Anti-Spam technologies come and go, but spammers never cease to operate. Unsolicited e-mail continues to increase. “Short, Pointless or Annoying Message” (Stands4 LLC, 2013), commonly referred to as spam, has reached epidemic proportions of 86% of all emails received by workplace computer users in 2012 (Pingdom, 2013). Productivity is significantly reduced in the workplace by spam. Statistics report that 11% or more of employees receive about 50 spam messages each day. Employees will waste more than half an hour in lost productivity going through, identifying and deleting spam mail. Anti-spam technologies are being developed all the time. Whether these new tools to fight spam are effective is yet to be determined.
New Spam Techniques
New anti-spam techniques are always being developed. A most recent method to reduce spam comes from the scientists at Concordia University, Institute of Information Systems Engineering, Canada, who conducted a broad study of numerous spam filters in the process of developing a more efficient anti-spam scheme. Researcher Ola Amayri said “Our new method for spam filtering is able to adapt to the dynamic nature of spam emails and accurately handle spammers’ tricks by carefully identifying informative patterns, which are automatically extracted from both text and images content of spam emails” (Bennett, Coleman & Co. Ltd, 2012).
Another method allows for junk mail to be identified based on a single packet of data. Software developed at the Georgia Institute for Technology (GIT) can identify spam before it hits the mail server. This method, known as Spatio-temporal Network-level Automatic Reputation Engine, or SNARE for short, will assign a score to an incoming e-mail based on a variation of criteria that can be collected from one data packet. The researchers at GIT claim the automated system will ease the burden on the network and minimize the necessity for system administrator intervention while accomplishing the same accuracy, if not better, as traditional spam filters. “The SNARE system is capable of detecting spam 70 percent of the time, with a 0.3 percent false positive rate” (Kremen, 2009). The GIT researchers discovered that by plotting the global distance between the Internet Protocol (IP) address of the spam sender and email recipient, they could determine whether the message was junk mail. An IP address can be mapped to a geographic area. The GIT researchers found that spam tends to travel farther than legitimate email. Spammers also seem to stick close to each other and tend to have similar numerically close IP addresses.
The above methods, as developed and implemented, have shown success in reducing spam. The problem is that when spammers realize that their current methods are not successful, they develop new spam techniques to bypass anti-spam technologies. To develop new solutions to reduce spam is a daunting task, one that would take a great deal of time, study and funding to accomplish. The writer of this report has none of these luxuries to even suggest a solution to the epidemic of the never-ending spam issue. A resolution to the national deficit crisis might be an easier task!
“The reason so many spam messages that advertise drugs, cheap mortgage rates, or items for sale are sent is because sending spam is a lucrative business. It costs spammers next to nothing to send millions of spam e-mail messages (Ciampa, 2009, p. 48). Spam is a phenomenon that is an ever-evolving menace. Whenever a spammer finds that the methods employed are not producing profits, new ways to beat the system are devised. To successfully stop spam from troubling employees, it is necessary to find solutions that encompass several technologies.
Currently, there is no one anti-spam solution used that is effective in the battle against spam.