I Always Feel Like Somebody's Sensing Me! A Framework to Detect, Identify, and Localize Clandestine Wireless Sensors Article Swipe
Akash Deep Singh
,
Luis Antonio Ribot García
,
Joseph Noor
,
Mani Srivastava
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2005.03068
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2005.03068
The increasing ubiquity of low-cost wireless sensors has enabled users to easily deploy systems to remotely monitor and control their environments. However, this raises privacy concerns for third-party occupants, such as a hotel room guest who may be unaware of deployed clandestine sensors. Previous methods focused on specific modalities such as detecting cameras but do not provide a generalized and comprehensive method to capture arbitrary sensors which may be "spying" on a user. In this work, we propose SnoopDog, a framework to not only detect common Wi-Fi-based wireless sensors that are actively monitoring a user, but also classify and localize each device. SnoopDog works by establishing causality between patterns in observable wireless traffic and a trusted sensor in the same space, e.g., an inertial measurement unit (IMU) that captures a user's movement. Once causality is established, SnoopDog performs packet inspection to inform the user about the monitoring device. Finally, SnoopDog localizes the clandestine device in a 2D plane using a novel trial-based localization technique. We evaluated SnoopDog across several devices and various modalities and were able to detect causality for snooping devices 95.2% of the time and localize devices to a sufficiently reduced sub-space.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2005.03068
- https://arxiv.org/pdf/2005.03068
- OA Status
- green
- Cited By
- 4
- References
- 39
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W3015492676
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3015492676Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2005.03068Digital Object Identifier
- Title
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I Always Feel Like Somebody's Sensing Me! A Framework to Detect, Identify, and Localize Clandestine Wireless SensorsWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-05-06Full publication date if available
- Authors
-
Akash Deep Singh, Luis Antonio Ribot García, Joseph Noor, Mani SrivastavaList of authors in order
- Landing page
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https://arxiv.org/abs/2005.03068Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2005.03068Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2005.03068Direct OA link when available
- Concepts
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Computer science, Inertial measurement unit, Wireless, Wireless sensor network, Real-time computing, Computer security, Causality (physics), Modalities, Network packet, Artificial intelligence, Computer network, Telecommunications, Sociology, Social science, Physics, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2023: 2, 2021: 1Per-year citation counts (last 5 years)
- References (count)
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39Number of works referenced by this work
- Related works (count)
-
20Other works algorithmically related by OpenAlex
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| best_oa_location.version | submittedVersion |
| best_oa_location.raw_type | text |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | False |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | http://arxiv.org/abs/2005.03068 |
| primary_location.id | pmh:oai:arXiv.org:2005.03068 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306400194 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | arXiv (Cornell University) |
| primary_location.source.host_organization | https://openalex.org/I205783295 |
| primary_location.source.host_organization_name | Cornell University |
| primary_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| primary_location.license | |
| primary_location.pdf_url | https://arxiv.org/pdf/2005.03068 |
| primary_location.version | submittedVersion |
| primary_location.raw_type | text |
| primary_location.license_id | |
| primary_location.is_accepted | False |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | http://arxiv.org/abs/2005.03068 |
| publication_date | 2020-05-06 |
| publication_year | 2020 |
| referenced_works | https://openalex.org/W2833690542, https://openalex.org/W2934945105, https://openalex.org/W2599271868, https://openalex.org/W2167266744, https://openalex.org/W2923835375, https://openalex.org/W2983028905, https://openalex.org/W2621148797, https://openalex.org/W2291324458, https://openalex.org/W2928689123, https://openalex.org/W2163839940, https://openalex.org/W2906551905, https://openalex.org/W2787614270, https://openalex.org/W2178225550, https://openalex.org/W2394784643, https://openalex.org/W2582846117, https://openalex.org/W2792106437, https://openalex.org/W2974043855, https://openalex.org/W1623286636, https://openalex.org/W2038396847, https://openalex.org/W2148253973, https://openalex.org/W2911205424, https://openalex.org/W1993128363, https://openalex.org/W2157349061, https://openalex.org/W2559096601, https://openalex.org/W2101449154, https://openalex.org/W2007920345, https://openalex.org/W2574448563, https://openalex.org/W2088944946, https://openalex.org/W3100966310, https://openalex.org/W2118291130, https://openalex.org/W1606643854, https://openalex.org/W2028437265, https://openalex.org/W2037869946, https://openalex.org/W2807035766, https://openalex.org/W2979856235, https://openalex.org/W2538592916, https://openalex.org/W2968383486, https://openalex.org/W2969862110, https://openalex.org/W1990260760 |
