TY - GEN
T1 - Demystifying the Presence of Cellular Network Attacks and Misbehaviors
AU - Echeverria, Mitziu
AU - Chowdhury, Omar
N1 - Publisher Copyright:
© 2022 Copyright held by the owner/author(s).
PY - 2022/10/25
Y1 - 2022/10/25
N2 - Cellular networks nowadays are not only responsible for powering up worldwide communication systems, but also enable highly sensitive applications, such as the earthquake and tsunami warning system (ETWS), telemedicine, and autonomous vehicle communication. Due to its importance, one would expect this technology to be highly robust, secure, and reliable. However, even in the newest generations (i.e., 5G), this is not the case. Due to either implementation slipups [6, 11], errors in the standard [3, 5], or misconfigurations [2]. These errors enable numerous destructive attacks, enabling malicious parties to track a victim’s location, disrupt cellular services, and eavesdrop on calls, among other implications. To make matters worse, developing defenses against these types of attacks is a non-trivial task as it requires network operator cooperation. Most importantly it requires a significant amount of resources to be allocated by network operators and device manufacturers [2]. To justify allocating resources to fix these issues, network operators need to quantify the misbehaviors and attacks being carried out in the wild. Unfortunately, there is no mechanism in place to perform this type of measurement. Furthermore, there is no empirical evidence of cellular network attacks occurring in the wild, which digresses the community from focusing on developing defenses. Instead, the defense community has to rely vastly on anecdotal evidence to motivate their work, such as the presence of rogue base stations near government facilities [8]. To provide the required empirical evidence and quantify the misbehaviors and attacks, we present HoneyLTE. HoneyLTE is the first tool that efficiently measures cellular network attacks and misbehaviors in the wild.
AB - Cellular networks nowadays are not only responsible for powering up worldwide communication systems, but also enable highly sensitive applications, such as the earthquake and tsunami warning system (ETWS), telemedicine, and autonomous vehicle communication. Due to its importance, one would expect this technology to be highly robust, secure, and reliable. However, even in the newest generations (i.e., 5G), this is not the case. Due to either implementation slipups [6, 11], errors in the standard [3, 5], or misconfigurations [2]. These errors enable numerous destructive attacks, enabling malicious parties to track a victim’s location, disrupt cellular services, and eavesdrop on calls, among other implications. To make matters worse, developing defenses against these types of attacks is a non-trivial task as it requires network operator cooperation. Most importantly it requires a significant amount of resources to be allocated by network operators and device manufacturers [2]. To justify allocating resources to fix these issues, network operators need to quantify the misbehaviors and attacks being carried out in the wild. Unfortunately, there is no mechanism in place to perform this type of measurement. Furthermore, there is no empirical evidence of cellular network attacks occurring in the wild, which digresses the community from focusing on developing defenses. Instead, the defense community has to rely vastly on anecdotal evidence to motivate their work, such as the presence of rogue base stations near government facilities [8]. To provide the required empirical evidence and quantify the misbehaviors and attacks, we present HoneyLTE. HoneyLTE is the first tool that efficiently measures cellular network attacks and misbehaviors in the wild.
UR - https://www.scopus.com/pages/publications/85141402505
U2 - 10.1145/3517745.3563017
DO - 10.1145/3517745.3563017
M3 - Conference contribution
AN - SCOPUS:85141402505
T3 - Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC
SP - 742
EP - 743
BT - IMC 2022 - Proceedings of the 2022 ACM Internet Measurement Conference
PB - Association for Computing Machinery
T2 - 22nd ACM Internet Measurement Conference, IMC 2022
Y2 - 25 October 2022 through 27 October 2022
ER -