Home > JOURNALS > IJSSAN > Vol. 2 > Iss. 2 (2012)
International Journal of Smart Sensor and Adhoc Network
Article Title
RECONFIGURABLE SELF-ADDRESSABLE MEMORY-BASED FSM A SCALABLE INTRUSION DETECTION ENGINE
Abstract
One way to detect and thwart a network attack is to compare each incoming packet with predefined patterns, also Called an attack pattern database, and raise an alert upon detecting a match. This article presents a novel pattern-matching Engine that exploits a memory-based, programmable state machine to achieve deterministic processing rates that are Independent of packet and pattern characteristics. Our engine is a self addressable memory based finite state machine (sam- Fsm), whose current state coding exhibits all its possible next states. Moreover, it is fully reconfigurable in that new attack Patterns can be updated easily. A methodology was developed to program the memory and logic. Specifically, we merge “non-equivalent” states by introducing “super characters” on their inputs to further enhance memory efficiency without Adding labels. This is the most high speed self addressable memory based fsm.sam-fsm is one of the most storage-Efficient machines and reduces the memory requirement by 60 times. Experimental results are presented to demonstrate the Validity of sam-fsm.
Recommended Citation
SRILATHA, B. and KISHORE, KRISHNA
(2012)
"RECONFIGURABLE SELF-ADDRESSABLE MEMORY-BASED FSM A SCALABLE INTRUSION DETECTION ENGINE,"
International Journal of Smart Sensor and Adhoc Network: Vol. 2
:
Iss.
2
, Article 13.
Available at:
https://www.interscience.in/ijssan/vol2/iss2/13
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