.png){kind=icon}
Return
Robust Sensor Localization against Known Sensor Position Attacks
.png){kind=icon}
PRE
AI
DOI：10.1109/TMC.2018.2883578.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Many localization techniques for wireless sensor networks have been proposed to estimate sensor positions even when there is malicious location information which distorts the estimate. Some of those solutions efficiently estimate sensor positions using the Minimum Mean Square Estimation methods and the Degree-Of-Consistency (DOC). Although such solutions can filter out most of malicious information, if an attacker knows the position of the target sensor, the attacker can significantly alter its estimated position. In this paper, we introduce two attacks based on the knowledge of target sensor positions. The first attack, called Aligned-Beacon-Position (ABP) attack, exploits beacon nodes that are aligned in a line. The second attack, called inside-attack, disables the DOC filtering algorithm by placing malicious location references inside benign location references. To protect against those two known sensor position attacks, we introduce two defense schemes. First, we propose a novel beacon placement strategy to protect against ABP attacks. Second, we present a filtering technique that can filter out malicious location references introduced by inside-attacks. Finally, we propose a localization algorithm which has enhanced accuracy and efficiency compared with previous algorithms. We assess the impact of those attacks and the performance of our defense schemes by simulation and test-bed experiments.
Keywords:
Robot sensing systems
Global Positioning System
Mobile computing
Wireless sensor networks
Estimation
Receivers
Security
Secure localization
sensor localization
MMSE
known sensor position attacks
beacon deployment
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
9.2
Papers:
5.9K
Citations:
1.8W
Organization
Cited Papers
.png){kind=icon}
ShareSaveShareSave
AB initio study of the structures and vibrational frequencies of CH3SiF3, [CH3SiF4]− and [CH3SiF5]2−
PREAI
ShareSaveSensor position determination with flying anchors in three-dimensional wireless sensor networks
PREAI
ShareSave
View more