Tailoring Onion Routing to the Internet of Things: Security and Privacy in Untrusted Environments

Hiller, Jens; Pennekamp, Jan; Dahlmanns, Markus; Henze, Martin; Panchenko, Andriy; Wehrle, Klaus

doi:10.1109/icnp.2019.8888033

Cited by 33 publications

(21 citation statements)

References 37 publications

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“…All experiments are conducted on a PC with a CPU 2.30 GHz, 8 GB of RAM. We compare the anonymous performance of our lightweight anonymous communication model with several existing anonymous models [8,36,19] in Table 2. It can be seen from Table 2 that only our model achieves all the anonymities, whereas the other models cannot.…”

Section: Experiments and Resultsmentioning

confidence: 99%

LacminCC: Lightweight Anonymous Communication Model In Cloud Computing

Li¹,

Wang

Hong-wei

et al. 2021

Preprint

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With increasing application of cloud computing and big data technologies, a large amount of personal information is stored on the Internet, which raises the issue of privacy leakage.To protect people's data privacy, this paper firstly presents a new anonymous Identify-Based Encryption (IBE) scheme and gives the proof of its security under the Bilinear Diffie-Hellman Security Assumption. Then, by introducing the anonymous IBE scheme into anonymous communication fields, this paper introduces a new lightweight anonymous communication model for cloud computing, which guarantees the anonymity of system users and the security of messages in small groups. Our analysis shows that, the proposed communication model cannot only reduce memory consumption and improve message transmission efficiency, but also effectively resist traffic-analysis attacks, node eavesdropping, and finally achieve secure anonymous communication in cloud computing.

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Section: Experiments and Resultsmentioning

confidence: 99%

LacminCC: Lightweight Anonymous Communication Model In Cloud Computing

Li¹,

Wang

Hong-wei

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…All experiments are conducted on a PC with a CPU 2.30 GHz, 8 GB of RAM. We compare the anonymous performance of our lightweight anonymous communication model with several existing anonymous models [8,19,36] in Table 2. It can be seen from Table 2 that only our model achieves all the anonymities, whereas the other models cannot.…”

Section: Experiments and Resultsmentioning

confidence: 99%

“…The idea of onion routing has been extended to all directions. Hiller et al used onion routing in the Internet of Things to protect the private sensitive information of data owners [8]. Raza uses onion routing to implement a distributed search engine [9].…”

mentioning

confidence: 99%

LacminCC: lightweight anonymous communication model in cloud computing

Wang

Hong-wei

et al. 2021

J Wireless Com Network

View full text Add to dashboard Cite

With increasing application of cloud computing and big data technologies, a large amount of personal information is stored on the Internet, which raises the issue of privacy leakage. To protect people’s data privacy, this paper firstly presents a new anonymous Identify-Based Encryption (IBE) scheme and gives the proof of its security under the Bilinear Diffie–Hellman Security Assumption. Then, by introducing the anonymous IBE scheme into anonymous communication fields, this paper introduces a new lightweight anonymous communication model for cloud computing, which guarantees the anonymity of system users and the security of messages in small groups. Our analysis shows that, the proposed communication model cannot only reduce memory consumption and improve message transmission efficiency, but also effectively resist traffic-analysis attacks, node eavesdropping, and finally achieve secure anonymous communication in cloud computing.

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“…This is still considered an open issue in the general case of constrained IoT devices (see, e.g. [20]), making such approach infeasible in practice in the short term.…”

Section: Anonymous Communication Protocolmentioning

confidence: 99%

Secure Distributed Queries over Large Sets of Personal Home Boxes

Ladjel

Anciaux

Pelletier

et al. 2020

Transactions on Large-Scale Data- And Knowledge-Centered Systems XLIV

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Smart disclosure initiatives and new regulations such as GDPR allow individuals to get the control back on their data by gathering their entire digital life in a Personal Data Management Systems (PDMS). Multiple PDMS architectures exist and differ on their ability to preserve data privacy and to perform collective computations crossing data of multiple individuals (e.g., epidemiological or social studies) but none of them satisfy both objectives. The emergence of Trusted Execution Environments (TEE) changes the game. We propose a solution called Trusted PDMS, combining the TEE and PDMS properties to manage the data of each individual, and a complete framework to execute collective computation on top of them, with strong privacy and fault tolerance guarantees. We demonstrate the practicality of the solution through a real case-study being conducted over 10.000 patients in the healthcare field.

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Tailoring Onion Routing to the Internet of Things: Security and Privacy in Untrusted Environments

Cited by 33 publications

References 37 publications

LacminCC: Lightweight Anonymous Communication Model In Cloud Computing

LacminCC: Lightweight Anonymous Communication Model In Cloud Computing

LacminCC: lightweight anonymous communication model in cloud computing

Secure Distributed Queries over Large Sets of Personal Home Boxes

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