Malware detection and prevention in RFID systems


Autoria(s): Fernando, Harinda; Abawajy, Jemal
Contribuinte(s)

Bessis, Nik

Xhafa, Fatos

Varvarigou, Dora

Hill, Richard

Li, Maozhen

Data(s)

01/01/2013

Resumo

The threat that malware poses to RFID systems was identified only recently. Fortunately, all currently known RFID malware is based on SQLIA. Therefore, in this chapter we propose a dual pronged, tag based SQLIA detection and prevention method optimized for RFID systems. The first technique is a SQL query matching approach that uses simple string comparisons and provides strong security against a majority of the SQLIA types possible on RFID systems. To provide security against second order SQLIA, which is a major gap in the current literature, we also propose a tag data validation and sanitization technique. The preliminary evaluation of our query matching technique is very promising, showing 100% detection rates and 0% false positives for all attacks other than second order injection.

Identificador

http://hdl.handle.net/10536/DRO/DU:30055202

Idioma(s)

eng

Publicador

Springer

Relação

http://dro.deakin.edu.au/eserv/DU:30055202/evid-internetofthings-2013.pdf

http://dro.deakin.edu.au/eserv/DU:30055202/fernando-malwaredetection-2013.pdf

http://doi.org/10.1007/978-3-642-34952-2_6

Direitos

2012, Springer

Tipo

Book Chapter