Intelligent Email Analysis - Essay Example

Email intelligence analysis Number: Lecturer: Intelligent email analysis An email takes a very crucial role and position in any given working place or area of an organization or firm. There are now very many email messages which exist due to the central role played by email in a firm. It is for the management of activities, archiving of individual files as well as being used as online communication synchronization (Dondio & Barret 2007). Various email users do not follow the codes of conduct governing them as users something that leads to hacking of other persons passwords to be used as a get through to the email accounts and perform dirty acts like sabotage and many others due to the differences they have with each other (Granot & Sosic 2005). Several articles have been found in the media which explain the problem of mail overloading or junk messages. The effectiveness of an email message to reach anyone at any given period from its central position in any modern firm has led to great volumes of messages received by one person (Li & Fu 2002). Since email is considered as a very crucial technique for communication, there are email logs which useful sources of research in analysis including link and textual analysis and social networking (Artz & Gil 2007). Due to the lack of enough and real life benchmarking, the field researches are made on synthesized facts and figures. The dataset is the same as the facts and figures collected for the detection of fraud and to counter the terrorists. This makes it an effective and efficient tool or technique used for stopping of terrorism and fraud detection (Li & Fu 2002). For one to start the analysis work or task, he or she has to consider the first high level requirements statements for any email function. Pick or select an email for commercial products to give communication and facts and figures exchange. The effects shall be minimized what will lead to an almost accurate maintenance being available and the time allowed for retrieval is reduced to two days for an attack which was very serious. The messages from email will be useful and accessible to some specified staff members that are ranging from the sophisticated to the naïve members (Li & Fu 2002). The first step is to critically analyze the services which are very helpful to the firm or individual. A selection of email products is made to provide information, communication and exchange of the facts and figures One of the requirement analysis tools for investigation is the dataset since it has a lot of integrity issues. It must be integrated with the database so as to catalyze the statistical analysis of the facts and figures. When some one is sent a message, the best indicator of an action is the receiver’s relationship with the message and the sender. The reply predictor employs the relational characteristics which depend on the profile of the user, which is generated from the training facts and figures for every user. Every users profile contains a total number of sent and received messages to every user including the address book. The usability requirement provides that the chosen product is easy to use and that its security mechanism is accessible to the user as much as possible. The operational need where there are system administrative schedules that give the capability or possibility to manage a distributed user community by simply moving the users among servers and duplicating user profile processed facts and figures across all the servers in the network. In order to separate the spear phishing mails used in sophisticated and major targeted attacks, the email malware protection system is used to analyze the attachments using a signature, an engine that runs virtually which can safely and accurately find zero day attacks. This extends beyond signature and systems based on reputation through the disattaching every attachment against a cross matrix of operating systems and applications consisting various web browsers and plug ins such as the adobe readers and flash players. The administrator is supposed to separate the emails from the malicious character contents for deletion or rather farther analysis. The problems of email calls for the processing of the text, text analysis, link analysis, extraction of entities and other various methods. The basis for email analysis seems to be easy on the surface but very sophisticated for the naïve users. In order to analyze the email, one has to copy the email to a storage device which is robust in terms of speed, instruct the email analysis program to index the very email, then key word search or browser outputs after which one is required to make notes, write out the email and read every single file of interest. This is done repetitively for the purposes of billing for the time. This is the best part of analyzing the email (Sullivan & Liu 2011). Email is an important tool used by people all over the world to communicate. It can be very shameful to find an organization which does not use email and further more one that uses email the wrong way. Various firms rely on emails for communication. Emails from every single inbox of a user in any company can be analyzed. The initial thing to perform is to find or identify the sources