Juniper Updated JN0-335 Exam Questions and Answers by rhea

Statistical sampling is a technique that reduces the amount of flow data that is sent to JSA by sampling a subset of packets from the network device. Statistical sampling can help reduce network bandwidth and storage requirements, but it also increases processor utilization on the network device and decreases event correlation accuracy on JSA. Statistical sampling can also affect the accuracy of reports and searches that are based on flow data. Therefore, it is recommended to use statistical sampling only when necessary and with caution12.

BGP FlowSpec is not used to collect traffic flows from Junos OS devices, but to distribute firewall filter rules to routers that participate in BGP. BGP FlowSpec can help mitigate distributed denial-of-service (DDoS) attacks by filtering unwanted traffic based on flow attributes such as source and destination IP addresses, ports, and protocols3.

Superflows are not a method of collecting network traffic flows, but a way of grouping individual flows that match certain criteria into a single record. Superflows can help detect common attack vectors and reduce the number of flows that are stored on JSA. Superflows do not reduce traffic licensing requirements, but they can help optimize the performance and storage of JSA4. References:

• 1: Flow Sources | JSA 7.5.0 | Juniper Networks
• 2: JSA Events and Flows | JSA 7.5.0 | Juniper Networks
• 3: Understanding BGP FlowSpec
• 4: Superflows | JSA 7.5.0 | Juniper Networks

AppFW and APPID are two application security features that can be used to block malicious applications regardless of the port number being used. AppFW provides policy-based enforcement and control on traffic based on application signatures. By using AppFW, you can block any application traffic not sanctioned by the enterprise. APPID identifies applications based on their behavior and characteristics, regardless of port, protocol, or encryption method. By using APPID, you can classify applications and apply appropriate security policies to them123 References:

• AppSecure: Application Visibility and Control Solution Brief
• Application Firewall | Junos OS | Juniper Networks
• Security Policy Applications and Application Sets | Junos OS | Juniper Networks

Encrypted Traffic Insights is a feature of Juniper ATP Cloud and SRX Series firewalls that can detect malicious threats that are hidden in encrypted traffic without intercepting and decrypting the traffic. It permits organizations greater visibility and policy control over encrypted traffic, without requiring resource-intensive SSL Decryption1.

Encrypted Traffic Insights assesses the threat of the traffic by using two methods:

• It validates the certificates used by the external servers that the internal hosts are trying to connect to. It compares the certificate signatures with a blocklist of known malicious certificates and also checks the certificate validity, issuer, and subject. If the certificate is invalid or matches a malicious signature, the connection is blocked or alerted2.
• It reviews the timing and frequency of the connections to the external servers. It uses behavior analysis and machine learning to identify patterns and anomalies that indicate malicious activity, such as command and control (C&C) communications, botnet traffic, or data exfiltration. It also uses threat intelligence feeds to enrich the analysis and provide additional context2.

Encrypted Traffic Insights does not decrypt the file or the data in a sandbox or to validate the hash, as these methods would require breaking the encryption of the traffic, which would violate data privacy laws and introduce latency and performance issues21. References:

• 3: SRX5400, SRX5600, SRX5800 Firewalls Datasheet - Juniper Networks
• 2: Encrypted Traffic Insights Overview and Benefits | ATP Cloud | Juniper …
• 1: Juniper Networks Expands Connected Security Portfolio with Encrypted …

In a Juniper Networks chassis clustering setup, when you enable chassis clustering on two devices and assign a cluster ID and a node ID to each device, the correct order for rebooting the devices is: C. Reboot the primary device, then the secondary device. Explanation: After assigning the cluster ID and node ID to each device, it is a good practice to reboot the primary device first. This ensures that the primary device comes online with the specified cluster and node IDs. Once the primary device is up and running, you can then reboot the secondary device. The secondary device will recognize the existing cluster and node IDs assigned to the primary device and join the cluster accordingly.