Tracking Private Browsing Sessions using CPU-based Covert Channels

Matyunin, Nikolay; Anagnostopoulos, Nikolaos Athanasios; Boukoros, Spyros; Heinrich, Markus; Schaller, André; Kolinichenko, Maksim; Katzenbeisser, Stefan

doi:10.1145/3212480.3212489

Cited by 6 publications

(3 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In particular, high CPU workload on a device typically requires more power, which results in a higher magnetic eld produced by the powersupplying wires. Matyunin et al [34] showed that this e ect is observable on a smartphone: Very high CPU activity on a Nexus 5X smartphone (close to 100% of the CPU load) led to a noticeable peak in magnetometer measurements.…”

Section: Reaction Of Magnetometers To Cpu Activitymentioning

confidence: 99%

“…Researchers used magnetometers to receive covert signals from a nearby computer encoded into hard drive activity [17], CPU activity [27], and combined I/O activity [35]. Recently, Matyunin et al [34] proposed a magnetometer-based intra-device covert channel on smartphones. e authors demonstrated that the magnetometer can be a ected by the peak CPU activity, emi ed by an active a acker from a webpage.…”

Section: Exploiting the Reaction Of Magnetometersmentioning

confidence: 99%

“…In this paper, we propose an alternative source of side-channel leakage for website and application ngerprinting on mobile devices, based on the reaction of magnetometer sensors to CPU activity. It has recently been shown that peak CPU activity on a smartphone can cause a noticeable disturbance in magnetic sensor measurements [34]. Authors utilized this reaction to establish a covert channel, by encoding a payload into pa erns of very high and idle CPU activity and analyzing the produced sensor disturbance.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

MagneticSpy: Exploiting Magnetometer in Mobile Devices for Website and Application Fingerprinting

Matyunin,

Wang,

Arul

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

Recent studies have shown that aggregate CPU usage and power consumption traces on smartphones can leak information about applications running on the system or websites visited. In response, access to such data has been blocked for mobile applications starting from Android 7. In this work, we explore a new source of sidechannel leakage for this class of a acks. Our method is based on the fact that electromagnetic activity caused by mobile processors leads to noticeable disturbances in magnetic sensor measurements on mobile devices, with the amplitude being proportional to the CPU workload. erefore, recorded sensor data can be analyzed to reveal information about ongoing activities. e a ack works on a number of devices: We evaluated 59 models of modern smartphones and tablets and observed the reaction of the magnetometer to CPU activity on 39 of them. On selected devices we were able to successfully identify which application has been opened (with up to 90% accuracy) or which web page has been loaded (up to 91% accuracy). We believe that the presented side channel poses a significant risk to end users' privacy, as the sensor data can be recorded from native apps and even from web pages without user permissions. Finally, we discuss possible countermeasures to prevent the presented information leakage.

show abstract

Section: Reaction Of Magnetometers To Cpu Activitymentioning

confidence: 99%