The Internet of Things (IoT) is increasingly more relevant. This growing importance calls for tools able to provide users with correct, reliable and secure systems. In this paper, we claim that traditional approaches to analyze distributed systems are not expressive enough to address this challenge. As a solution to this problem, we present SIoT, a framework to analyze networked systems. SIoT's key insight is to look at a distributed system as a single body, and not as separate programs that exchange messages. By doing so, we can crosscheck information inferred from different nodes. This crosschecking increases the precision of traditional static analyses. To construct this global view of a distributed system we introduce a novel algorithm that discovers inter-program links efficiently. Such links lets us build a holistic view of the entire network, a knowledge that we can thus forward to a traditional tool. We prove that our algorithm always terminates and that it correctly models the semantics of a distributed system. To validate our solution, we have implemented SIoT on top of the LLVM compiler, and have used one instance of it to secure 6 ContikiOS applications against buffer overflow attacks. This instance of SIoT produces code that is as safe as code secured by more traditional analyses; however, our binaries are on average 18% more energy-efficient.

Wireless Sensor Networks (WSNs) are comprised mainly of resource-constrained sensor nodes that can be used to monitor areas of interest. In sensor networks, replacement of node batteries is usually infeasible and power consumption must be minimal to increase node lifetime. A large fraction of power consumption is controlled by the MAC layer, which orchestrates access to the wireless medium trading-off power consumption and throughput. Unfortunately, this orchestration requires exchange of additional data and itself ends up consuming energy. In this work we design a novel approach that does not require extra data to be exchanged. More precisely, we present ID-MAC: an identity-based MAC protocol for WSNs. In ID-MAC, sensor nodes compute when they should wake up in order to transmit and receive frames from their neighbors without exchanging coordination messages. Our evaluation shows that, by eliminating coordination messages, ID-MAC saves energy and prolongs the network's operating lifespan.

Under-Water Wireless Sensor Networks (UWSNs) are a particular class of Wireless Sensor Networks (WSNs) in which sensors are located, as the name suggests, underwater. Applications of UWSNs range from oceanographic data collection to disaster prevention. UWSNs are vulnerable to attacks and because of their idiosyncrasies, security solutions for ground WSNs might not be applicable underwater. As a result, there is a need for mechanisms exclusively tailored to underwater environments. In this work we address the problem of authentication in UWSNs. We evaluate energy costs for different digital signature schemes for end-to-end authentication and discuss the tradeoffs involved in a number of scenarios. Our results show that schemes that perform well in ground WSN do not necessarily do well in UWSNs; and shed light on characteristics of a digital signature scheme that make them particularly suited to underwater networks.

Hop-by-hop authentication in wireless sensor networks (WSNs) prevents outside intruders from taking part in the network and launching attacks. Due to resource constraints of WSNs, standard key distribution schemes are not applicable. Such networks require resilience when intruders compromise a key. This paper presents NEKAP - neighborhood-based key agreement protocol, a key distribution protocol for WSNs. NEKAP is intruder resilient: an intruder that compromises a key has access to the links of a limited neighborhood, and not to those in other regions of the network. NEKAP is energy-efficient in that only a few messages are exchanged in small neighborhoods to establish the keys. The paper presents the protocol and algorithms, make a security analysis, compare it with other protocols in the literature and shows one implementation for the TinySec platform.

Wireless sensor networks are ad hoc networks comprised mainly of small sensor nodes with limited resources and one or more base stations, which are much more powerful laptopclass nodes that connect the sensor nodes to the rest of the world. The advent of this tecnology over the last decade enables largescale deployment of such sensors. On the other hand, this poses the challenging of how the great amount of information generated by these sensor networks will be handled at the base station. In this paper, we propose a network processor architecture tailored specifically to handling information at sensor network base stations. Our approach optimize information processing by implementing tasks in hardware. We show that the novel architecture is one order of magnitude faster than an architecture based on traditional RISC processor.

Clustered sensor networks have been shown to increase system throughput, decrease system delay, and save energy. While those with rotating cluster heads, such as LEACH, have also advantages in terms of security, the dynamic nature of their communication makes most existing security solutions inadequate for them. In this paper, we show how random key predistribution, widely studied in the context of flat networks, can be used to secure communication in hierarchical (cluster-based) protocols such as LEACH. To our knowledge, it is the first work that investigates random key predistribution as applied to hierarchical WSNs

Both mobile ad hoc networks (MANETs) and peer-to-peer (P2P) networks are decentralized and self-organizing networks with dynamic topology and are responsible for routing queries in a distributed environment. Because MANETs are composed of resource-constrained devices susceptible to faults, whereas P2P networks are fault-tolerant, P2P networks are the ideal data sharing system for MANETs. We have conducted an evaluation of two approaches for P2P content discovery running over a MANET. The first, based on unstructured P2P networks, relies on controlled flooding, while the second, based on structured P2P networks, uses distributed indexing to optimize searches. We use simulations to evaluate the effect of network size, mobility, channel error rates, network workload, and application dynamics in the performance of P2P protocols over MANETs. Results show that unstructured protocols are the most resilient, although at higher energy and delay costs. Structured protocols, conversely, consume less energy and are more appropriate for MANETs where topology is mostly static.

Summary form only given. This work provides a solution to identify malicious nodes in wireless sensor networks through detection of malicious message transmissions in a network. A message transmission is considered suspicious if its signal strength is incompatible with its originator's geographical position. We provide protocols for detecting suspicious transmissions - and the consequent identification of malicious nodes - and for disseminating this information in the network. We evaluate the detection rate and the efficiency of our solution along a number of parameters.

Wireless Sensor Networks (WSNs) have emerged as a new monitoring and control solution for a variety of applications. Although the behavior of a WSN is characterized by the type of its application, a common element exist: faults are a normal fact, not isolated events as in traditional networks. Thus, in order to guarantee the network quality of service it is essential for the WSN to be able to detect failures and perform something akin to healing, recovering from events that might cause some of its parts to malfunction. In this work we propose and evaluate a failure detection scheme using a management architecture for WSNs, called MANNA. We take a deep look at its fault management capabilities supposing the existence of an event-driven WSN. This is a challenging and attractive kind of WSN and we show how the use of automatic management services defined by MANNA can provide self-configuration, self-diagnostic, and self-healing (some of the self-managing capabilities). We also show that the management solution promote the resources productivity without incurring a high cost to the network.