100% accuracy yet (and probably never will), the only way to free us from checking the killed mail folder is a challenge/response system. This is where a message is automatically sent back to the sender requiring them to take some action for their message to actually be delivered.

Some systems tend to go overboard with the challenge/response system. These systems - often called Whitelist systems - block messages from anyone that isn t in the user s friends list. Guaranteed 100% effective, but too drastic a measure for most users.

Now, it seems that the most intelligent use of this system would be to send challenges only to messages that were flagged as questionable . Good message can be delivered, definite spam can be deleted and questionable ones would earn themselves a challenge message.

So, to sum up, let s rewrite the qualities of our perfect filter and get a shopping list of what to look for while we wait for the SpamSplatter 3000 to arrive:

1. Simple, minimal setup and maintenance.
2. Extremely low rate of false positives and as few false negatives as possible.
3. A transparent fail-safe mechanism whereby the victims of those false positives can force the message through to you.

It s simple really. Now, who s going to build me this SpamSplatter 3000 ?

Alan Hearnshaw is the owner of http://www.WhichSpamFilter.com, a site which provides weekly in-depth spam filter reviews, user help and guidance and a community forum.
alan@whichspamfilter.com

About the Author

Alan Hearnshaw is a computer programmer and the owner of http://www.WhichSpamFilter.com, a site which provides weekly in-depth spam filter reviews, user help and guidance and a community forum.

Learn How to Protect Your Family from the Worst of the Web!

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In a word Bayesian spam filters are “intelligent”. Bayesian spam filters are intelligent in so far as they’re capable of comparing two sets of information and acting on the result. This is in direct contrast to the vast majority of other spam filters who use pre-built rules to decide which e-mail is spam and which is not.

Bayesian spam filters can take one group of legitimate e-mail and another group of spam and compare the values and data of each. The definition of legitimate e-mail that it creates at the end of this comparison session is what it uses going forward to scan your inbox for spam.

FYI Bayesian spam filters are named after Thomas Bayes an 18 century cleric who created something known as Bayes Theorem. In summary Bayes Theorem is as follows: ..”in statistical inference to update estimates of the probability that different hypotheses are true, based on observations and a knowledge of how likely those observations are, given each hypothesis.” In plain English it looks for obvious repeating patterns to form an “opinion” on something. In spam filter terms that “opinion” becomes a rule which keeps you spam free (or pretty close

The really neat thing about Bayesian filters is that they’re capable of learning. For example if they decided to block an e-mail because the filter perceived it as junk but the user marked it as valid mail the Bayesian filter then knows not to block that type of e-mail in the future. So, in time, this type of spam filter learns enough to block spam far more effectively. AOL have embraced this type of spam filter with the launch of AOL 9.0 and AOL Communicator- if the big dog wants it then it must be worthwhile?

So what Bayesian spam filtering options are available to you? Well quite a few to be honest and you’ll be pleasantly surprised by some of the names involved The first one on the list is AOL with their AOL Communicator product. The spam filtering features in AOL Communicator and AOL 9 are, to be honest, impressive. Think what you will of the provider themselves AOL Communicator is an excellent product and is suitable for use by both PC and Mac OSX users.

Next up we have Eudora. The nice folks at Qualcomm have designed an excellent e-mail client that also has built in Bayesian spam filtering. I’ve used Eudora in the past and it’s a neat little package. Again the benefits here are advanced integrated spam filtering with your e-mail automatically. Mac OSX and OS9 users are in luck with Eudora providing support for both.

If you’d like to know more about spam filters or just spam in general please do drop by http://www.spam-site.com for more information.

About the Author

Niall Roche is the content author and owner of www.spam-site.com which reviews and tests spam blockers.

Learn How to Protect Your Family from the Worst of the Web!

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A common problem with filters is the fact that they are
a one-size-fits all solution to SPAM. The rules are concrete
and only change based on input from updates from the Anti-spam
service.

SPAM changes too quickly to make that method effective.
Additionally, what is SPAM to you may not be to someone else.
That is where Bayesian filters come in.

They are very effective at eliminating SPAM and have
very low false-positive rates for their users.

Bayesian filters are based on Bayesian logic, a branch
of logic named for Thomas Bayes, an eighteenth century
Mathematician.

This type of logic applies to decision making by
determining the probability of a certain event based on the
history of past events.

Using this as a model seemed a logical step for SPAM
filtering. If you can predict what SPAM will look like now
based on what is has looked like in the past, you are halfway to
the solution.

To finish solving the problem, Bayesian filters were
developed to be dynamic and continue to be effective as the SPAM
changes.

Bayesian filters are content based. They look for
characteristics in each email that you receive and calculate the
probability of it actually being SPAM.

These characteristics are generally words in the content
and the header file information that each email contains. They
can also include common SPAM HTML code, word pairs, phrases, and
the location of a phrase in the body of the email.

Typical words in SPAM would be “Free” and “Win”, while
“humility” would probably not appear. The filter begins with a
50% neutral score for the email, and then adds points for SPAM
characteristics.

Likewise, deductions are made for non-SPAM characteristics
present. The total score is calculated and then action is taken
based on its likelihood of being SPAM.

The filter does not assume that all arriving email is
bad, rather that all email is neutral and should be considered
equally.

Bayesian filters are better than traditional content
scoring filters in that they are trained by you to recognize
your email.

A doctor, for example, might have many emails
legitimately using the word “Viagra”. A traditional content
scoring filter would probably shoot that email to the SPAM
folder, or delete it.

This would result in a high false-positive rate for the
doctor, even if you don’t want Viagra emails. The filter will
build a list based on the doctors email use and corrections to
incorrectly marked email.

The initial training period may be a little time consuming,
but once complete offers a tailored solution to SPAM
control for each user.

In addition to protecting the good email, the filter makes
it difficult for Spammers to trick as every filter will have
individual requirements.

That being said, Spammers do have a few weapons in their
arsenal to attempt to circumvent Bayesian filters. The easiest
would be to create SPAM that looks like an everyday letter.

This would remove their ability to use typical marketing
techniques and so is not as likely with normal commercial email.
For the purveyors of fraud, however, this would be easier.

Spammers could also so weight a message with a common
good word, or distort the bad ones, that it becomes scored as
neutral or lower and get through.

Once correctly marked as SPAM by you, though, the filter
will adjust and not be fooled again. This automation and
ability of the software to grow as you and SPAM change over time
is key to the significance of these types of filters.

Widespread use of good Bayesian filters will not only
eliminate SPAM on your end, but would reduce the practice of
Spamming altogether. If they cannot get the mail through, they
are just wasting their time.

About the Author

Debbie Hamstead is the webmaster of http://www.StompingOutSPAM.com
Offering a comprehensive Quick Start Guide to keeping SPAM out
of your inbox. She also manages http://www.nichesites4profit.com