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Technology and Security Systems
Research Guide
What is Technology and Security Systems?
Technology and Security Systems is a field within computer science that applies Internet of Things (IoT) and Big Data technologies to areas including data security, deep learning, wireless communication, smart grid, sensor networks, cloud computing, machine learning, and industrial IoT.
The field encompasses 28,248 papers focused on IoT and Big Data applications with security implications. Key areas include sensor networks, cloud computing, and industrial IoT systems. Growth data over the last five years is not available.
Topic Hierarchy
Research Sub-Topics
IoT Data Security and Privacy
This sub-topic addresses encryption, authentication, and intrusion detection for protecting IoT device data streams. Researchers develop lightweight protocols and blockchain integrations.
Deep Learning in IoT Applications
This sub-topic explores convolutional and recurrent neural networks for edge computing in sensor data analysis. Researchers optimize models for resource-constrained IoT devices.
Smart Grid Security with IoT
This sub-topic focuses on cybersecurity for IoT-enabled energy distribution, including anomaly detection and resilience. Researchers simulate attacks and test distributed ledger solutions.
Industrial IoT and Sensor Networks
This sub-topic investigates wireless sensor deployments for manufacturing monitoring and fault prediction. Researchers address scalability, latency, and integration with Industry 4.0.
Cloud Computing for Big Data in IoT
This sub-topic covers hybrid cloud architectures for processing massive IoT-generated datasets. Researchers study fog computing, data analytics, and scalability frameworks.
Why It Matters
Technology and Security Systems supports secure deployment of IoT in agriculture, railways, and smart infrastructure. For example, Fan TongKe (2013) applied cloud computing and IoT to smart agriculture, addressing issues in China's agricultural modernization through real-time data processing. In railways, Paula Fraga‐Lamas et al. (2017) reviewed Industrial IoT-connected systems enabling communication technologies for smart trains. These applications enhance data security in wireless networks and sensor systems, as seen in rice disease detection using deep learning by Guoxiong Zhou et al. (2019) with 243 citations.
Reading Guide
Where to Start
'Research on the architecture of Internet of Things' by Miao Wu et al. (2010) provides a foundational overview of IoT features and distinctions from Internet and telecom networks, making it accessible for beginners.
Key Papers Explained
Miao Wu et al. (2010) 'Research on the architecture of Internet of Things' establishes core IoT architecture (612 citations), which Shuai Zhang et al. (2010) 'Cloud Computing Research and Development Trend' extends to cloud models (414 citations). Fan TongKe (2013) 'Smart Agriculture Based on Cloud Computing and IOT' applies these to agriculture (296 citations), while Paula Fraga‐Lamas et al. (2017) 'Towards the Internet of Smart Trains: A Review on Industrial IoT-Connected Railways' advances to industrial contexts (257 citations). Guoxiong Zhou et al. (2019) 'Rapid Detection of Rice Disease Based on FCM-KM and Faster R-CNN Fusion' incorporates deep learning for security-relevant detection (243 citations).
Paper Timeline
Most-cited paper highlighted in red. Papers ordered chronologically.
Advanced Directions
Recent preprints are unavailable, limiting visibility into immediate frontiers. Cheng Zhou (2011) 'Overview of the Internet of Things' suggests ongoing applications in public safety and environment, but no new news coverage indicates stable focus on established IoT layers.
Papers at a Glance
| # | Paper | Year | Venue | Citations | Open Access |
|---|---|---|---|---|---|
| 1 | Chemical Engineering Kinetics | 2007 | Advances in chemical e... | 1.4K | ✕ |
| 2 | Research on the architecture of Internet of Things | 2010 | — | 612 | ✕ |
| 3 | THE REUTERS INSTITUTE FOR THE STUDY OF JOURNALISM | 2011 | Journalism Studies | 455 | ✕ |
| 4 | Cloud Computing Research and Development Trend | 2010 | — | 414 | ✕ |
| 5 | Smart Agriculture Based on Cloud Computing and IOT | 2013 | Journal of Convergence... | 296 | ✕ |
| 6 | Towards the Internet of Smart Trains: A Review on Industrial I... | 2017 | Sensors | 257 | ✓ |
| 7 | Rapid Detection of Rice Disease Based on FCM-KM and Faster R-C... | 2019 | IEEE Access | 243 | ✓ |
| 8 | Overview of the Internet of Things | 2011 | Information Security a... | 240 | ✕ |
| 9 | A Recognition Method for Rice Plant Diseases and Pests Video D... | 2020 | Sensors | 236 | ✓ |
| 10 | Investigation and assessment on mountain tunnels and geotechni... | 2009 | Science in China. Seri... | 233 | ✕ |
Frequently Asked Questions
What is the architecture of the Internet of Things?
Miao Wu et al. (2010) describe IoT architecture as a technological revolution combining features of the Internet and telecommunications networks with distinct characteristics. It extends beyond simple Internet or telecom expansions. The paper 'Research on the architecture of Internet of Things' received 612 citations.
How does cloud computing integrate with IoT in agriculture?
Fan TongKe (2013) shows cloud computing and IoT enable smart agriculture by introducing modernization to China's farming through data sharing and processing. This addresses agricultural, rural, and farmer issues. The paper 'Smart Agriculture Based on Cloud Computing and IOT' has 296 citations.
What technologies support Industrial IoT in railways?
Paula Fraga‐Lamas et al. (2017) detail the evolution of communication technologies for IIoT in railways under the Internet of Trains paradigm. This positions the railway industry to exploit IIoT opportunities. The review 'Towards the Internet of Smart Trains: A Review on Industrial IoT-Connected Railways' has 257 citations.
How is deep learning used for rice disease detection?
Guoxiong Zhou et al. (2019) propose FCM-KM and Faster R-CNN fusion for rapid rice disease detection, handling noise, blurred edges, and background interference. This improves accuracy in agricultural IoT applications. The paper 'Rapid Detection of Rice Disease Based on FCM-KM and Faster R-CNN Fusion' has 243 citations.
What are the layers in IoT systems?
Cheng Zhou (2011) outlines IoT definition and technologies for perception, network, and application layers. Applications span public safety and environment. The paper 'Overview of the Internet of Things' has 240 citations.
Open Research Questions
- ? How can data security be enhanced in Industrial IoT-connected railways beyond current communication technologies?
- ? What methods improve accuracy of deep learning models for real-time crop disease detection in noisy IoT sensor data?
- ? Which architectures best integrate cloud computing with wireless sensor networks for smart grid security?
- ? How do machine learning techniques address vulnerabilities in big data processing for IoT applications?
Recent Trends
No recent preprints or news coverage from the last 12 months is available, maintaining emphasis on established works like Miao Wu et al. with 612 citations on IoT architecture.
2010The field holds 28,248 papers with no reported five-year growth rate.
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