| Added for You |
Hubs | Hubbers | Topics | Request |
| #1 in Business | Subscribe Email Print |
|
You are here: Home > Internet and Businesses Online > Spam Blocker > Spam Filters Explained |
|
Added for You - Spam Filters Explained
Dos and Don'ts for Jobseekers -mails carry a forged “from” address, there is little point in collecting this address to ban it in future as it is very unlikely to be the same next time.When looking for a job you can take advantage of many methods: either you turn to your friends’ protection, or surf the net and peruse the newspapers or finally use the services of the recruiting agency. Even if your friends have no influential connections or can’t assist you in employment at the present moment, let them know that you are seeking a new job. A worthy position may turn up in a week’s time. And during this week you are to conquer the net, newspapers and recruiting agencies. So, let’s start...Composing a resume. There can be two approaches here. You write it yourself or entrust this mission to one of the most reputable resume writing services. Each of the approaches has its strong and weak points, though of course a resum There are bodies on the internet that maintain a list of known “bad” sources of e-mail. Many filters today have the ability to query these servers to see if the message they are looking at comes from a source identified by this Internet-based blacklist, or RBL. While being quite effective, they do tend to suffer from “false positives” where good messages are incorrectly identified as spam. This happens often with newsletters. Challenge/Response Filters “Open sesame!” Challenge/Response filters are characterised by their ability to automatically send a response to a previously unknown sender asking them to take some further action before th Content – The Lifeblood Of ALL Business Online! Part 1 (of 4) What do they do? How do they work? Which one is right for me?
By Alan HearnshawWhat Is “Content?” - Two Different Online Business Models.Generally, anyone who has a venture that is “doing business” online will operate in a manner that will fall into one of two categoriesFirst option is that they will be involved in some kind of “virtual” business, in which all (or almost all) transactions, advertising and so on will take place online. As is often advertised as an asset of such a business, there will be no physical office or shop premises, no inventory to store or deliver and so on.Indeed, and probably most confusingly, there sometimes appears to be a lack of “product” at all!This is quite common where, for example, the “product” is some kind of online marketing system, which is marketed and Spam is a very real problem that many people have to deal with on a daily basis. For those that have decided to do something about it and start to investigate the options available in spam filtering, this article provides a brief introduction to your options and the types of spam filters available. Despite the bewildering array of spam filters available today, all claiming to the best one “of its kind” there are really just five filtering methodologies in general use today and all products rely on one, or a combination of these: Content-Based Filters “In the beginning, there were content-based filters.” These filters scan the contents of the and look for tell-tale signs that the message is spam. In the early days of spamming it was quite simple to look out for “Kill Words” such as ”Lose Weight” and mark a message as spam if it was found. Very soon though, spammers got wise to this and started resorting to all kinds of tricks to get their message past the filters. The days of “obfuscation” had begun. We started getting messages containing the phrase “L0se Welght” (Notice the zero for “o” and “l” for “i”) and even more bizarre – and sometimes quite ingenious – variations. This rendered basic content-based filters somewhat ineffective, although there are one or two on the market now that are clever enough to “see through” theses attempts and still provide good results. Bayesian Based Filters “The Reverend Bayes comes to the rescue” Born in London 1702, the son of a minister, Thomas Bayes developed a formula which allowed him to determine the probability of an event occurring based on the probabilities of two or more independent evidentiary events. Bayesian filters “learn” from studying known good and bad messages. Each message is split into single “word bytes”, or tokens and these tokens are placed into a database along with how often they are found in each kind of message. When a new message arrives to be tested by the filter, the new message is also split into tokens and each token is looked up in the database. Extrapolating results from the database and applying a form of the good reverend’s formula, know as the a “Naive Bayesian” formula, the message is given a “spamicity” rating and can be dealt with accordingly. Bayesian filters typically are capable of achieving very good accuracy rates (>97% is not uncommon), and require very little on-going maintenance. Whitelist/Blacklist Filters “Who goes there, friend or foe?” This very basic form of filtering is seldom used on its own nowadays, but can be useful as part of a larger filtering strategy. A “whitelist” is nothing more than a list of e-mail addresses from which you wish to accept communications. A whitelist filter would only accept messages from these people and all others would be rejected A “blacklist”, conversely, is a list of e-mail addresses - and sometimes IP Addresses (computer identification addresses) - from which communications will not be accepted. While this may seem like a good idea from the outset, a whitelist methodology is too restrictive for most people and, as virtually all spam e-mails carry a forged “from” address, there is little point in collecting this address to ban it in future as it is very unlikely to be the same next time. There are bodies on the internet that maintain a list of known “bad” sources of e-mail. Many filters today have the ability to query these servers to see if the message they are looking at comes from a source identified by this Internet-based blacklist, or RBL. While being quite effective, they do tend to suffer from “false positives” where good messages are incorrectly identified as spam. This happens often with newsletters. Challenge/Response Filters “Open sesame!” Challenge/Response filters are characterised by their ability to automatically send a response to a previously unknown sender asking them to take some further action before the Rank Well In The Search Engines With The Right Keywords y days of spamming it was quite simple to look out for “Kill Words” such as
