TY - GEN
T1 - Securing PKES
T2 - 5th International Conference on Software Security and Assurance, ICSSA 2019
AU - Rizvi, Syed
AU - Imler, Jarrett
AU - Ritchey, Luke
AU - Tokar, Michael
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - Passive Keyless Entry and Start System (PKES) is a convenient feature found in newer cars that allows the user to enter their car without having to press a button on a key fob. Users can simply walk up to their vehicle and once they are in close enough proximity, it unlocks and the user is granted access. However, the convenience of PKES comes at a price; vulnerability to relay attacks and amplified relay attacks. Our proposed method, PKES Forcefield, would protect the user from these attacks without sacrificing any convenience. PKES Forcefield utilizes coordinate tracing and multifactor authentication to secure the user. To add more security to PKES Forcefield, we propose AI integration to construct a profile for each user of the vehicle. This profile will store data on the habits of the user (location, walking speed, time, etc.). Once each user has a profile built from their input data, our system will be able to detect any behaviors that differ from the user's profile (anomalies) and then proper security measures will be taken depending on if the anomaly is considered to be a Low Risk Anomaly or a High Risk Anomaly.
AB - Passive Keyless Entry and Start System (PKES) is a convenient feature found in newer cars that allows the user to enter their car without having to press a button on a key fob. Users can simply walk up to their vehicle and once they are in close enough proximity, it unlocks and the user is granted access. However, the convenience of PKES comes at a price; vulnerability to relay attacks and amplified relay attacks. Our proposed method, PKES Forcefield, would protect the user from these attacks without sacrificing any convenience. PKES Forcefield utilizes coordinate tracing and multifactor authentication to secure the user. To add more security to PKES Forcefield, we propose AI integration to construct a profile for each user of the vehicle. This profile will store data on the habits of the user (location, walking speed, time, etc.). Once each user has a profile built from their input data, our system will be able to detect any behaviors that differ from the user's profile (anomalies) and then proper security measures will be taken depending on if the anomaly is considered to be a Low Risk Anomaly or a High Risk Anomaly.
UR - http://www.scopus.com/inward/record.url?scp=85101132520&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85101132520&partnerID=8YFLogxK
U2 - 10.1109/ICSSA48308.2019.00008
DO - 10.1109/ICSSA48308.2019.00008
M3 - Conference contribution
AN - SCOPUS:85101132520
T3 - Proceedings - 2019 International Conference on Software Security and Assurance, ICSSA 2019
SP - 10
EP - 15
BT - Proceedings - 2019 International Conference on Software Security and Assurance, ICSSA 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 25 July 2019 through 26 July 2019
ER -