Neural-Network-Based Fuzzy Logic Control and Decision System
IEEE Transactions on Computers - Special issue on artificial neural networks
TCP/IP illustrated (vol. 1): the protocols
TCP/IP illustrated (vol. 1): the protocols
Network management (2nd ed.): a practical perspective
Network management (2nd ed.): a practical perspective
Fuzzy logic: intelligence, control, and information
Fuzzy logic: intelligence, control, and information
An efficient e-mail filtering using time priority measurement
Information Sciences—Informatics and Computer Science: An International Journal
Detecting Junk Mails by Implementing Statistical Theory
AINA '06 Proceedings of the 20th International Conference on Advanced Information Networking and Applications - Volume 02
An new E-mail filtering technique using time priority measurement
ISCC '04 Proceedings of the Ninth International Symposium on Computers and Communications 2004 Volume 2 (ISCC"04) - Volume 02
A genetic fuzzy agent using ontology model for meeting scheduling system
Information Sciences: an International Journal
A parallel fuzzy inference model with distributed prediction schemefor reinforcement learning
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Genetic-based fuzzy image filter and its application to image processing
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Building agents for rule-based intrusion detection system
Computer Communications
A two-dimensional circumplex approach to the development of a hacker taxonomy
Digital Investigation: The International Journal of Digital Forensics & Incident Response
E-mail bombs and countermeasures: cyber attacks on availability and brand integrity
IEEE Network: The Magazine of Global Internetworking
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It is hard to block e-mail bombs because they are usually sent by normal SMTP (Simple Mail Transfer Protocol) applications with fake mail sender addresses and IP addresses. Fortunately, original network packets contain real IP address information anyway. Collecting and analyzing these packet contents can help an administrator to realize where the e-mail bombs are coming from and block them. This article presents a simple method that uses a bandwidth manager device to collect and analyze packets to get e-mail bombs information as well as to block e-mail bomb source IP addresses in routers. In practical application experiences at the computer center in a university, this method blocked e-mail bombs simply and effectively. Furthermore, a fuzzy inference system was also designed to help identify e-mail bombs. Its fuzzy membership functions could be adapted using the fuzzy neural network learning method. In brief, the proposed method affords an automatic and adaptable alarm to find e-mail bombs.