Name
Abstract | ||
|---|---|---|
The Internet of Things (IoT) offers immense benefits by enabling devices to leverage networked resources thereby making intelligent decisions. The numerous heterogeneous connected devices that exist throughout the IoT system creates new security and privacy concerns. Some of these concerns can be overcome through trust, transparency, and integrity, which can be achieved with data provenance. Data provenance, also known as data lineage, provides a history of transformations that occurs on a data object from the time it was created to its current state. Data provenance has been explored in the areas of scientific computing, business, forensic analysis, and intrusion detection. Data provenance can help in detecting and mitigating malicious cyber attacks. In this paper, we explore the integration of provenance within the IoT. We introduce Provenance Aware Internet of Things System (PAIoTS), a provenance collection framework for IoT devices. We evaluate the effectiveness of our framework by developing a prototype system for proof of concept. |
Year | Venue | Field |
|---|---|---|
2017 | 2017 IEEE SMARTWORLD, UBIQUITOUS INTELLIGENCE & COMPUTING, ADVANCED & TRUSTED COMPUTED, SCALABLE COMPUTING & COMMUNICATIONS, CLOUD & BIG DATA COMPUTING, INTERNET OF PEOPLE AND SMART CITY INNOVATION (SMARTWORLD/SCALCOM/UIC/ATC/CBDCOM/IOP/SCI) | Data science,Transparency (graphic),Data modeling,Computer science,Data lineage,Internet of Things,Computer network,Provenance,Proof of concept,Intrusion detection system,Cloud computing |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ebelechukwu Nwafor | 1 | 0 | 0.34 |
| Andre Campbell | 2 | 0 | 0.34 |
| David Hill | 3 | 2 | 1.08 |
| Gedare Bloom | 4 | 68 | 13.95 |