In 2003, et al. Jerome R. Bellegarda, showed the conventional mail filtering techniques based on unsupervised learning where the classification is done on the basis keyword matching. But if spammers change the tricks of spam mails framing than the old classifiers will than not able to give the accurate results. That is the worst part of the unsupervised learning. On the other hand, in the same paper, machine learning techniques based on supervised learning is introduced where the classifiers are regularly fed with the changing patterns of spam mails with different data sets[15]. In 2006, et al. Giorgio Fumera, focused in his work in [20] on text categorization techniques based on the machine learning and pattern recognition approaches for e-mail semantic content analysis instead of manually coded rules derived from the analysis of spam e-mails. This paper lighted the concept of content based spam filtering and anti-spam filtering which exploits the text information embedded into images sent as attachments. In 2009, et al. Ronald Bhuleskar tricked a new approach of HSF Model. It is a combinational filter model of various spam filteration techniques. Author used unsupervised and supervised techniques simultaneously in its model. It filters an incoming mail through various filters separately but all the filters should be arranged in parallel. Parallel filters used in this paper were black and white listing, content based filtering and Forging filtering. In forging, IP address of the sender is checked and then at server level validating the domain name of Email sending server with its IP address or Reverse DNS Lookup[18]. In 2010, et al. Morteza Zi Hayat showed in [19], again the supervised learning is used and promoted. In this re... ... middle of paper ... ...s and Networks, IEEE Computer Society, 2009, pp. 302-307. [19] Morteza Zi Hayat, Javad Basiri, Leila Seyedhossein, Azadeh Shakery, “Content-Based concept drift detection for email spam filtering”, 5th International Symposium on Telecommunications (IST'2010), 2010, pp. 531-536. [20] Giorgio Fumera, Ignazio Pillai, Fabio Roli, “Spam filtering based on the analysis of text information embedded into images”, in Journal of Machine Learning Research, Vol. 7, Dec.-2006,pp. 2699-2720. [21] Zhenyu Zhong, Kang Li, “Speed up statistical spam filter by approximation”, ieee transactions on computers, vol. 60, no. 1, january 2011, pp. 120-133. [22] Basheer Al-Duwairi, Ismail Khater , Omar Al-Jarrah, “Detecting image spam using image texture features”, International Journal for Information Security Research (IJISR), Volume 2, Issues 3/4, September/December 2012, pp. 344-353.
Email security services will include blocking ransomware and emerging threats with the highest effectiveness and accuracy, stopping new and sophisticated threats such as ransomware, spear phishing, and business email compromise. Spear phishing will be prevented by having a comprehensive defense that includes multiple layers of protection, strong isolation , deep visibility and dynamic security awareness. Attacks will be contained and responses will be orchestrated across endpoint security and web gateways by remediating attacks and blacklisting threats. Dynamically classify impostor email and other threats that don't involve malware. Sender-recipient relationship, domain reputation, email headers, envelope attributes and email content will be analyzed. Custom rules will be integrated allowing group and user level controls to meet the needs of the client. Quarantines will enable the customer to separate email
Computer hackers in today's world are becoming more intelligent. They are realizing that people are constantly developing more hack-proof systems. This presents the hackers with a bigger challenge and a bigger thrill. The government is realizing this and is working on making harsher laws to, hopefully, scare the potential hackers. With the increase in hacking and hacker intelligence, governmental regulation of cyberspace hasn't abolished the fact that it's nearly impossible to bring a hacker to justice.
There is a debate between the benefits and potential informational privacy issues in web-data mining. There are large amount of valuable data on the web, and those data can be retrieved easily by using search engine. When web-data mining techniques are applied on these data, we can get a large number of benefits. Web-data mining techniques are appealing to business companies for several reasons [1]. For example, if a company wants to expand its bu...
A major flaw of the proposed filter is the futility to prevent crime. The internet is a massive network of computers and web pages are just one use of thi...
