I Am Joe's Fridge: Scalable Identity in the Internet of Things

Anantharaman, Prashant; Palani, K.; Nicol, David M.; Smith, Sean W.

doi:10.1109/ithings-greencom-cpscom-smartdata.2016.47

Cited by 3 publications

(6 citation statements)

References 13 publications

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“…16 Recall that both the DCMS 13 guidelines document and ETSI provisions document suggest use of the 1013-item dataset for next-level detail. a whole, 17 our results show that it appears to be more useful (i.e., the sub-topics individually are more actionable, as measured by our methodology, than together, Fig. 6.1) to consider each sub-topic as a distinct piece of advice if actionability is important to the advice follower.…”

Section: Dcms 13 Guidelines (Tagging Results and Actionability)mentioning

confidence: 72%

“…The main contribution of this chapter is the development of the coding tree methodology and its use to analyze a large collection of IoT security advice. In particular, we examined how actionable current advice 17 is, and what advice characteristics (i.e., corresponding to the codes of Fig. 4.4) emerge from this dataset.…”

Section: Discussionmentioning

confidence: 99%

“…We note that, beyond the device identification process (our focus) per se, the resulting classification of device instances is often used in subsequent management or processing tasks as observed in our literature review (e.g., applying policies to specific classes of devices). ✓ Noguchi [161] ✓ Perdisci [167] ✓ Ray [171] ✓ AA3 Yousefnezhad [225] ✓ AA3 Aneja [19] ✓ AA3 Chowdhury [52] ✓ AA3 Hamad [100] ✓ ✓ AA3 Anantharaman [18] ✓ ✓ Kotak [126] ✓ ✓ Ammar [15] ✓ Ammar [16] ✓ Santos [183] ✓ Meidan [150] ✓ Singla [190] ✓ Marchal [144] ✓ Bao [28] ✓ Thomsen [203] ✓ Miettinen [152] ✓ Yu [227] ✓ Bezawada [40] ✓ Salman [181] ✓ Marchal [144] ✓ Aksoy [6] ✓ Kumar [130] ✓ AA4 Anantharaman [17] ✓ AA1, AA4 Mukhandi [155] ✓ AA1 Bin-Rabiah [41] ✓ AA1 Gritti [91] ✓ AA1 Kalra [119] ✓ AA1 Malche [143] ✓ AA1 Nashwan [157] ✓ AA1 Kim [122] ✓ AA2 Kim [123] ✓ AA1, AA2 Wang [214] ✓ AA2 Niya [160] ✓ AA2…”

Section: Determine Device Classesmentioning

confidence: 99%

“…It is evident from Table 7.1 that in almost all cases reviewed, there is a one-to-one mapping of objective to approach. In cases where a paper looks to reach two objectives (e.g., [17,100,126]), typically one approach is used for each objective.…”

Section: Objective and Approach Categorization Insightsmentioning

confidence: 99%

“…Reviewed AA2 proposals include the following. Anantharaman [17] AA1, AA4 ✓ ✓ Nashwan [157] AA1 ✓ ▲ Bin-Rabiah [41] AA1 ✓ ▲ Kalra [119] AA1 ✓ ▲ Gritti [91] AA1 ✓ Malche [143] AA1 ✓ Mukhandi [155] AA1 ✓ Kumar [130] AA4 ✓ ▲ Kim [123] AA1, AA2 ✓ Wang [214] AA2 ✓ ▲ Kim [122] AA2 ✓ ▲ Niya [160] AA2 ✓ revocation of key pairs (a similar challenge as in certificate-based approaches, Section 7.4). The primitives used to facilitate authentication and encryption in JEDI and authorization with macaroons may be lightweight, but the infrastructure and management requirements are non-trivial.…”

Section: Further Analysis Of One Identification Approach: Authenticationmentioning

confidence: 99%

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On Security Best Practices, Systematic Analysis of Security Advice, and Internet of Things Devices

Bellman¹

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While Internet of Things (IoT) security best practices have recently attracted considerable attention from industry and governments, academic research has highlighted the failure of many IoT product manufacturers to follow accepted practices. We begin by investigating a surprising lack of consensus, and void in the literature, on what (generically) best practice means, and provide a technical examination of related terminology. We use iterative inducting coding to design an analysis methodology for categorizing security advice and measuring its actionability. We use this methodology to analyze three datasets: a set of 1013 IoT security best practices, recommendations, and guidelines, and two formally recommended IoT security advice documents. We find all three sets to be largely non-actionable. Through design and use of this methodology, we identify the characteristics of actionable security advice.We also analyze recent work on IoT device identification based on three identification objectives (distinguish device instances, distinguish device classes, and authenticate device identity), and the technical approaches by which they are reached: device fingerprinting, classification, and authentication. We differentiate the role of these objectives and approaches in IoT security, and develop a model relating them. viii ix Ashraf Matrawy (Carleton University), and Dr. Mohammad Zulkernine (Queen's University).Finally, a special thank-you goes to my family and friends for all the support over the past five years-your encouragement is deeply appreciated, and I could not have done this without your support.

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Section: Dcms 13 Guidelines (Tagging Results and Actionability)mentioning

confidence: 72%

Section: Discussionmentioning

confidence: 99%