”Lose Weight” and mark a message as spam if it was found.Through good keyword research, you'll be surely able to find the website containing the correct data that you need/want. It is extremely important for those who want to create (and eventually launch) a website to have good keyword research. When developing your website the html coding is not the only important part, you must recognize the keyword development. Writing about your products or services and submitting these articles to free content websites is a great way to market your website, as it provides you with a way of building pages that link back to your site, and as you know, the more links that point to your site the better your website will rank for the engines.If you want to rely on organic traffic from the search engines yo Very soon though, spammers got wise to this and started resorting to all kinds of tricks to get their message past the filters. The days of “obfuscation” had begun. We started getting messages containing the phrase “L0se Welght” (Notice the zero for “o” and “l” for “i”) and even more bizarre – and sometimes quite ingenious – variations. This rendered basic content-based filters somewhat ineffective, although there are one or two on the market now that are clever enough to “see through” theses attempts and still provide good results. Bayesian Based Filters “The Reverend Bayes comes to the rescue” Born in London 1702, the son of a minister, Thomas Bayes developed a formula which allowed him to determine the probability of an event occurring based on the probabilities of two or more independent evidentiary events. Bayesian filters “learn” from studying known good and bad messages. Each message is split into single “word bytes”, or tokens and these tokens are placed into a database along with how often they are found in each kind of message. When a new message arrives to be tested by the filter, the new message is also split into tokens and each token is looked up in the database. Extrapolating results from the database and applying a form of the good reverend’s formula, know as the a “Naive Bayesian” formula, the message is given a “spamicity” rating and can be dealt with accordingly. Bayesian filters typically are capable of achieving very good accuracy rates (>97% is not uncommon), and require very little on-going maintenance. Whitelist/Blacklist Filters “Who goes there, friend or foe?” This very basic form of filtering is seldom used on its own nowadays, but can be useful as part of a larger filtering strategy. A “whitelist” is nothing more than a list of e-mail addresses from which you wish to accept communications. A whitelist filter would only accept messages from these people and all others would be rejected A “blacklist”, conversely, is a list of e-mail addresses - and sometimes IP Addresses (computer identification addresses) - from which communications will not be accepted. While this may seem like a good idea from the outset, a whitelist methodology is too restrictive for most people and, as virtually all spam e-mails carry a forged “from” address, there is little point in collecting this address to ban it in future as it is very unlikely to be the same next time. There are bodies on the internet that maintain a list of known “bad” sources of e-mail. Many filters today have the ability to query these servers to see if the message they are looking at comes from a source identified by this Internet-based blacklist, or RBL. While being quite effective, they do tend to suffer from “false positives” where good messages are incorrectly identified as spam. This happens often with newsletters. Challenge/Response Filters “Open sesame!” Challenge/Response filters are characterised by their ability to automatically send a response to a previously unknown sender asking them to take some further action before th Accounting for Your New Business developed a formula which allowed him to determine the probability of an event occurring based on the probabilities of two or more independent evidentiary events.“I Can Keep It in My Head”No you can’t! No matter what size your new business is or will be, you’ll need to set up a system to keep track of your financial status. This must be done to prove your income to the government for tax purposes at the end of the year, to prove your status to the bank when applying for a business loan and to show you your own profitability and where you might make improvements to it. As you grow and perhaps incorporate, it will become the law for you to keep good accounting records and have them regularly audited by certified accountants.For now you don’t need that, but you might as well start out right.The Very Least You Can Get Away WithIn some situations, you don’t need to get a fan Bayesian filters “learn” from studying known good and bad messages. Each message is split into single “word bytes”, or tokens and these tokens are placed into a database along with how often they are found in each kind of message. When a new message arrives to be tested by the filter, the new message is also split into tokens and each token is looked up in the database. Extrapolating results from the database and applying a form of the good reverend’s formula, know as the a “Naive Bayesian” formula, the message is given a “spamicity” rating and can be dealt with accordingly. Bayesian filters typically are capable of achieving very good accuracy rates (>97% is not uncommon), and require very little on-going maintenance. Whitelist/Blacklist Filters “Who goes there, friend or foe?” This very basic form of filtering is seldom used on its own nowadays, but can be useful as part of a larger filtering strategy. A “whitelist” is nothing more than a list of e-mail addresses from which you wish to accept communications. A whitelist filter would only accept messages from these people and all others would be rejected A “blacklist”, conversely, is a list of e-mail addresses - and sometimes IP Addresses (computer identification addresses) - from which communications will not be accepted. While this may seem like a good idea from the outset, a whitelist methodology is too restrictive for most people and, as virtually all spam e-mails carry a forged “from” address, there is little point in collecting this address to ban it in future as it is very unlikely to be the same next time. There are bodies on the internet that maintain