DDoS Protection
Distributed denial-of-service (DDoS) protection solutions detect and mitigate attacks that flood a network, service, or application with excessive traffic. These attacks can overwhelm infrastructure, degrade performance, and cause service outages.
Modern DDoS protection tools use a combination of traffic analysis, rate limiting, and filtering to block malicious requests while allowing legitimate traffic to pass through. Many services are cloud-based and provide always-on or on-demand protection, scaling dynamically to absorb large-scale attacks.
Advanced solutions offer real-time analytics, automated threat response, and integration with threat intelligence feeds. Some also include scrubbing centers that clean traffic before forwarding it to the target network, reducing the attack's impact.
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Bot Management
Bot management solutions are designed to detect, block, and mitigate malicious bots that attempt to access web applications, APIs, or other digital services. Bots can be used for various malicious activities, including credential stuffing, web scraping, and denial-of-service attacks, all of which can disrupt business operations and compromise sensitive data.
Modern bot management platforms use advanced techniques like behavioral analysis, machine learning, and challenge-response tests to differentiate between human users and automated bots. These solutions can enforce rate limits, implement CAPTCHAs, and block traffic from known botnets, effectively protecting applications and services from automated threats.
A critical component of bot management is the ability to identify sophisticated bots that mimic human behavior to bypass traditional defenses. Solutions often integrate with threat intelligence feeds and leverage device fingerprinting and IP reputation analysis to enhance detection accuracy. By deploying a comprehensive bot management strategy, organizations can reduce fraud, protect user data, and maintain the integrity of their online services.
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Endpoint Detection and Response (EDR)
EDR is a security solutions category created by Gartner in 2013. Its goal is to enable security teams to detect breaches on endpoint devices and immediately intervene to contain and eradicate the threat. Thus, EDR is complementary to NGAV and preventive endpoint protection solutions.
Without EDR, security teams have very limited visibility into what is happening on endpoint devices. EDR lets them detect security incidents, provides the data needed for rapid forensic investigation, and also allows them to respond to an incident, for example, by isolating the endpoint from the network, or wiping and reimaging it.
According to the Gartner definition, an EDR solution has three components:
- Data collection: An agent running on endpoints which collects data about network activity, running processes, and user activity.
- Detection engine: A system that analyzes data from an endpoint and reports anomalies and suspicious activity to security teams.
- Analysis engine: A system that integrates data from endpoints with other data sources, including threat intelligence feeds, enriching the data to identify security incidents.
Extended Detection and Response (XDR)
XDR tools automatically collect information from several security layers and correlate it to facilitate rapid threat identification. The technology can track threats across multiple sources within an organization to extend visibility and response across the entire ecosystem, including servers, endpoints, email systems, application workloads, and cloud environments.
XDR technology connects individual security datasets to provide a unified attack view across the entire environment. It helps prevent threats from hiding between security silos due to a lack of integration between different security tools. XDR can also help improve productivity, providing security teams with a centralized platform for threat investigation and remediation.
UEBA
User and Entity Behavior Analytics (UEBA) is a cybersecurity solution that uses machine learning to identify abnormal behavior that could indicate a potential security threat. UEBA tools analyze data about user behavior and other entities (such as devices and applications) to identify anomalies that deviate from established patterns.
UEBA is particularly effective at detecting insider threats. While other security solutions focus on external threats, UEBA is designed to identify potentially harmful actions taken by legitimate users within an organization. This capability is crucial in helping organizations protect their sensitive data from insider threats.
The strength of UEBA lies not just in its ability to detect threats, but also in its ability to provide context about these threats. By analyzing behavior patterns, UEBA can provide insights into the motives and methods of an attacker, helping organizations to understand and prevent similar attacks in the future.
Learn more in the detailed guide to UEBA.
Related product offering: Exabeam | AI-Driven Security Operations
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Managed Detection and Response (MDR)
MDR services leverage advanced tools and expert security personnel to provide threat monitoring, hunting, and response. Organizations can outsource their detection and response responsibilities to MDR services that have the resources to identify threats and quickly minimize the scope of attacks.
MDR services leverage advanced analytics and threat intelligence to remotely monitor, detect, and respond to threats. It typically involves deploying EDR technology to achieve visibility and push alerts to relevant parties. These tools collect forensic data, helping security analysts triage alerts to determine the appropriate response.
Cloud Backups
Cloud backups involve storing copies of data and applications on remote servers, often managed by third-party providers. This ensures data availability and protection in case of hardware failure, cyberattacks, or natural disasters. Unlike traditional backups, cloud backups offer greater scalability and flexibility, enabling organizations to easily adjust storage capacity as their needs grow.
Cloud backups have critical security benefits. They are an effective protection against ransomware attacks, in which attackers encrypt sensitive data, making it inaccessible to its owners, and demand a ransom to release it.
