IA 2 - UNIT 1 and 5 Flashcards
refers to extremely large and complex datasets that are difficult to process and analyze using traditional data processing tools and techniques.
Big Data
Key Characteristics of Big Data
- volume
- velocity
- veracity
- variety
- value
Refers to the massive amount of data generated every second from various sources, such as social media, sensors, transactions, and machines. Big data involves handling datasets that range from terabytes to petabytes and beyond
Volume
Describes the speed at which data is generated and processed. With big data, information is produced rapidly and continuously, requiring real-time or near-real-time processing to derive actionable insights.
Velocity
Refers to the diversity of data types, including structured (like databases), unstructured (like text, images, or video), and semi-
structured data (such as JSON or XML files). Big data involves dealing with this variety of formats from different sources.
Variety
Refers to the uncertainty or quality of the data, as big data can sometimes be incomplete, inaccurate, or inconsistent.
Veracity
Highlights the importance of extracting meaningful and valuable insights from big data.
Value
- The vast array of physical objects equipped with sensors and software that enable them to interact with little human intervention by collecting and exchanging data via a network.
- includes the many “smart,” computer-like devices so commonplace today, which can connect with the Internet or interact via wireless networks
iot
Benefits of IoT in the Society
- improved efficiency
- better health outcomes
- environmental benefits
- enhanced convinience
- enhanced safety and security
- new business opportunities
What impact will IoT have in
the economy
- job creation
- new business models
- cost savings
- increased productivity
- improved customer experience
- new revenue streams
Data Security in
IoT
- Device Authentication and Authorization
- Data Encryption
- Secure Firmware and Software Updates
- Network Security
- data integrity and verification
- privacy protection
- resilience and redundancy
- user education and awareness
One of the first steps to secure IoT systems is to make
sure only approved devices and users can connect to
the network. Using strong ways to verify identities, like
multi-factor authentication and unique device IDs,
helps block unauthorized access.
Device Authentication and Authorization
crucial for protecting information both while it is being sent and when it is stored. IoT devices often send sensitive data, and encrypting this data makes sure that even if someone intercepts it, they cannot read it.
data enctyption
Regular updates are essential for keeping IoT devices secure. However, updates can be risky if not done safely. Using secure update methods, like digitally signed firmware and over-the-air (OTA) updates, ensures that only approved updates are installed, protecting devices from harmful software.
Secure Firmware
and Software
Updates
IoT devices are usually part of larger networks, so
keeping the network secure is crucial for overall IoT
security. Using firewalls, intrusion detection systems
(IDS), and intrusion prevention systems (IPS) helps
monitor and protect the network from threats.
Network Security
Making sure the data collected and sent by IoT devices
is accurate and unchanged is very important. Using
techniques like cryptographic hashing can verify that
data hasn’t been altered.
Data Integrity
and Verification
IoT devices often collect a lot of personal data, so
protecting privacy is very important. Companies must
follow data privacy laws like GDPR or CCPA and only
collect necessary data.
Privacy Protection
IoT systems should be built to handle failures and
attacks. Creating resilience through backups and
failover systems ensures that important services keep
running even during security issues.
Resilience and
Redundancy
Teaching users about IoT security and safe practices is
crucial. Users need to know the risks and how to set
up and use their devices securely.
User Education
and Awareness
12 common iot security concerns
- Poor vulnerability testing
- Unpatched vulnerabilities
- Default passwords and weak authentication
- Outdated firmware and software
- Poor device management and visibility
- Limited security integration
- Legacy assets
- Remote work
- Overwhelming data volume
- Data privacy concerns
- Complex Environments
- APIs as entry points for attacks
Examples of
IoT Hacking and
Vulnerabilities
- The Mirai Botnet (aka Dyn Attack)
- The Hackable Cardiac Devices from St. Jude
- The Owlet WiFi Baby Heart Monitor Vulnerabilities
- The TRENDnet Webcam Hack
- The Jeep Hack
Implementing
IoT Security in
3 Steps
- DEVICE DISCOVERY
- RISK ANALYSIS
- MONITOR, PROTECT, ENFORCE
The first step in securing IoT is identifying the devices connected to your network, which typically uses a device identification and discovery tool to automate three critical IoT security functions:
DEVICE DISCOVERY
Once all IoT devices are identified, the next step is to conduct a thorough risk analysis, which assesses the vulnerabilities and potential threats associated with each device and its communication channels.
RISK ANALYSIS
The final step involves actively monitoring the IoT environment, applying protective measures, and enforcing security policies to maintain a secure posture over time
MONITOR, PROTECT, ENFORCE
