Recently voice over IP (VoIP) is experiencing a phenomenal growth. Being a real-time service, VoIP is more susceptible to denial-of-service (DoS) attacks than regular Internet services. Moreover, VoIP uses multiple protocols for call control and data delivery, making it vulnerable to various DoS attacks at different protocol layers. An attacker can easily disrupt VoIP services by flooding TCP SYN packets, UDP-based RTP packets, or SIP-based INVITE messages, which pose a critical threat to IP telephony. In this paper, we present an online statistical detection mechanism, called vFDS, to detect DoS attacks in the context of VoIP. The core of vFDS is based on Hellinger distance method, which computes the variability between two probability measures. Using Hellinger distance, we characterize normal protocol behaviors and then detect the traffic anomalies caused by flooding attacks. Our experimental results show that vFDS achieves fast and accurate detection of DoS attacks

Automatic Dependent Surveillance Broadcast (ADS- B) is one the most prominent air traffic surveillance technologies that emerged in recent years. It can be used not only as a complement to existing radar-based technologies to locate air- craft, but also as a replacement in areas without radar coverage. However, a major flaw in the deployment of this technology is its reliance on clear-text, open broadcast of messages, which makes it vulnerable to attackers. In this paper, we propose ADS-Bsec, a holistic framework that solves the root cause of ADS-B problems by enforcing the much needed authenticity and integrity in ADS- B messages. It does so without changing the message format, and along with a proper key exchange mechanism. In addition, our framework also leverages results from radio-location and risk- adaptive techniques in order to prevent attacks targeting ADS- B. An important characteristic of our framework is that it was mostly implemented using a test bed with actual prototype radios, which mimics as much as possible real flight conditions. As a result, our framework is a promising approach for integrating ADS-B to NextGen infrastructure in a secure and affordable fashion.