The field of network security and privacy is rapidly evolving, with a focus on developing innovative techniques to detect and mitigate threats. Recent research has highlighted the importance of understanding the behavior of network intermediaries, such as Deep Packet Inspection (DPI) devices, and identifying anomalies in peer-to-peer networks. Additionally, the increasing connectivity of Internet of Things (IoT) devices has expanded the attack surface, making it essential to develop proactive security strategies to protect these devices. Noteworthy papers in this area include: Fingerprinting Deep Packet Inspection Devices by Their Ambiguities, which presents a remote measurement framework to derive behavioral fingerprints for DPIs. IoTFuzzSentry: A Protocol Guided Mutation Based Fuzzer for Automatic Vulnerability Testing in Commercial IoT Devices, which demonstrates a mutation-based fuzzing tool to identify vulnerabilities in commercial IoT devices. Friend or Foe? Identifying Anomalous Peers in Moneros P2P Network, which presents a comprehensive study of anomalous behavior in Monero's P2P network and a formal framework to detect and classify anomalous patterns. Threats and Security Strategies for IoMT Infusion Pumps, which analyzes the cybersecurity vulnerabilities of IoMT infusion pumps and provides a structured understanding of the security gaps.