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USENIX Security '21 - A Stealthy Location Identification Attack Exploiting Carrier Aggregation
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A Stealthy Location Identification Attack Exploiting Carrier Aggregation in Cellular Networks
Nitya Lakshmanan and Nishant Budhdev, National University of Singapore; Min Suk Kang, KAIST; Mun Choon Chan and Jun Han, National University of Singapore
We present the SLIC that achieves fine-grained location tracking (e.g., finding indoor walking paths) of targeted cellular user devices in a passive manner. The attack exploits a new side channel in modern cellular systems through a universally available feature called carrier aggregation (CA). CA enables higher cellular data rates by allowing multiple base stations on different carrier frequencies to concurrently transmit to a single user. We discover that a passive adversary can learn the side channel — namely, the number of actively transmitting base stations for any user of interest in the same macrocell. We then show that a time series of this side channel can constitute a highly unique fingerprint of a walking path, which can be used to identify the path taken by a target cellular user. We first demonstrate the collection of the new side channel and a small-scale path identification attack in an existing LTE-A network with up to three CA capability (i.e., three base stations can be coordinated for concurrent transmission), showing the feasibility of SLIC in the current cellular networks. We then emulate a near-future 5G network environment with up to nine CA capability in various multi-story buildings in our institution. SLIC shows up to 98.4% of path-identification accuracy among 100 different walking paths in a large office building. Through testing in various building structures, we confirm that the attack is effective in typical office building environments; e.g., corridors, open spaces. We present complete and partial countermeasures and discuss some practical cell deployment suggestions for 5G networks.
Nitya Lakshmanan and Nishant Budhdev, National University of Singapore; Min Suk Kang, KAIST; Mun Choon Chan and Jun Han, National University of Singapore
We present the SLIC that achieves fine-grained location tracking (e.g., finding indoor walking paths) of targeted cellular user devices in a passive manner. The attack exploits a new side channel in modern cellular systems through a universally available feature called carrier aggregation (CA). CA enables higher cellular data rates by allowing multiple base stations on different carrier frequencies to concurrently transmit to a single user. We discover that a passive adversary can learn the side channel — namely, the number of actively transmitting base stations for any user of interest in the same macrocell. We then show that a time series of this side channel can constitute a highly unique fingerprint of a walking path, which can be used to identify the path taken by a target cellular user. We first demonstrate the collection of the new side channel and a small-scale path identification attack in an existing LTE-A network with up to three CA capability (i.e., three base stations can be coordinated for concurrent transmission), showing the feasibility of SLIC in the current cellular networks. We then emulate a near-future 5G network environment with up to nine CA capability in various multi-story buildings in our institution. SLIC shows up to 98.4% of path-identification accuracy among 100 different walking paths in a large office building. Through testing in various building structures, we confirm that the attack is effective in typical office building environments; e.g., corridors, open spaces. We present complete and partial countermeasures and discuss some practical cell deployment suggestions for 5G networks.