Journal of Intelligent Information Systems

, Volume 36, Issue 1, pp 1–26 | Cite as

Collaborative RFID intrusion detection with an artificial immune system



The current RFID systems are fragile to external attacks, due to the limitations of encryption authentication and physical protection methods used in implementation of RFID security systems. In this paper, we propose a collaborative RFID intrusion detection method that is based on an artificial immune system (AIS). The new method can enhance the security of RFID systems without need to amend the existing technical standards of RFID. Mimicking the immune cell collaboration in biological immune systems, RFID operations are defined as self and nonself antigens, representing legal and illegal RFID operations, respectively. Data models are defined for antigens’ epitopes. Known RFID attacks are defined as danger signals represented by nonself antigens. We propose a method to collect RFID data for antigens and danger signals. With the antigen and danger signal data available, we use a negative selection algorithm to generate adaptive detectors for self antigens as RFID legal operations. We use an immune based clustering algorithm aiNet to generate collaborative detectors for danger signals of RFID intrusions. Simulation results have shown that the new RFID intrusion detection method has effectively reduced the false detection rate. The detection rate on known types of attacks was 98% and the detection rate on unknown type of attacks was 93%.


Radio Frequency IDentification (RFID) Collaborative intrusion detection Negative selection Artificial immune system (AIS) Immune based clustering 



The project was supported by the National Natural Science Foundation of China under Grants 60973132, and Guangdong Natural Science Foundation under grants 8451064101000630.


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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.College of Automation Science and EngineeringSouth China University of TechnologyGuangzhouChina
  2. 2.School of Computer ScienceGuangdong Polytechnic Normal UniversityGuangzhouChina

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