Tactical communication environments are characterized by frequent disruptions, intermittent connectivity, and low bandwidth (DIL) due to the unfavorable, unfriendly, and sometimes very dynamic network conditions. Nevertheless, there is still an expectation that tactical applications can communicate seamlessly despite the challenging communication environment. In this paper, we propose and evaluate the use of Named Data Networking (NDN) in tactical communication environments. NDN has inherent functionalities that makes it more robust in a DIL environment in comparison to IP. In this work, we consider a notional tactical environment and compare network performance under IP versus NDN. In our evaluation, we consider different levels of network disruption and different data dissemination mechanisms. Our results show that NDN can provide significant improvement gains in network performance that is superior to IP, under similar network conditions.

Named Data Networking (NDN) is considered to be a viable replacement of the traditional IP networking for the next generation Internet architecture. NDN is a data centric, rather than host centric, approach to discovery and retrieval of information distributed across a network. This paradigm shift results in a host of new challenges, one of which is authentication of data and data-sources. NDN requires each content producer to digitally sign each data packet it produces. While the use of digital signatures certainly accomplishes data and data source authentication, it imposes significant overhead on the whole network. In this paper, we propose a novel data and source authentication mechanism that relies primarily on hashing. The mechanism utilizes hash chaining to ensure that unauthorized modification, insertion, or deletion of data can be easily detected by routers and content consumers.

Reputation management systems have been proposed as a cooperation enforcement solution in ad hoc networks. Typically, the functions of reputation management (evaluation, detection, and reaction) are carried out homogeneously across time and space. However, the dynamic nature of ad hoc networks causes node behavior to vary both spatially and temporally due to changes in local and network-wide conditions. When reputation management functions do not adapt to such changes, their effectiveness, measured in terms of accuracy (correct identification of node behavior) and promptness (timely identification of node misbehavior), may be compromised. We propose an adaptive reputation management system that realizes that changes in node behavior may be driven by changes in network conditions and that accommodates such changes by adapting its operating parameters. We introduce a time-slotted approach to allow the evaluation function to quickly and accurately capture changes in node behavior. We show how the duration of an evaluation slot can adapt according to the network's activity to enhance the system accuracy and promptness. We then show how the detection function can utilize a Sequential Probability Ratio Test (SPRT) to distinguish between cooperative and misbehaving neighbors. The SPRT adapts to changes in neighbors' behavior that are a by-product of changing network conditions, by using the node's own behavior as a benchmark. We compare our proposed solution to a nonadaptive system, showing the ability of our system to achieve high accuracy and promptness in dynamic environments. To the best of our knowledge, this is the first work to explore the adaptation of the reputation management functions to changes in network conditions.

To support high data rates, CDMA lx Ev- DO utilizes TDMA technology on the downlink allowing a single receiver per time slot. Accordingly, a scheduling algorithm is necessary to determine which user receives data in a given time slot. Typically, schedulers consider efficiency (increasing network throughput) or fairness (fair allocation of resources among users) as the basis for scheduling. To realize a reasonable tradeoff between efficiency and fairness, opportunistic schedulers have been proposed that take advantage of instantaneous improvements in users radio conditions by serving them at higher rates. However, given the increasing demand to support user QoS requirements, a QoS-aware scheduler may need to serve users even at times of inadequate radio conditions. In this paper, we propose a QoS-aware packet scheduling algorithm that takes into account policy rules that govern the relationships between different user QoS classes. Our scheduler uses marginal utility functions defined to embody the given rules when selecting users to be served on the downlink. Our scheduling algorithm is implemented in the OPNET module of the CDMA lx Ev-DO system that we have developed, and its performance is compared to other scheduling algorithms. The simulation results show that our scheduler performs well ensuring the policy rules are followed, meeting users' QoS requirements, and providing fairness among users within the same QoS class.

Ad hoc networks employ a decentralized unstructured networking model that relies on node cooperation for key network functionalities such as routing and medium access. In this paper, we develop and evaluate a model based on the sequential probability ratio test to characterize how nodes can differentiate between routes that include misbehaving nodes (infected routes) and routes that do not. An advantage of the model is that the number of observations required to evaluate a route need not be determined in advance.

We propose a secure routing architecture for mobile ad hoc networks (MANETs) called throughput-feedback (TUF) routing, which is resilient against a wide range of routing disruption denial-of-service (DoS) attacks. Unlike many existing solutions, TUF does not focus on a particular type of attack, but instead takes an approach that is fundamentally more general. TUF is a cross-layer technique that detects attacks at the transport layer but responds to attacks at the network layer. Because most routing disruption attacks cause a significant drop in end-to-end goodput, monitoring the goodput of a route at the transport layer can detect abnormalities in the network (e.g., node or link failures, DoS attacks, etc.). Once an abnormal event is detected, a route rebuilding process is initiated at the network layer to find a new route. Using analysis and simulation results, we show that the TUF architecture is effective in thwarting a wide range of attacks, including protocol-compliant (also known as "JellyFish") attacks.

For ad hoc networks to realize their potential in commercial deployments, it is important that they incorporate adequate security measures. Selfish behavior of autonomous network nodes could greatly disrupt network operation. Such behavior should be discouraged, detected, and isolated. In this paper, we propose a reputation-based mechanism to detect and isolate selfish nodes in an ad hoc network. The proposed mechanism allows a node to autonomously evaluate the "reputation" of its neighbors based on the completion of the requested service. The underlying principle is that when a node forwards a packet through one of its neighbors, it holds that neighbor responsible for the correct delivery of the packet to the destination. Our mechanism is efficient and immune to node collusion since, unlike most contemporary mechanisms for reputation-based trust, it does not depend on exchanging reputation information among nodes. We also explore various reputation functions and report on their effectiveness in isolating selfish nodes and reducing false positives. Our simulation results demonstrate that the choice of the reputation function greatly impacts performance and that the proposed mechanism, with a carefully selected function, is successful in isolating selfish nodes while maintaining false positives at a reasonably low level.