Anti-TTL (aa 355-385) polyclonal antibody

The Interplanetary Network (IPN) or the Interplanetary Internet is a network composed of interconnected space objects, which are in turn connected to mission control stations on the surface of Earth. The IPN is our only portal to the deep space, and yet it has been relatively sparse, until recently. With the ongoing and the planned missions to the outer space, the Delay Tolerant Networking (DTN) based network infrastructure will require more scalable routing and scheduling algorithms. In this paper, we propose the first Mixed Integer Linear Programming (MILP) model for message routing and scheduling in the IPN using Multi-Attribute Decision Making (MADM) principles. Based on this model, we propose a novel MADM-based algorithm called Multi-Attribute Routing and Scheduling (MARS) algorithm. This algorithm uses a sliding window of size n to schedule the first n messages in the buffer based on multiple attributes. After finding the optimal schedule for these messages (in terms of delivery rate), they are routed using our proposed Dijkstra-based routing algorithm. We use an existing MADM technique, PROMETHEE II, and consider the four main attributes of a message: size, priority, time to live (TTL), and time in buffer (TiB). Finally, we run multiple simulation experiments in order to test the performance of the proposed MARS and show that MADM coupled with scheduling and routing in IPN delivers at least three times more messages than a previously proposed technique, the Contact Graph Routing (CGR), while significantly reducing the average end-to-end delay and overhead.

A major disturbance for network providers in recent years have Distributed Reflective Denial-of-Service (DRDoS) attacks. In such an attack, the adversary spoofs the IP address of a victim and sends a flood of tiny packets to vulnerable services. The services then respond to spoofed the IP, flooding the victim with large replies. Led by the idea that an attacker cannot fabricate the number of hops a packet travels between amplifier and victim, Hop Count Filtering (HCF) mechanisms that analyze the Time-to-Live (TTL) of incoming packets have been proposed as a solution. In this paper, we evaluate the feasibility of using HCF to mitigate DRDoS attacks. To that end, we detail how a server can use active probing to learn TTLs of alleged packet senders. Based on data sets of benign and spoofed NTP requests, we find that a TTL-based defense could block over 75% of spoofed traffic, while allowing 85% of benign traffic to pass. To achieve this performance, however, such an approach must allow for a tolerance of +/- 2 hops. Motivated by this, we investigate the tacit assumption that an attacker cannot learn the correct TTL value. By using a combination of tracerouting and BGP data, we build statistical models which allow to estimate the TTL within that tolerance level. We observe that by wisely choosing the used amplifiers, the attacker is able to circumvent such TTL-based defenses. Finally, we argue that any (current or future) defensive system based on TTL values can be bypassed in a similar fashion, and find that future research must be steered towards more fundamental solutions to thwart any kind of IP spoofing attacks.