In supervised learning, what type of data is used to make predictions?
- Testing data
- Training data
- Unlabeled data
- Validation data
In supervised learning, 'Training data' is used to make predictions. The model learns patterns from this labeled dataset to make predictions on new, unseen data.
In wireless networking, which protocol is specifically designed to secure Wi-Fi networks?
- DNS
- TCP/IP
- WEP (Wired Equivalent Privacy)
- WPA (Wi-Fi Protected Access)
'WPA (Wi-Fi Protected Access)' is a protocol specifically designed to secure Wi-Fi networks. It provides encryption and authentication to protect the confidentiality and integrity of wireless data transmissions.
In software engineering, which process model emphasizes iterative development and the rapid construction of prototypes?
- Agile Model
- Spiral Model
- V-Model
- Waterfall Model
The 'Agile Model' emphasizes iterative development and rapid prototyping. It promotes flexibility and customer collaboration during the development process, leading to quicker and more adaptable software delivery.
In a switched network, what technique is used to prevent the broadcast storms that can be caused by switching loops?
- Internet Control Message Protocol (ICMP)
- Routing Information Protocol (RIP)
- Spanning Tree Protocol (STP)
- VLAN Trunking Protocol (VTP)
To prevent broadcast storms caused by switching loops in a network, the 'Spanning Tree Protocol (STP)' is employed. STP helps in determining a loop-free path through the switched network and blocks redundant links to prevent loops.
What is the primary goal of information assurance?
- Ensuring data accuracy
- Maximizing data size
- Protecting data
- Storing data securely
The primary goal of information assurance is 'protecting data.' Information assurance focuses on safeguarding the confidentiality, integrity, and availability of data and information assets.
What is a key component of IT governance that ensures risks associated with IT investments are identified and managed?
- Cryptocurrency
- Data Loss Prevention (DLP)
- IT Portfolio Management
- IT Service Management
'IT Portfolio Management' is a critical component of IT governance that focuses on identifying and managing risks associated with IT investments. It involves assessing the value, risk, and performance of IT projects and assets to make informed decisions about resource allocation.
Which advanced threat in network security involves a cyber attacker establishing a foothold within a network and then moving laterally to access more resources?
- APT (Advanced Persistent Threat)
- DoS (Denial of Service)
- Phishing Attack
- Ransomware
An "APT" (Advanced Persistent Threat) is a complex and prolonged cyberattack where an attacker gains initial access to a network and then stealthily moves laterally to maintain a persistent presence and access more resources.
What is the main difference between a cloud-based "load balancer" and a "traffic manager"?
- Load balancers distribute network traffic across multiple servers.
- Load balancers route traffic based on geographical locations.
- Traffic managers monitor the quality of network traffic.
- Traffic managers provide cybersecurity for cloud-based services.
The main difference is that 'load balancers' distribute incoming network traffic across multiple servers to ensure high availability and optimal resource utilization. 'Traffic managers' typically focus on routing traffic efficiently based on various factors but may not necessarily distribute load.
Which cryptographic scheme provides both authentication and secrecy for a message using block ciphers?
- AES-GCM
- Diffie-Hellman Key Exchange
- HMAC (Hash-based Message Authentication Code)
- RSA
AES-GCM (Advanced Encryption Standard-Galois/Counter Mode) is a cryptographic scheme that combines block cipher (AES) with a mode of operation (GCM) to provide both authentication and secrecy for a message. It ensures the message's confidentiality and verifies its authenticity.
In the context of convolutional neural networks (CNNs), what operation is used to reduce the spatial dimensions of the input volume?
- Batch Normalization
- Normalization
- Pooling
- Weight Initialization
In CNNs, 'pooling' is used to reduce the spatial dimensions of the input volume. Pooling layers downsample the feature maps, which helps in reducing computational complexity while retaining essential information, enabling the network to focus on important features.