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Mitigation of Periodic Jamming in a Spread Spectrum System by Adaptive Filter Selection
Any type of content formally published in an academic journal, usually following a peer-review process.
Jamming has long been a problem in wireless communication systems. Traditionally, defense techniques have looked to raise the cost of mounting an equally effective jamming attack. One technique to raise the cost of jamming is direct sequence spread spectrum (DSSS) which spreads data over a wider bandwidth and has built-in error correction. To work around this, attackers have developed intelligent jamming techniques to minimize the cost of mounting attacks on these systems. To lower the cost of attacking a DSSS system, an attacker can use periodic jamming which alternates between an attacking and sleeping state. Previously, a digital filter has been used to mitigate a periodic jamming attack at the center frequency of the attacker. In this work, we expand this previous attack model by allowing an attacker to jam at any frequency and even to move to different frequencies in the channel. To defend against the more general attack, we propose the use of an adaptive filter selection technique. This technique monitors packet delivery ratio (PDR) at the receiver and uses this information to infer whether it is being attacked. If the receivers PDR is low, it activates a filter from a pre-defined filter bank and tests if performance improves. This process continues by activating different filters from the filter bank until adequate PDR performance is achieved. We show that this approach can search through a small set of filters and recover over 90% of packets with a search time of less than 3 seconds on average for an attacker who randomly chooses its center frequency.