| referenced_works_count | 39 |
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| abstract_inverted_index.be | 37, 68 |
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| abstract_inverted_index.do | 54 |
| abstract_inverted_index.in | 109, 117, 154 |
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| abstract_inverted_index.The | 0 |
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| abstract_inverted_index.but | 53, 95 |
| abstract_inverted_index.for | 26, 179 |
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| abstract_inverted_index.the | 118, 142, 145, 151, 184 |
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| abstract_inverted_index.such | 29, 49 |
| abstract_inverted_index.that | 89, 127 |
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| abstract_inverted_index.user | 143 |
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| abstract_inverted_index.(IMU) | 126 |
| abstract_inverted_index.95.2% | 182 |
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| abstract_inverted_index.plane | 157 |
| abstract_inverted_index.their | 19 |
| abstract_inverted_index.user, | 94 |
| abstract_inverted_index.user. | 72 |
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| abstract_inverted_index.which | 66 |
| abstract_inverted_index.work, | 75 |
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| abstract_inverted_index.across | 167 |
| abstract_inverted_index.common | 85 |
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| abstract_inverted_index.detect | 84, 177 |
| abstract_inverted_index.device | 153 |
| abstract_inverted_index.easily | 11 |
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| abstract_inverted_index.raises | 23 |
| abstract_inverted_index.sensor | 116 |
| abstract_inverted_index.space, | 120 |
| abstract_inverted_index.user's | 130 |
| abstract_inverted_index.between | 107 |
| abstract_inverted_index.cameras | 52 |
| abstract_inverted_index.capture | 63 |
| abstract_inverted_index.control | 18 |
| abstract_inverted_index.device. | 101, 147 |
| abstract_inverted_index.devices | 169, 181, 188 |
| abstract_inverted_index.enabled | 8 |
| abstract_inverted_index.focused | 45 |
| abstract_inverted_index.methods | 44 |
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| abstract_inverted_index.privacy | 24 |
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| abstract_inverted_index.reduced | 192 |
| abstract_inverted_index.sensors | 6, 65, 88 |
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| abstract_inverted_index."spying" | 69 |
| abstract_inverted_index.Finally, | 148 |
| abstract_inverted_index.However, | 21 |
| abstract_inverted_index.Previous | 43 |
| abstract_inverted_index.SnoopDog | 102, 136, 149, 166 |
| abstract_inverted_index.actively | 91 |
| abstract_inverted_index.captures | 128 |
| abstract_inverted_index.classify | 97 |
| abstract_inverted_index.concerns | 25 |
| abstract_inverted_index.deployed | 40 |
| abstract_inverted_index.inertial | 123 |
| abstract_inverted_index.localize | 99, 187 |
| abstract_inverted_index.low-cost | 4 |
| abstract_inverted_index.patterns | 108 |
| abstract_inverted_index.performs | 137 |
| abstract_inverted_index.remotely | 15 |
| abstract_inverted_index.sensors. | 42 |
| abstract_inverted_index.snooping | 180 |
| abstract_inverted_index.specific | 47 |
| abstract_inverted_index.ubiquity | 2 |
| abstract_inverted_index.wireless | 5, 87, 111 |
| abstract_inverted_index.SnoopDog, | 78 |
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| abstract_inverted_index.detecting | 51 |
| abstract_inverted_index.evaluated | 165 |
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| abstract_inverted_index.modalities | 48, 172 |
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| abstract_inverted_index.observable | 110 |
| abstract_inverted_index.occupants, | 28 |
| abstract_inverted_index.sub-space. | 193 |
| abstract_inverted_index.technique. | 163 |
| abstract_inverted_index.Wi-Fi-based | 86 |
| abstract_inverted_index.clandestine | 41, 152 |
| abstract_inverted_index.generalized | 58 |
| abstract_inverted_index.measurement | 124 |
| abstract_inverted_index.third-party | 27 |
| abstract_inverted_index.trial-based | 161 |
| abstract_inverted_index.established, | 135 |
| abstract_inverted_index.establishing | 105 |
| abstract_inverted_index.localization | 162 |
| abstract_inverted_index.sufficiently | 191 |
| abstract_inverted_index.comprehensive | 60 |
| abstract_inverted_index.environments. | 20 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/16 |
| sustainable_development_goals[0].score | 0.6100000143051147 |
| sustainable_development_goals[0].display_name | Peace, Justice and strong institutions |
| citation_normalized_percentile |