Identifying TV Channels &amp; On-Demand Videos using Ambient Light Sensors

Schwittmann, Lorenz; Boelmann, Christopher; Matkovic, Viktor; Wander, Matthaus; Weis, Torben

doi:10.1016/j.pmcj.2016.08.018

Cited by 8 publications

(4 citation statements)

References 8 publications

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“…Video Side-Channel [81], [82] Software-based solutions may help mitigate several video-based side-channel attacks [83]- [87]. Sensory Side-Channel Attacks [88]- [96] Solutions to sensory attacks include dedicated machine-learning frameworks [18], [97], [98]. Battery Exhaustion Battery Exhaustion Attacks [99]- [102] IDS frameworks such as MVP-IDS and B-SIPS [101], [103].…”

Section: E-iot Devices Layer: Attacks and Vulnerabilitiesmentioning

confidence: 99%

“…For instance, Xu et al created a video recognition attack where they were able to identify a video being watched on a television using the light emitted by the television through a window [82]. Similar works as presented by Schwittmann et al used ambient light sensors on smartphones and smartwatches to perform similar attacks [88], [89]. Alternatively, Light Ears, presented by Maiti et al, proposed a new attack vector designed to infer a user's private data and preferences from smart lighting media visualization features [90].…”

Section: E-iot Devices Layer: Attacks and Vulnerabilitiesmentioning

confidence: 99%

See 1 more Smart Citation

Survey on Enterprise Internet-of-Things Systems (E-IoT): A Security Perspective

Rondon¹,

Babun²,

Arış³

et al. 2021

Preprint

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As technology becomes more widely available, millions of users worldwide have installed some form of smart device in their homes or workplaces. These devices are often off-theshelf commodity systems, such as Google Home or Samsung SmartThings, that are installed by end-users looking to automate a small deployment. In contrast to these "plug-and-play" systems, purpose-built Enterprise Internet-of-Things (E-IoT) systems such as Crestron, Control4, RTI, Savant offer a smart solution for more sophisticated applications (e.g., complete lighting control, A/V management, security). In contrast to commodity systems, E-IoT systems are usually closed source, costly, require certified installers, and are overall more robust for their use cases. Due to this, E-IoT systems are often found in expensive smart homes, government and academic conference rooms, yachts, and smart private offices. However, while there has been plenty of research on the topic of commodity systems, no current study exists that provides a complete picture of E-IoT systems, their components, and relevant threats. As such, lack of knowledge of E-IoT system threats, coupled with the cost of E-IoT systems has led many to assume that E-IoT systems are secure. To address this research gap, raise awareness on E-IoT security, and motivate further research, this work emphasizes E-IoT system components, E-IoT vulnerabilities, solutions, and their security implications. In order to systematically analyze the security of E-IoT systems, we divide E-IoT systems into four layers: E-IoT Devices Layer, Communications Layer, Monitoring and Applications Layer, and Business Layer. We survey attacks and defense mechanisms, considering the E-IoT components at each layer and the associated threats. In addition, we present key observations in state-of-the-art E-IoT security and provide a list of open research problems that need further research.

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Section: E-iot Devices Layer: Attacks and Vulnerabilitiesmentioning

confidence: 99%

Section: E-iot Devices Layer: Attacks and Vulnerabilitiesmentioning

confidence: 99%

Survey on Enterprise Internet-of-Things Systems (E-IoT): A Security Perspective

Rondon¹,

Babun²,

Arış³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Similarly, Schwittmann et al [36] were able to infer a video played on a TV, by exploiting a smartphone's ambient light sensor. An extended work by Schwittmann et al [35] employed the ambient light sensor on a smartwatch to accomplish the same attack. Alternatively, Backes et al [12], [13] demonstrated how reflections from objects such as, users' eyes, teapots and walls can be exploited for spying on printed or digitally displayed data.…”

Section: Related Workmentioning

confidence: 99%

Light Ears: Information Leakage via Smart Lights

Maiti,

Jadliwala

2018

Preprint

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Modern Internet-enabled smart lights promise energy efficiency and many additional capabilities over traditional lamps. However, these connected lights create a new attack surface, which can be maliciously used to violate users' privacy and security. In this paper, we design and evaluate novel attacks that take advantage of light emitted by modern smart bulbs in order to infer users' private data and preferences. The first two attacks are designed to infer users' audio and video playback by a systematic observation and analysis of the multimediavisualization functionality of smart light bulbs. The third attack utilizes the infrared capabilities of such smart light bulbs to create a covert-channel, which can be used as a gateway to exfiltrate user's private data out of their secured home or office network. A comprehensive evaluation of these attacks in various real-life settings confirms their feasibility and affirms the need for new privacy protection mechanisms.

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“…With the advancements in optoelectronic information technology, microelectronics technology, and communication technology, ambient light sensors, as key devices for photoelectric detection technology, are widely used in consumer electronics, automotive electronics, and industrial control. More and more electronic products have entered and changed our daily lives, such as multimedia music players, smartphones, digital cameras, tablet PCs, and car navigation systems [ 1 , 2 , 3 , 4 , 5 ], all of which use ambient light sensors to convert light illumination into electrical signals to prolong battery life and backlight life, as well as improve power efficiency. These portable electronic devices have become an indispensable part of our lives and work, making our lives more convenient and our quality of life higher.…”

Section: Introductionmentioning

confidence: 99%

A Programmable Ambient Light Sensor with Dark Current Compensation and Wide Dynamic Range

Shi,

Yang,

Cao

et al. 2024

Sensors

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Ambient light sensors are becoming increasingly popular due to their effectiveness in extending the battery life of portable electronic devices. However, conventional ambient light sensors are large in area and small in dynamic range, and they do not take into account the effects caused due to a dark current. To address the above problems, a programmable ambient light sensor with dark current compensation and a wide dynamic range is proposed in this paper. The proposed ambient light sensor exhibits a low current power consumption of only 7.7 µA in dark environments, and it operates across a wide voltage range (2–5 V) and temperature range (−40–80 °C). It senses ambient light and provides an output current proportional to the ambient light intensity, with built-in dark current compensation to effectively suppress the effects of a dark current. It provides a wide dynamic range over the entire operating temperature range with three selectable output-current gain modes. The proposed ambient light sensor was designed and fabricated using a 0.18 µm standard CMOS process, and the effective area of the chip is 663 µm × 652 µm. The effectiveness of the circuit was verified through testing, making it highly suitable for portable electronic products and fluorescent fiber-optic temperature sensors.

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Identifying TV Channels & On-Demand Videos using Ambient Light Sensors

Cited by 8 publications

References 8 publications

Survey on Enterprise Internet-of-Things Systems (E-IoT): A Security Perspective

Survey on Enterprise Internet-of-Things Systems (E-IoT): A Security Perspective

Light Ears: Information Leakage via Smart Lights

A Programmable Ambient Light Sensor with Dark Current Compensation and Wide Dynamic Range

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