A Diameter firewall is essential for mobile operators to protect their subscribers, as Diameter networks lack end-to-end authentication and heavily rely on trust among partner operators. Among the various attacks exploiting the Diameter protocol, one notable example involves falsely updating a subscriber's location and illegitimately requesting authentication data. Conventional methods, known as velocity checks, validate the originating network of messages by assessing the plausibility of subscriber movement based solely on network-provided information. However, attackers can still bypass these checks by simulating their presence in nearby or bordering countries. This poster introduces a user-interactive Diameter firewall, which incorporates user engagement by allowing subscribers to confirm suspicious requests.

In cellular networks, authorities may need to physically locate user devices to track criminals or illegal equipment. This process involves authorized agents tracing devices by monitoring uplink signals with cellular operator assistance. However, tracking uncooperative uplink signal sources remains challenging, even for operators and authorities. Three key challenges persist for fine-grained localization: i) devices must generate sufficient, consistent uplink traffic over time, ii) target devices may transmit uplink signals at very low power, and iii) signals from cellular repeaters may hinder localization of the target device. While these challenges pose significant practical obstacles to localization, they have been largely overlooked in existing research.

LTE sniffers are important for security and performance analysis because they can passively capture the wireless traffic of users in LTE network. However, existing open-source LTE sniffers have only limited functionality and cannot decode data traffic. This paper introduces LTESNIFFER, the first open-source LTE sniffer that can passively decode both uplink and downlink data traffic. Implementing a sniffer is not trivial because one needs to understand detailed configurations and parameters to successfully decode each user's traffic. Using multiple techniques, we found mechanisms to understand these, which improves our decoding performance. We evaluated the performance of LTESNIFFER on both testbed and commercial network environments. We also compare the performance of LTESNIFFER with AirScope, a popular commercial LTE sniffer. Additionally, LTESNIFFER provides a proof-of-concept API with three functions that can be used for security applications, including identity mapping, identity collecting, and device capability profiling. We release LTESNIFFER as open-source for future research.

The recent emerging concept in the networking world is known as SDN (Software-Defined Network). SDN architecture introduced the new methods of network management and configuration. It makes underlying networking devices as simply just packet forwarding units and leaving the control logic on centralized software program to dictate the entire network behavior. In logically centralized SDN architecture the switches are statically assigned to controllers regardless of actual load of individual controllers. One of the key concern of network operators is to efficiently monitor the actual load of individual controllers in a logically centralized SDN environment. In this paper, we propose an adaptive solution to monitor the actual load of a SDN controller for efficient utilization in a logically centralized SDN architecture. We proposed a load monitoring solution which is combination of ONOS (Open Network Operating System) based collection manager and collectd based “onos write” plugin/module that act as an agent on SDN controllers. Our proposed solution helps to overcome the under-utilization and over-utilization of a controller implemented in logically centralized SDN environment. The results show that our proposed monitoring system gives a comprehensive statistical view of individual controller's load.

Caching similar videos transparently in a network is a cost-effective solution that potentially reduces redundant data transfers. Recent study shows that network redundancy elimination (NRE) on the content level could produce high bandwidth savings in ISPs. However, we find that blindly employing existing NRE techniques to video contents could lead to suboptimal redundancy suppression rates. This is because (a) randomness in the video encoding process could produce completely different binaries even when they deal with seemingly identical video clips and (b) existing NRE chunking schemes incur high overheads since they do not utilize the underlying video format.