A subnet mask is a 32-bit number that defines the network portion and host portion of an IP address. It helps in dividing a large network into smaller subnetworks. How does it work, and what are the different classes of ...
Several AI technologies significantly enhance cybersecurity measures in the IT industry: Machine Learning (ML): ML algorithms analyze patterns and detect anomalies, improving threat detection and response times. They can identify malicious activities by learning from historical data. Natural LanguagRead more
Several AI technologies significantly enhance cybersecurity measures in the IT industry:
- Machine Learning (ML): ML algorithms analyze patterns and detect anomalies, improving threat detection and response times. They can identify malicious activities by learning from historical data.
- Natural Language Processing (NLP): NLP helps in analyzing vast amounts of unstructured data, such as logs and alerts, to identify potential threats and streamline threat intelligence.
- Behavioral Analytics: AI analyzes user behavior to detect unusual activities that may indicate insider threats or compromised accounts.
- Automated Threat Hunting: AI automates the process of threat hunting, continuously scanning for signs of breaches or vulnerabilities, allowing security teams to focus on critical issues.
- Predictive Analytics: AI predicts potential threats by analyzing trends and historical data, enabling proactive measures against emerging threats.
- AI-powered Security Information and Event Management (SIEM): Integrates AI to enhance the correlation and analysis of security events, providing real-time insights and automated responses.
- Deep Learning: Advanced neural networks can identify complex patterns and relationships within data, improving the accuracy of threat detection.
- User and Entity Behavior Analytics (UEBA): Uses AI to monitor and analyze behaviors of users and entities, detecting deviations that may indicate security breaches.
These technologies bolster defenses, enhance threat detection, and streamline response efforts in cybersecurity.
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A subnet mask is a number used in computer networking to divide an IP address into two parts: the network portion and the host portion. It helps devices determine which part of the IP address identifies the network and which part identifies a specific device (or host) on that network. An IP addressRead more
A subnet mask is a number used in computer networking to divide an IP address into two parts: the network portion and the host portion. It helps devices determine which part of the IP address identifies the network and which part identifies a specific device (or host) on that network.
An IP address consists of four numbers separated by dots (like 192.168.1.1), and each number can range from 0 to 255. The subnet mask is also written in the same format (like 255.255.255.0) and works alongside the IP address to define the network.
For example, if an IP address is 192.168.1.10 and the subnet mask is 255.255.255.0, the first three numbers (192.168.1) represent the network, while the last number (10) identifies the specific device within that network.
Subnet masks help improve network performance and security by allowing the division of larger networks into smaller, manageable ones. This way, network traffic can be efficiently routed, and it’s easier to manage different groups of devices. Understanding subnet masks is essential for anyone working with networks, as they play a crucial role in organizing and managing IP addresses.
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