The concept of ________ allowed devices to collect and exchange data, leading to the birth of IoT.
- "Data Networking"
- "Internet of People"
- "Internet of Things"
- "Machine Learning"
The concept of the "Internet of Things" (IoT) allowed devices to collect and exchange data. IoT refers to the network of interconnected devices that communicate and share data, enabling various applications and automation. It has revolutionized industries by connecting physical objects to the internet, leading to greater efficiency and convenience.
When discussing privacy in IoT, the primary concern revolves around:
- Data ownership and consent
- Device compatibility
- Hardware specifications
- Network speed and latency
Privacy in IoT is primarily concerned with data ownership and consent. IoT devices collect a wide range of personal and sensitive data, and it's essential to address who owns this data, how it's used, and obtaining consent from users for data collection and processing.
The convergence of Big Data and IoT has led to the emergence of which computing paradigm?
- Cloud Computing
- Edge Computing
- Fog Computing
- Quantum Computing
The convergence of Big Data and IoT has given rise to "Fog Computing." Fog Computing extends cloud computing capabilities to the edge of the network, closer to where data is generated, thus enabling faster processing and real-time decision-making in IoT systems.
A company is deploying thousands of IoT sensors in an agricultural field to monitor soil moisture, weather conditions, and crop growth. They need to store this data and analyze it for patterns to predict the best harvest times. Their primary concern is the velocity of incoming data. What should be their main focus?
- Data Analytics
- Data Ingestion Speed
- Data Security
- Data Storage Capacity
In this scenario, where thousands of IoT sensors generate data in real-time, the primary concern should be the velocity of incoming data. Data ingestion speed is crucial to ensure that data is collected and analyzed in a timely manner to make accurate predictions about the best harvest times.
In the context of IoT, why is predictive analytics important?
- To achieve real-time data visualization
- To enhance physical device durability
- To proactively identify issues and optimize performance
- To transmit data to the cloud for storage
Predictive analytics in the context of IoT is essential because it allows organizations to proactively identify issues and optimize the performance of IoT devices and systems. By analyzing historical data and patterns, predictive analytics can help prevent problems before they occur, leading to more efficient operations.
________ keys are cryptographic keys that can be used for both encryption and decryption in symmetric cryptography, commonly used in IoT devices.
- Private
- Public
- Session
- Shared
Shared keys, often referred to as symmetric keys, are used in symmetric cryptography. These keys are shared between the sender and receiver, allowing them to both encrypt and decrypt data, making them a common choice for IoT devices.
A company's smart thermostat was remotely accessed and its settings were maliciously changed. This is an example of:
- Cyber Attack
- Cybersecurity Vulnerability
- Data Breach
- Unauthorized Access
This scenario represents a Cyber Attack where a malicious entity remotely accessed the thermostat to make unauthorized changes. It's a clear instance of a deliberate attack rather than just an unauthorized access or a vulnerability.
One of the best practices for IoT device provisioning is ensuring devices have unique ________ to prevent cloning.
- "Device Names"
- "Firmware Versions"
- "MAC Addresses"
- "Serial Numbers"
One of the best practices for IoT device provisioning is ensuring devices have unique "Serial Numbers" to prevent cloning. Each IoT device should have a distinct serial number to prevent unauthorized duplication or replication of devices, which can help maintain the integrity and security of the IoT ecosystem.
An IoT device that is susceptible to a man-in-the-middle attack is lacking in:
- Encryption
- Identity Verification
- Secure Communication Protocols
- Strong Authentication
When an IoT device lacks secure communication protocols, it becomes vulnerable to man-in-the-middle attacks, where an attacker intercepts and potentially alters the communication between two parties. Strong authentication, encryption, and identity verification are important, but without secure communication, these measures can be compromised.
In an agricultural setup, a farmer wants to monitor the soil moisture, temperature, and pest activity across large fields. The most suitable technology to deploy would be:
- Bluetooth Technology
- Drones
- Satellite Imagery
- Wireless Sensor Networks
Wireless Sensor Networks are the most suitable technology for monitoring soil conditions and pest activity across large fields. They offer a cost-effective and efficient way to collect data from various points in the field. Satellite imagery, drones, and Bluetooth technology have their uses in agriculture but may not be as suitable for this specific purpose.