a list of known “bad” sources of e-mail. Many filters today have the ability to query these servers to see if the message they are looking at comes from a source identified by this Internet-based blacklist, or RBL. While being quite effective, they do tend to suffer from “false positives” where good messages are incorrectly identified as spam. This happens often with newsletters. Challenge/Response Filters “Open sesame!” Challenge/Response filters are characterised by their ability to automatically send a response to a previously unknown sender asking them to take some further action before th Analyzing One-Way Vs. Reciprocal Links ccuracy rates (>97% is not uncommon), and require very little on-going maintenance.Link building has become a cornerstone of SEO/SEM services so many are interested in knowing what makes a good link, what they should strive for, etc. that will provide the biggest impact on their site optimization.I was recently asked the following:"These days, I've heard alot about one-way links being better than reciprocal and worth more in respect to pr rankings. If possible, could you please offer me some insight on reciprocal vs. one way links."Here was my response:"We certainly believe that one-way links are better than reciprocal links, but not to the extent that many others assume. You hear a lot of talk about reciprocal links being dead and for a while we believed this is the direction the search engines Whitelist/Blacklist Filters “Who goes there, friend or foe?” This very basic form of filtering is seldom used on its own nowadays, but can be useful as part of a larger filtering strategy. A “whitelist” is nothing more than a list of e-mail addresses from which you wish to accept communications. A whitelist filter would only accept messages from these people and all others would be rejected A “blacklist”, conversely, is a list of e-mail addresses - and sometimes IP Addresses (computer identification addresses) - from which communications will not be accepted. While this may seem like a good idea from the outset, a whitelist methodology is too restrictive for most people and, as virtually all spam e-mails carry a forged “from” address, there is little point in collecting this address to ban it in future as it is very unlikely to be the same next time. There are bodies on the internet that maintain a list of known “bad” sources of e-mail. Many filters today have the ability to query these servers to see if the message they are looking at comes from a source identified by this Internet-based blacklist, or RBL. While being quite effective, they do tend to suffer from “false positives” where good messages are incorrectly identified as spam. This happens often with newsletters. Challenge/Response Filters “Open sesame!” Challenge/Response filters are characterised by their ability to automatically send a response to a previously unknown sender asking them to take some further action before th Internet Advertising Strategies for Success -mails carry a forged “from” address, there is little point in collecting this address to ban it in future as it is very unlikely to be the same next time.With the technological and conceptual breakthrough that internet has offered, internet advertising has become a full time employment option not only for companies, but for persons like you and me alike. Because most companies choose to go online with their businesses, the immense market that online advertising offers is like a new gold rush.There are two primary ways to advertise on the Internet:1. Register your Web site with major search engines so Internet visitors can find you;2. Place an ad banner for your site on another Web site that has a lot of traffic (viewers).Ad banners allow viewers to link to your site when they click on the banner. Internet Advertising Advantages Relatively cost-effective. The costs There are bodies on the internet that maintain a list of known “bad” sources of e-mail. Many filters today have the ability to query these servers to see if the message they are looking at comes from a source identified by this Internet-based blacklist, or RBL. While being quite effective, they do tend to suffer from “false positives” where good messages are incorrectly identified as spam. This happens often with newsletters. Challenge/Response Filters “Open sesame!” Challenge/Response filters are characterised by their ability to automatically send a response to a previously unknown sender asking them to take some further action before their message will be delivered. This is often referred to as a "Turing Test" - named after a test devised by British mathematician Alan Turing to determine if machines could “think”. Recent years have seen the appearance of some internet services which automatically perform this Challenge/Response function for the user and require the sender of an e-mail to visit their web site to facilitate the receipt of their message. Critics of this system claim it to be too drastic a measure and that it sends a message that "my time is more important than yours" to the people trying to communicate with you. For some low traffic e-mail users though, this system alone may be a perfectly acceptable method of completely eliminating spam from their inbox - one step above the "Whitelist" system outlined above. Community Filters “A united front” These types of filters work on the principal of "communal knowledge" of spam. When a user receives a spam message, they simply mark it as such in their filter. This information is sent to a central server where a “fingerprint” of the message is stored. After enough people have “voted” this message to be spam, then it is stopped from reaching all the other people in the community. This type of filtering can prove to be quite effective, although it stands to reason that it can never be 100% effective as a few people have to receive the spam for it to be “flagged” in the first place. Just like its similar cousin the Internet black list (RBL), this system also can suffer from “false positives”, or messages incorrectly identified as spam. Hopefully you are now armed with a little more information to be able to make an informed decision on the best spam filter for you. For further information, consider reading the reviews and articles found at http://www.whichspamfilter.com
HTTP = HTML link (for blogs, profiles,phorums):
Related Articles:Online Ideas And Opportunities For Businesses Wholesale Name Brand Clothing Versus Non Branded Clothing Possessing Gold: A Lesson in Business Identity
|