Abstract :
The transport of goods around the globe is a major commercial activity, vital to the world´s economies. Much of this is accomplished using ISO standard cargo containers, which can be readily on and off loaded from different platforms for travel by road, rail, air and sea. Criminals and terrorists may target such containers for their own purposes. The threats include using the containers to assist with smuggling (drugs, currency or arms), stowaways (illegal immigrants or terrorists) and terrorist attacks (weapons of mass destruction). At present, the checking of containers is limited, and hence they are vulnerable prime targets. In an effort to combat these threats and improve security, smart containers are being introduced. These contain a variety of sensors to detect, identify, log and communicate what happens to a container and its contents during its travels around the world. Reliable methods for detection of cargo container intrusions are difficult to find, as they tend to suffer from false alarms due to container movement and outside disturbances, or are adversely affected by the cargo within the container. One promising approach is to attach microphones to the container to detect the sounds that are generated by attempts to cut open the container. This paper describes some investigations made to characterise the waveforms generated by different types of attack using, for example, saws, drills, hammer/chisels, and gas cutting torches. The methods used to analyse the waveforms and some promising signal processing algorithms that could be used within the smart containers are described. Particular emphasis is placed on the dependency of microphone sensor position relative to the point of attack, and the variation of the detected waveforms with the phase of the attack.
