Javascript must be enabled to continue!
A Commitment Scheme with Output Locality-3 Fit for the IoT Device
View through CrossRef
Low output locality is a property of functions, in which every output bit depends on a small number of input bits. In IoT devices with only a fragile CPU, it is important for many IoT devices to cooperate to execute a single function. In such IoT’s collaborative work, a feature of low output locality is very useful. This is why it is desirable to reconstruct cryptographic primitives with low output locality. However, until now, commitment with a constant low output locality has been constructed by using strong randomness extractors from a nonconstant-output-locality collision-resistant hash function. In this paper, we construct a commitment scheme with output locality-3 from a constant-output-locality collision-resistant hash function for the first time. We prove the computational hiding property of our commitment by the decisional
M
,
δ
-bSVP assumption and prove the computational binding property by the
M
,
δ
-bSVP assumption, respectively. Furthermore, we prove that the
M
,
δ
-bSVP assumption can be reduced to the decisional
M
,
δ
-bSVP assumption. We also give a parameter suggestion for our commitment scheme with the 128 bit security.
Title: A Commitment Scheme with Output Locality-3 Fit for the IoT Device
Description:
Low output locality is a property of functions, in which every output bit depends on a small number of input bits.
In IoT devices with only a fragile CPU, it is important for many IoT devices to cooperate to execute a single function.
In such IoT’s collaborative work, a feature of low output locality is very useful.
This is why it is desirable to reconstruct cryptographic primitives with low output locality.
However, until now, commitment with a constant low output locality has been constructed by using strong randomness extractors from a nonconstant-output-locality collision-resistant hash function.
In this paper, we construct a commitment scheme with output locality-3 from a constant-output-locality collision-resistant hash function for the first time.
We prove the computational hiding property of our commitment by the decisional
M
,
δ
-bSVP assumption and prove the computational binding property by the
M
,
δ
-bSVP assumption, respectively.
Furthermore, we prove that the
M
,
δ
-bSVP assumption can be reduced to the decisional
M
,
δ
-bSVP assumption.
We also give a parameter suggestion for our commitment scheme with the 128 bit security.
Related Results
Access mechanisms for massive Internet of Things in 5G and beyond networks
Access mechanisms for massive Internet of Things in 5G and beyond networks
(English) The Massive Internet of Things (MIoT) characterizes a communication scenario where a massive number of battery-operated devices perform infrequent, primarily uplink-orien...
Classification, natural history, and evolution of Epiphloeinae (Coleoptera: Cleridae). Part VII. The genera Hapsidopteris Opitz, Iontoclerus Opitz, Katamyurus Opitz, Megatrachys Opitz, Opitzia Nemesio, Pennasolis Opitz, new genus, Pericales Opitz, new gen
Classification, natural history, and evolution of Epiphloeinae (Coleoptera: Cleridae). Part VII. The genera Hapsidopteris Opitz, Iontoclerus Opitz, Katamyurus Opitz, Megatrachys Opitz, Opitzia Nemesio, Pennasolis Opitz, new genus, Pericales Opitz, new gen
This study deals with minimally speciose epiphloeine genera. Hapsidopteris, based on H. diastenus Opitz, (type locality: México: Jalapa), is the presumed sister taxon of Opitzia Ne...
Pelatihan Internet of Things (IoT) dalam peningkatan kompetensi siswa multimedia di SMK Perguruan Buddhi
Pelatihan Internet of Things (IoT) dalam peningkatan kompetensi siswa multimedia di SMK Perguruan Buddhi
Pelatihan Internet of Things (IoT) menjadi bagian penting dalam pengembangan kompetensi siswa jurusan multimedia di SMK Perguruan Buddhi. Era digital menuntut adanya pemahaman mend...
Impact and Innovations of Azure IoT: Current Applications, Services, and Future Directions
Impact and Innovations of Azure IoT: Current Applications, Services, and Future Directions
Azure IoT, developed by Microsoft, is a leading platform in the realm of Internet of Things (IoT), revolutionizing industries through enhanced connectivity, robust data management,...
INTEGRATION IOT AND BIM FOR TECHNOLOGY AND IOT ENVIRONMENT
INTEGRATION IOT AND BIM FOR TECHNOLOGY AND IOT ENVIRONMENT
Abstract: This research focuses on technology and integration tools for IoT environments, with an emphasis on three main aspects: the integration of Building Information Modeling (...
Performance and Verifiability of IoT Security Protocols
Performance and Verifiability of IoT Security Protocols
Performance et vérifiabilité des protocoles de sécurité IoT
L'internet des objets (IoT) est l'une des technologies les plus importantes de notre monde actuel. Il es...
IoT-Flock: An Open-source Framework for IoT Traffic Generation
IoT-Flock: An Open-source Framework for IoT Traffic Generation
Abstract
Network traffic generation is one of the primary techniques that is used to design and analyze the performance of network security systems. However, due to the div...
Applications of Ontology in the Internet of Things: A Systematic Analysis
Applications of Ontology in the Internet of Things: A Systematic Analysis
Ontology has been increasingly implemented to facilitate the Internet of Things (IoT) activities, such as tracking and information discovery, storage, information exchange, and obj...

