IoTCrawler: Challenges and Solutions for Searching the Internet of Things
- Scalability: Coming from the issue of Volume, a requirement for scalability arises when designing products for the IoT. The huge amount of available, and often heterogeneous, data sources, which have to be considered for the process of search, leads to a challenge of scalability. All components and solutions in this environment have to be designed to work with large scale data. As a result, the machine initiated search shall be answered within a reasonable time.
- Semantics and Context for Machine Initiated Search: Newly emerging search models require to tackle the search problems based on the human- and machine originated users’ contexts and requirements such as location, time, activity, previous records and profile. The search results are targeted to be based on emerging IoT application models, where search can be initiated without human involvement. The generation of higher-level context, such as traffic conditions, e.g., from low-level observations, can enhance the search functionality for applications that require information on trends and profiles about sensory data. Generated data from IoT deployments are largely multivariate, and therefore require aggregation methods that can preserve and represent its key characteristics, while reducing the processing time and storage necessities.
- Discovery and Search: To provide a well performing and responsive IoT search framework, the entire process needs to be considered as a two stages approach, namely Discovery and Search. In the first stage, knowledge about available IoT devices and the data streams they provide has to be crawled. The goal is to build up a data repository containing available information about the data streams. In the second stage, while processing a search request, the potential data streams, satisfying the search query, are then extracted from the repository. Before being returned to the requester, the list of candidates needs to be ranked, to allow the application to use the best fitting data streams.
- Security and Privacy by Design: It is vital that Privacy and Security are addressed from the beginning in a design phase and through all the development of a project. It requires authentication, access control and privacy mechanisms in order to provide a controlled environment where providers can specify the access policy attached to their data, and even broadcast it in a privacy preserving manner, so that only legitimate consumers are able to access the information.
2. Related Work
2.1. Search over Discovered Metadata
2.2. Semantics, Ontologies and Information Models for Interoperability
2.3. Security and Privacy in IoT
2.4. Reliability in IoT
2.5. Indexing of Discovered Resources
2.6. Ranking of Search Results
3. Search Framework for IoT
4. Enablers for Discovery and Processing Layer
4.1. Information Model
4.2. Federation of Metadata Repositories
4.3.1. Fault Detection and Fault Recovery
4.3.2. Virtual Sensor
4.4. Semantic Enrichment
4.4.1. QoI Analyser
4.4.2. Pattern Extractor
5. Enablers for Search and Orchestration Layer
5.1. Privacy and Security
- Untrustworthy entities: First, Policy Administration Point (PAP) might be subject to an attack and perform malicious actions such as updating a policy against the resource owner’s will. Having a Blockchain helps avoid misbehaviour of PAP. The access control policy’s integrity is checked by registering and checking its meta-data, such as the hash value managed by the Blockchain network. Second, policy evaluation done by Policy Decision Point (PDP), which could be manipulated by an untrusted PAP. The Blockchain ensures this misbehaviour to be detectable.
- Auditability: The verifiable property of Blockchain allows detecting if an access control service falsely denied access to a subject that the policy would grant or if the access control service granted a permission while the policy was not satisfied.
- Revocability: The attribute-based access control model that we have in this framework assumes, once a subject has granted an access permission, that the subject will receive an access token. It is challenging to revoke the token once it has been misused or stolen. Blockchain resolves this issue by executing a token smart contract to invalidate the vulnerable token.
- Fault tolerance: Access control components are distributed among peers over the Blockchain network. Such components are PAP, PDP and CM, among others. By having functions executed as smart contracts and invoked by a peer of the network, it avoids becoming a single point of failure as it would be the case with traditional PAP, PDP or CM.
- Integrity: New changes may cause disruption of such services and therefore they should be done cautiously. No single individual can introduce changes. This property is essential in the network where the participants often do not trust each other.
5.1.1. Identity Management and Authentication Evaluation
5.1.2. Authorisation Evaluation
5.3. Search Enabler
6. Application Domain Instantiation
6.1. Smart Home—Semantic Integration Focus
6.2. Smart Parking—Security and Privacy Focus
7. Conclusions and Future Work
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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|Model/Data Set||Arrow Head||Lightning 7||Coffee||Ford A||Proximal|
|Raw Data k-means||0.47||0.12||0.33||0.05||0.46|
|PCA-Lagrangian + GMM||0.69|
|Raw data + GMM||0.46|
|Lagrangian scaling + GMM||0.45|
|PCA + GMM||0.39|
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Iggena, T.; Bin Ilyas, E.; Fischer, M.; Tönjes, R.; Elsaleh, T.; Rezvani, R.; Pourshahrokhi, N.; Bischof, S.; Fernbach, A.; Xavier Parreira, J.; Schneider, P.; Smirnov, P.; Strohbach, M.; Truong, H.; González-Vidal, A.; Skarmeta, A.F.; Singh, P.; Beliatis, M.J.; Presser, M.; Martinez, J.A.; Gonzalez-Gil, P.; Krogbæk, M.; Holmgård Christophersen, S. IoTCrawler: Challenges and Solutions for Searching the Internet of Things. Sensors 2021, 21, 1559. https://doi.org/10.3390/s21051559
Iggena T, Bin Ilyas E, Fischer M, Tönjes R, Elsaleh T, Rezvani R, Pourshahrokhi N, Bischof S, Fernbach A, Xavier Parreira J, Schneider P, Smirnov P, Strohbach M, Truong H, González-Vidal A, Skarmeta AF, Singh P, Beliatis MJ, Presser M, Martinez JA, Gonzalez-Gil P, Krogbæk M, Holmgård Christophersen S. IoTCrawler: Challenges and Solutions for Searching the Internet of Things. Sensors. 2021; 21(5):1559. https://doi.org/10.3390/s21051559Chicago/Turabian Style
Iggena, Thorben, Eushay Bin Ilyas, Marten Fischer, Ralf Tönjes, Tarek Elsaleh, Roonak Rezvani, Narges Pourshahrokhi, Stefan Bischof, Andreas Fernbach, Josiane Xavier Parreira, Patrik Schneider, Pavel Smirnov, Martin Strohbach, Hien Truong, Aurora González-Vidal, Antonio F. Skarmeta, Parwinder Singh, Michail J. Beliatis, Mirko Presser, Juan A. Martinez, Pedro Gonzalez-Gil, Marianne Krogbæk, and Sebastian Holmgård Christophersen. 2021. "IoTCrawler: Challenges and Solutions for Searching the Internet of Things" Sensors 21, no. 5: 1559. https://doi.org/10.3390/s21051559