IOT, Edge Computing, Cybersecurity and Privacy Flashcards
refers to a network of
interconnected devices that communicate and exchange
data over the internet.
Internet of Things (IoT)
data is sent to remote servers (data
centers) for processing.
cloud computing
processes data locally, either on the device itself or on
a nearby edge server, reducing the need to send data to the cloud.
Edge computing
focuses on safeguarding networks,
devices, and data from malicious attacks, unauthorized
access, and other vulnerabilities.
Cybersecurity
ensures that
individuals’ personal data is protected and not misused.
Privacy
Devices that collect data from the physical
environment (e.g., temperature, humidity, motion sensors).
Sensors and Actuators
Communication protocols like Wi-Fi, Bluetooth, Zigbee, or
5G that connect devices to networks or the internet.
Connectivity
Devices send data to centralized systems or the cloud
for analysis.
Data Processing
Software applications that allow users to interact with IoT
systems and make decisions.
User Interfaces
IoT enables devices like thermostats, lighting, security cameras, and
appliances to be interconnected, making homes more energy-efficient and secure.
Smart Homes
IoT facilitates remote patient monitoring through wearables that
track vital signs and send alerts in real-time to healthcare providers.
Healthcare
Factories and industries use sensors to monitor equipment performance,
predict maintenance needs, and optimize production, leading to increased efficiency and
reduced downtime.
Industrial IoT (IIoT)
IoT contributes to the development of smart cities by connecting traffic lights,
waste management systems, and public utilities, resulting in optimized resource use and
better public services.
Smart Cities
In autonomous vehicles, edge computing is
crucial for processing sensor data in real-time to make immediate driving
decisions, such as obstacle detection and route planning.
Real-Time Decision Making
Smart manufacturing systems use edge computing to
instantly detect machine malfunctions and adjust production lines in real-
time, minimizing downtime.
Reduced Latency
Edge computing reduces the amount of data sent
to cloud servers, which is particularly important for IoT devices that
generate massive amounts of data, such as security cameras, drones, and
smart meters.
Bandwidth Optimization
Malicious software like viruses, worms, ransomware, and spyware
that damage systems or steal information.
Malware
Fraudulent attempts to obtain sensitive information (e.g.,
passwords, credit card numbers) by disguising as trustworthy entities via
email or websites.
Phishing
Attacks that flood a network with traffic,
overwhelming it and causing a shutdown of services.
Denial of Service (DoS/DDoS)
Interception of communication between two
parties to eavesdrop or alter information being exchanged.
Man-in-the-Middle (MITM)
Data is encrypted both at rest and in transit to protect it from unauthorized
access. Modern encryption protocols, such as AES (Advanced Encryption Standard), ensure
that sensitive information like financial records and healthcare data remains secure.
Encryption
adds an extra layer of security beyond just
passwords, requiring users to verify their identity through additional means (e.g., biometrics,
SMS codes).
Multi-Factor Authentication (MFA)
monitor incoming and outgoing network traffic and block potentially
harmful data packets. They are a fundamental line of defense in preventing unauthorized
access to systems.
Firewalls
In this approach, no user or device is automatically trusted, whether
inside or outside the organization. Access is granted based on strict verification, reducing the
risk of insider threats or compromised accounts.
Zero Trust Architecture
Companies often collect vast amounts of user data, which
can include personal details, location information, and online activity. This
raises concerns about how data is used and shared.
Data Collection
Third-party sharing of user data without consent is a significant
privacy issue, particularly in industries like advertising, where personal
information is sold for targeted marketing.
Data Sharing
Unauthorized access to sensitive data can result in identity
theft, financial fraud, and other serious consequences for individuals.
Data Breaches
Only collecting the data that is necessary for a specific purpose,
reducing the risk of exposure and misuse.
Data Minimization
Techniques such as data anonymization remove or mask
personally identifiable information (PII) so that individuals cannot be traced back
through the data.
Anonymization
Legislation like the GDPR (General Data Protection
Regulation) in the EU and CCPA (California Consumer Privacy Act) in the US sets
strict guidelines for how organizations can collect, process, and store user data,
ensuring that individuals’ privacy rights are respected.
Compliance with Regulations
Implementing transparent mechanisms for user consent, giving
individuals control over their data and how it is used.
User Consent
Ensuring that data is encrypted at the edge
before it is transmitted to other devices or the cloud.
Encryption at the Edge
Ensuring that only authorized devices can connect to
the IoT network to prevent spoofing or unauthorized access.
Authentication
Edge computing can enable faster
detection and mitigation of cyberattacks on IoT devices, as
processing happens locally, reducing latency.
Real-Time Threat Detection
