Name
Title | ||
|---|---|---|
Security Vs. Privacy: How Integrity Attacks Can Be Masked By The Noise Of Differential Privacy |
Abstract | ||
|---|---|---|
Privacy concerns have increased in the last years due to the unprecedented scale of data collected regarding human activity. Differential privacy has emerged in the last decade as an important mechanism to ensure privacy by adding random noise with a specific distribution to the information being collected (e.g., adding noise to smart meters, and sensor readings). Differential privacy has been mainly used in private databases, but lately it has also been extended to consider applications like estimation, consensus algorithms, and control of dynamical systems.In addition to privacy, another threat to modern control systems is that of integrity attacks, where an attacker compromises a sensor or control signal and then attempts to drive a dynamical system to an undesired state.In this work, we study how differential privacy affects attack detection mechanisms that prevent integrity attacks. We analyze how an attacker can take advantage of the added noise in differential privacy to design stealthy attacks that maximize the physical impact in the system. Because of the added differential privacy noise, detection mechanisms have to increase their tolerance to anomalies in order to keep a low number of false alarms, but on the other hand attackers have more options for injecting false information that will remain undetected. |
Year | Venue | Field |
|---|---|---|
2017 | 2017 AMERICAN CONTROL CONFERENCE (ACC) | Consensus algorithm,Internet privacy,Differential privacy,Computer science,Computer security,Random noise,Dynamical systems theory,Information privacy,Privacy software |
DocType | ISSN | Citations |
Conference | 0743-1619 | 1 |
PageRank | References | Authors |
0.36 | 6 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jairo Alonso Giraldo | 1 | 134 | 10.27 |
| Alvaro A. Cárdenas | 2 | 1390 | 101.51 |
| Murat Kantarcioglu | 3 | 2470 | 168.03 |