Sizzle: A standards-based end-to-end security architecture for the embedded Internet

Gupta, Vipul; Wurm, Michael; Zhu, Yuhan; Millard, Matthew; Fung, Stephen; Gura, Nils; Eberle, Hans; Shantz, Sheueling Chang

doi:10.1016/j.pmcj.2005.08.005

Cited by 126 publications

(99 citation statements)

References 15 publications

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“…However, the verification takes several minutes. Sizzle (Gupta et al, 2005) is another application of ECC system developed recently. The standard internet security protocol(SSL) is efficiently implemented in sensor motes by using ECC.…”

Section: Related Workmentioning

confidence: 99%

Elliptic curve cryptography-based access control in sensor networks

Wang¹,

Sheng²,

Li³

2006

IJSN

145

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Access control in sensor networks is used to authorise and grant users the right to access the network and data collected by sensors. Different users have different access right due to the access restriction implicated by the data security and confidentiality. Even though symmetric-key scheme, which has been investigated extensively for sensor networks, can fulfil the requirement, public-key cryptography is more flexible and simple rendering a clean interface for the security component. Against the popular belief that a public key scheme is not practical for sensor networks, this paper describes a public-key implementation of access control in a sensor network. We detail the implementation of Elliptic Curve Cryptography (ECC) over primary field, a public-key cryptography scheme, on TelosB, which is the latest sensor network platform. We evaluate the performance of our implementation and compare with other implementations we have ported to TelosB.

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Section: Related Workmentioning

confidence: 99%

Elliptic curve cryptography-based access control in sensor networks

Wang¹,

Sheng²,

Li³

2006

IJSN

145

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“…Applications such as MedCheck [27] are needed on the smartphones for PoC applications. For developing embedded secure web servers, an architecture similar to Sizzle platform is required in securing PoC web servers [28].…”

Section: Cross-site Scriptingmentioning

confidence: 99%

Security Framework for Managing Data Security within Point of Care Tests

Tulasidas¹,

Mackay²,

Hudson³

et al. 2017

JSEA

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Point of Care (PoC) devices and systems can be categorized into three broad classes (CAT 1, CAT 2, and CAT 3) based on the context of operation and usage. In this paper, the categories are defined to address certain usage models of the PoC device. PoC devices that are used for PoC testing and diagnostic applications are defined CAT 1 devices; PoC devices that are used for patient monitoring are defined as CAT 2 devices (PoCM); PoC devices that are used for as interfacing with other devices are defined as CAT 3 devices (PoCI). The PoCI devices provide an interface gateway for collecting and aggregating data from other medical devices. In all categories, data security is an important aspect. This paper presents a security framework concept, which is applicable for all of the classes of PoC operation. It outlines the concepts and security framework for preventing security challenges in unauthorized access to data, unintended data flow, and data tampering during communication between system entities, the user, and the PoC system. The security framework includes secure layering of basic PoC system architecture, protection of PoC devices in the context of application and network. Developing the security framework is taken into account of a thread model of the PoC system. A proposal for a low-level protocol is discussed. This protocol is independent of communications technologies, and it is elaborated in relation to providing security. An algorithm that can be used to overcome the threat challenges has been shown using the elements in the protocol. The paper further discusses the vulnerability scanning process for the PoC system interconnected network. The paper also presents a four-step process of authentication and authorization framework for providing the security for the PoC system. Finally, the paper concludes with the machine to machine (M2M) security viewpoint and discusses the key stakeholders within an actual deployment of the PoC system and its security challenges.

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“…Gura et al (2004) compare the performance of two asymmetric cryptography algorithms, namely Rivest-Shamir-Adleman (RSA) and ECC on 8 bit CPUs, showing that ECC is better suited for devices with restricted computational resources. Gupta et al (2005) present results of implementing a web server with Secure Socket Layer (SSL) on constrained embedded devices. They use ECC based cryptography and the device having 8-bit CPU and 4 kB of RAM can complete a full SSL handshake in less than 4 seconds.…”

Section: Related Workmentioning

confidence: 99%

Trading off Latency Against Security in Open Energy Metering Infrastructures

Kalns

Nadjm‐Tehrani

Vasilevskaya

2016

Electronic Workshops in Computing

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Embedded devices are expected to transform the landscape of networked services in many domains, among them smart homes and smart grid systems. The reliable and optimised operation of smart grids is dependent on reliable data provided by end nodes (e.g. smart meters), and assurance of secure communication across networks. Understanding whether advanced security building blocks have a role to play in forthcoming infrastructures needs a basic understanding of each potential building block with respect to resource usage and impact on timing. In this paper we study the performance penalty of asymmetric cryptography techniques used for protection of wirelessly transmitted data in a prototype smart metering system. The prototype system is built using hardware and software components from "Open Energy Monitor" project using a wireless data link between the metering device and the data collector device. We investigate the use of the Elliptic Curve Integrated Encryption Scheme (ECIES) in two versions -with standard building blocks and with added Elliptic Curve Digital Signature Algorithm (ECDSA) support. The use of the ECDSA allows the system to achieve the non-repudiation property. We compare those cryptographic techniques with the Advanced Encryption Standard in Galois Counter Mode (AES-GCM) technique in two versions -with 128 bit and 256 bit keys. Performance is compared in terms of execution time of (1) preparing data, (2) unpacking it, and (3) roundtrip time. We then discuss the implications of the measurements, where the roundtrip time of sending one measurement ranges from 378 ms in case of AES128-GCM to 16.3 sec using ECIES with ECDSA.Smart meter infrastructure security, Elliptic Curve Cryptography, Performance and latency trade-off

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Sizzle: A standards-based end-to-end security architecture for the embedded Internet

Cited by 126 publications

References 15 publications

Elliptic curve cryptography-based access control in sensor networks

Elliptic curve cryptography-based access control in sensor networks

Security Framework for Managing Data Security within Point of Care Tests

Trading off Latency Against Security in Open Energy Metering Infrastructures

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