I want to be able to zap the sender with so much spam that their inbox
Any watermarking technique [3] has to be evaluated to judge its performance .Three factors, as give...
Steganography is the art and science of communicating in a way which hides the existence of the communication. In contrast to Cryptography, where the enemy is allowed to detect, intercept, modify messages without being able to violate certain security premises guaranteed by a cryptosystem, the goal of steganographic method is that no one will be able to know whether anything is hidden in the image or not. For hiding secret message in images, there exists a large variety of steganographic techniques some are more complex than others and all of them have respective strong and weak points. Different applications have different requirements of the steganography technique used. Based on the PSNR value of each images, the stego image has a higher PSNR value. The proposed algorithm is based on merge between the idea from the random pixel manipulation methods and Least Significant (LSB) matching of Steganography embedding and extracting method.
Delete Spam mails immediately and report such mails from unknown parties. DO NOT open spam e-mail, click on links in the e-mail, or open attachments. These often contain malware that will give subjects access to your computer system. 8. Forward vs. Reply: Do not use the “Reply” option to respond to any business e-mails.
In the different application areas like spell checking, intrusion detection system, bioinformatics applications, plagiarism detection, pattern identifying, document searching, text mining, video retrieval, data cleaning and so on, both the string-matching algorithms are applied. Different functions, concepts, and approaches are applied to both types of the algorithms to achieve optimum and efficient results. String matching is very important for this generation because most of the information has become online and millions of people are aware of internet so searching any information in the search engines is very convenient now with the help of the string- matching
My thesis contain the identification of accurately classifying the sentiment in text from micro blogs. This addresses the problem by retrieving opinions, performing processing on the data and analyzing the data using machine learning techniques to classify them by sentiment as positive, negative or neutral. I proposed sentimental natural language processing method for processing the text and use various machine learning algorithms and feature selection methods to determine the best approach. The approaches towards sentiment analysis are machine learning based methods, lexicon based methods and linguistic analysis. I proposed sentimental natural language processing Model for processing text to remove irrelevant features that do not affect its orientation. Sentimental natural language processing model carries opinions in natural language process as well as unstructured reviews with pointers, punctuations, emotions, repeated words, symbols, WH questions, URL’s are preprocessed to extract relevant features while sanitizing inputs. Sentimental natural language processing measures the importance of feature...
Nazario, Jose “Defense and Detection Strategies against Internet Worms”, Artech House Computer Security Library, 2004
Nowadays when more and more sensitive information is stored on computers and transmitted over the Internet, we need to ensure information security and safety. Image is also an important part of our information .Therefore it’s very important to protect our image from unauthorized access.Security of multimedia information is used to protect the multimedia content...
Electronic Mail, a means of communication that is growing at a very rapid rate. In this paper, I will write about introduction of e-mail, the advantage and disadvantage of e-mail, mailing lists, sending an e-mail message, sending attachments, e-mail improvement, and security features. Introduction of Electronic Mail Electronic mail (E-mail) has become popular and easy way of communication in this decade. E-mail is a method of sending and receiving document or message from one person to another. E-mail is not only replacement for postal mail and telephones, and also it is a new medium. E-mail send plain text, images, audio, spreadsheets, computer programs can attach to an e-mail message. Using the e-mail, you must have a computer on a network. The computer must require a modem and phone line. Sending and receiving e-mail needs an e-mail program. Every e-mail user requires an e-mail address. This e-mail address is similar to a postal address. E-mail address is written as username@domain, for instance, PCLEE@juno.com. The username is used for sending and receiving e-mail.
Humans can expand their knowledge to adapt the changing environment. To do that they must “learn”. Learning can be simply defined as the acquisition of knowledge or skills through study, experience, or being taught. Although learning is an easy task for most of the people, to acquire new knowledge or skills from data is too hard and complicated for machines. Moreover, the intelligence level of a machine is directly relevant to its learning capability. The study of machine learning tries to deal with this complicated task. In other words, machine learning is the branch of artificial intelligence that tries to find an answer to this question: how to make computer learn?