Learn more in the detailed guides to:
Related product offering: N2WS | Cloud Backup and Restore
Related technology update: [Tool] AWS Cost Saving Calculator
Web Application Protection
Web application protection focuses on securing web-based applications from a variety of threats, such as cross-site scripting (XSS), SQL injection, and denial-of-service attacks. Modern web applications are highly interactive and dynamic, making them attractive targets for attackers who exploit vulnerabilities in application code or underlying frameworks.
To protect web applications, organizations deploy a combination of security measures, including web application firewalls (WAFs) and secure development practices. WAFs inspect incoming traffic for known attack patterns. Developers can enhance web application security by adopting secure coding standards, conducting regular code reviews, and integrating security testing into the software development lifecycle.
Effective web application protection also involves continuous monitoring and real-time threat intelligence to quickly identify and respond to emerging threats. By integrating web application security with other defense mechanisms—such as DDoS protection and API security—organizations can build a comprehensive security posture that reduces risk across the entire application stack.
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Next-Generation Antivirus (NGAV)
NGAV technology employs machine learning and behavioral analysis to detect today’s sophisticated threats. It goes beyond traditional signature-based detection, providing functionality that helps detect and respond to unknown threats. Most NGAV solutions offer cloud-based deployment that enables organizations to leverage the technology quickly.
Network Firewall
A network firewall mediates communication between internal and external devices, blocking or mitigating unauthorized access to the network. It is a security device that sits in front of the network and uses policies to allow or deny traffic into the network. It protects private networks from traffic flowing from the public Internet or across intranet networks.
Organizations can configure their network firewall to control all traffic passing through, examining all incoming messages and rejecting any that do not meet predefined policies. However, it needs proper configuration to ensure it blocks only threats, like worms and malware, while allowing users access to the resources they require to perform their job.
VPN
A Virtual Private Network (VPN) is a technology that creates a secure connection over a less-secure network, such as the Internet. It encrypts data and provides anonymity to users by masking their IP address and location. This makes it harder for cybercriminals to track online activities and steal data.
VPNs are widely used by individuals and businesses to protect sensitive data, especially when using public Wi-Fi networks, which are often unsecured and vulnerable to cyberattacks.
Learn more in the detailed guide to VPN.
Intrusion Prevention System (IPS)
An IPS examines network traffic to detect and prevent the exploitation of vulnerabilities. This technology has evolved from intrusion detection systems (IDS) that passively scan traffic to report detected threats.
IPS sits inline, placed within the direct communication path between the source and the destination, and actively analyzes traffic attempting to access the network. IPS is a proactive layer of analysis that can take automated actions on traffic and detect or prevent malicious activity.
Vulnerability Scanning
Vulnerability scanning tools provide automated identification of potentially exploitable vulnerabilities in applications. These tools use data on publicly disclosed vulnerabilities, and check the application against a list of previously identified signatures.
Learn more in the detailed guide to vulnerability scanners.
Network Monitoring
Network monitoring offers continuous visibility into a computer network, checking for internal issues such as server or component failures, slow traffic, overloaded routers, and various network connection issues. Unlike IPS technology, network monitoring tools do not check for intrusion.
Network monitoring solutions continuously monitor the network and automatically notify administrators when detecting network issues, typically via email or text. These solutions can also initiate failover to remove problem circuits or devices before remediation. Proactive tools can identify anomalies indicating potential outages to prevent failure or downtime before it occurs.
Security Information and Event Management (SIEM)
SIEM solutions aggregate, analyze, and correlate security event data from across an organization’s IT infrastructure. They help security teams detect threats, investigate incidents, and ensure compliance with regulatory requirements.
A SIEM system typically collects logs from various sources, such as firewalls, servers, endpoint devices, and network appliances. It then applies real-time analytics and correlation rules to identify patterns that may indicate a security threat. Many SIEM platforms incorporate artificial intelligence and machine learning to improve detection capabilities and reduce false positives.
Beyond detection, SIEM systems provide incident response tools, allowing security teams to investigate threats and take action. Some SIEM solutions also integrate with other security tools, such as EDR and XDR, to provide more comprehensive protection and faster remediation.
Learn more in the detailed guide to SIEM security
Brand Protection
Brand protection refers to strategies and technologies used to safeguard a company’s brand and reputation from various cyberthreats. It involves monitoring and addressing activities that could harm the brand, such as phishing attacks, trademark infringement, counterfeiting, and fraudulent websites.
To implement an effective brand protection strategy, organizations should first identify which brand assets are most critical, such as logos, trademarks, and domain names. The priority is protecting these assets across all digital channels. Advanced technologies like AI and machine learning can detect anomalies and potential threats in real time, while automated monitoring and response systems can quickly address brand abuse incidents.
By implementing a comprehensive brand protection strategy, organizations can protect their reputation, maintain customer trust, and prevent financial losses caused by cyberthreats.