of the email and the way in which the email servers and clients are used in a firm. Other than sending of messages via mail, the email servers and clients have extended their operation into full databases, file repositories, contact managers, time managers, calendars and various other applications. Firms should use the powerful database enabled email and messaging servers in order to manage attack cases, monitor the clients and share facts and figures (Artz & Gil 2007). The GDF is able to help in appropriately asking for and analyzing email and the firm’s tools. The analysis process is more than just checking at the email messages, but the analyzer must beware of the advanced characteristics and analyzing possibilities for every single type of email system (Sullivan & Liu 2011). It is always able or possible to retrieve email that was developed or got by web based email systems and from free web based email services like the hotmail, gmail and yahoo mail. These kinds of mail systems make use of a browser to link with the email servers (Li & Fu 2002). The browsers act as a database or cache which helps to store the information to the disk drive used in the computer to recover or create the email hence saving the copies or replicate to the disk. An html base email can be retrieved from the drive and the path identified to the source. If properly done and managed, the intelligent analysis of email produces files and documents which can be easily identified by date, recipients, subject, sender and give a great understandable and simple to follow map of activities and entities (Godbole 2007). Intelligent analysis ensures high standards and uses specialized tools to interface entities, dates, times and activities making sure that the firms email clients and their other clients in the network get the highest level of efficiency and quality work product when they make the choices to conduct their intelligent email analysis and or email retrieval activities or events (Godbole 2007). The email can be analyzed by the red highlighted line which includes the return path line where the header or the preprocessor directive shows that if one replies to a certain specific email message, the reply will be sent to some email account. Another line used to analyze is the received tags which includes the web blogs which are read from the top to the bottom (Athappilly 2000). The header identifies the origin of the email by use of the internet protocols such as from 206.75 to 217.254. These are the names or internet protocol of the initial mail server which got involved into transporting the message. The next received tag also says that the message was received from some email like root@localhost, by mailv.fx.ro (Allen 2003). Email analysis is an ultimate goal for a complete system forensics. It involves not only recovery of deleted facts and figures like the files and graphics and also the documents. It also entails the searching of the unallocated memory on the hard drive and places where unidentified evidence always resides. Email analysis allows the processing the hidden documents, those which are not able to be traced, accessed or viewed to the user, documents which consist of past usage processed facts and figures. This is the process of rebuilding and analyzing the facts and figures codes for every document and determining the time each was generated, last upgraded, last viewed and when it was deleted (Artz & Gil 2007). An email analysis reveals the amount of internet used, recover facts and figures and maintain a full analysis even after the system is formatted. Email intelligent analysis provides services such as the acquisition and recovery of data, the collection of evidences and the examination of the results in a written report (Athappilly 2000). Datasets are used to improve the email tools and help in explaining how the email is used. Some datasets are public while others are not simply because of security and privacy purposes or concerns (Artz & Gil 2007). References Allen, J 2003, The ultimate guide to system security, Madison-Wesley, Boston. Artz, D & Gil, Y 2007, A survey of trust in computer science and the Semantic Web, Journal of Web Semantics, vol 5, pp. 58-71. Athappilly, K 2000, A dynamic web-based knoweldge system for prototype development for extended enterprise, 3rd International Conference on the Practical Applications of Knowledge Management, PAKEM, Manchester. Castells, M 2003, The galaxy of the internet: Reflections on the internet, business, and ERP system, Oxford University Press, London. Dondio, P & Barret, S 2007, Computational trust in Web Content quality, Informatica. Godbole, R 2007, Web technologies , Tata McGraw-Hill Education, New Jersey. Granot, D & Sosic, G 2005, Formation of alliances in Internet-based supply exchange, Management Science, vol 51, no. 1, pp. 92-105. Huntington, D 2000, Web-based expert systems are on the way: Java-based web delivery, PC AI Intelligent Solutions for Desktop Computers, vol 14, no. 6, pp. 34-36. Li, D & Fu, ZY 2002, Duan Fish-Expert: A web-based expert system for fish disease diagnosis, Expert Systems With Applications, vol 23, no. 3, pp. 311-320. Sullivan, B & Liu, V 2011, Web application security, a beginners guide, McGraw-Hill Prof /Med Tech, New York. Read More