Although it seems like the spread of spam-unwanted junk e-mails sent to millions of people each day – is recent problem, spam has been around as long as the Internet has. In fact, the first documented case of spam occurred in 1978, when a computer company sent out 400 e-mails via the Arpanet, the precursor to the modern Internet. Now, spam e-mails account for more than two-thirds of all the e-mails sent over the Internet, and for some unlucky uses, spam makes up 80 percent of the messages they receive. And despite technological innovations such as spam filters and event new legislation designed to combat spam, the problem will not go away easily.
The reason spammers – the people who and businesses that spread spam – are difficult to stop is that spam is so cost effective. It costs a spammer roughly one-hundredth of a send spam, which means that a spammer can still make a profit even with an extremely low response rate, as low as one sale per 100,000 e-mails sent. This low rate gives spammers a tremendous incentive to continue sending out millions and millions and millions of e-mils, even if the average person never purchases anything from them. With so much at stake, spammers have gone to great lengths to avoid or defeat spam blockers and filters.
Most spam filters rely on a fairly primitive “fingerprinting” system. In this system, a program analyzes several typical spam messages and identifies common features in them. Any arriving e-mails that match these features are deleted. But the fingerprinting defense proves quite easy for spammer to defeat. To confuse the program, a spammer simply has to include as series of random characters or number. The additions to the spam message change its “fingerprint” and thus allow the spam to escape detection. And when programmers modify the fingerprint software to look for random strings of letter, spammers respond by including nonrandom content, such as sports scores or stock prices, which again defeats the system.
A second possible solution takes advantage of a computer’s limited learning abilities. So called “smart filters” use complex algorithms, which allow them to recognize new versions of spam messages. These filters may be initially fooled by random characters or bogus content, but they soon learn to identify these features. Unfortunately, spammers have learned how to avoid these smart filters as well.
1. The following statements describe spam, except _____
a. It affects million of internet users
b. It totals more than 80% of e-mail
c. It is beneficial to the general public
d. It is an unwanted message for mass audience
e. It may be a good source of income for spammers
2. The best title for the above text is _____.
a. The Development of Spam Filters
b. The Success of the Development of Spam Filters
c. The Disadvantages of Using E-mails
d. How to Make Profit through Spamming
e. Spam: Problems and Solutions
Answer : E
3. Smart filters are superior to fingerprinting systems because smart filters _____.
a. Are eventually able to recognize new versions of spam
b. Have the ability to learn from their previous mistakes
c. Do not need to find common features to detect spam.
d. Are not fooled by random characters or content
e. Take advantages of computer’s limited learning abilities
Answer : A
4. The word ‘program’ in line 17 refers to _____.
a. A spam message
b. A character or a number
c. A type of spam filter
d. A common feature
e. A fingerprint
Answer : E
5. From the text we can conclude that spammers _____
a. Have always managed to get responses from internet users
b. Produce spam that can never be detected by spam blockers.
c. Have been able to sell cheap products to users
d. Make a big profit from the combat against spam blockers
e. Always send 100,000 e-mail a day to make profit.
Answer : B