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2015 | Book

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Secure Wireless Sensor Networks

Threats and Solutions

Author: Mauro Conti

Publisher: Springer New York

Book Series : Advances in Information Security

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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About this book

This book explores five fundamental mechanisms to build secure Wireless Sensor Networks (WSNs). It presents security issues related to a single node which deals with the authentication and communication confidentiality with other nodes. It also focuses on network security, providing solutions for the node capture attack and the clone attack.

It examines a number of areas and problems to which WSNs are applied continuously, including: supporting rescue operations, building surveillance, fire prevention, battlefield monitoring and more. However, known and unknown threats still affect WSNs and in many applications of this new technology the security of the network is a fundamental issue for confidentiality, integrity, authenticity and availability. The last section of the book addresses security for a common WSN service. Case studies are provided throughout.

Secure Wireless Sensor Networks: Threats and Solutions targets advanced-level students and researchers in computer science and electrical engineering as a secondary text book. Professionals working in the wireless sensor networks field will also find this book useful as a reference.

Table of Contents

Frontmatter
Chapter 1. Introduction
Abstract
The evolution of computing devices followed different paths.Despite the famous misquotation attributed to Thomas J. Watson Sr., then-president of IBM, (“I think there is a world market for maybe five computers.”), during the 70’s a new paradigm emerged: The Personal Computer.
Mauro Conti
Chapter 2. Pair-Wise Key Establishment
Abstract
In this chapter we start addressing the security of Wireless Sensor Networks (WSNs) from the point of view which is closest to the single node: We consider the authentication and the confidentiality of the communications with other nodes. In particular, this chapter presents the ECCE Protocol, a new distributed, probabilistic, cooperative protocol to establish a secure pair-wise communication channel between any pair of sensors in a WSN. The main contribution of the ECCE Protocol is: To allow the set up of a secure channel between two sensors (principals) that do not share any pre-deployed key. This feature is obtained involving a set of sensors (cooperators) in the channel establishment protocol to provide probabilistic authentication of the principals as well as the cooperators. In particular, the probability for the attacker to break authentication check decreases exponentially with the number of cooperators involved. We provide analytical analysis and extensive simulations of the ECCE, which show that the proposed solution increases both the probability of a secure channel set up and the probability of channel resilience with respect to other protocols.
Mauro Conti
Chapter 3. Capture Detection
Abstract
The previous chapter looked at the security of WSNs from the single node perspective. We proposed a new probabilistic protocol for the node authentication and the communication confidentiality. Given that in our solution a secret key can be shared between more than two nodes, the attacker that physically captures a node is potentially able to compromise the confidentiality of a fraction of network communications. Actually, one of the most vexing problems for WSNs security is the node capture attack: An adversary can capture a node from the network eventually acquiring all the cryptographic material stored in it. Further, the captured node can also be reprogrammed by the adversary and re-deployed in the network in order to perform malicious activities.
Mauro Conti
Chapter 4. Clone Detection
Abstract
The previous chapter considered the node capture problem. The capture of a node affects all the network: All the nodes should be aware that the corresponding node’s ID is untrusted from the moment of the capture. We proposed a new approach for the node capture detection. However, the capture detection comes with a cost (in terms of energy consumption) that is inversely proportional to the detection time and should not be prohibitive for the network. As a result, the detection time cannot be decreased under a given threshold. If the node capture is undetected, the adversary can first re-program the captured node and then clone it in a large number of clones, easily taking over the network. Then, the detection of node clone attacks in a wireless sensor network is also a fundamental problem. A few distributed solutions to this problem have been recently proposed in literature. However, these solutions are not satisfactory. First, they are energy and memory demanding: A serious drawback for any protocol to be used in a resource constrained environment like a sensor network. Further, they are vulnerable to specific adversary models introduced in this chapter.
Mauro Conti
Chapter 5. Secure Data Aggregation
Abstract
Chapter 4 considered a general WSN security problem. In this chapter we want to focus on a specific WSN service: The data collection. If each single node sends its own data to the collecting point in an independent way this will result in a huge waste of energy. To meet the severe energy constraints in WSNs, some researchers have proposed to use the in-network data aggregation technique (i.e., combining partial results at intermediate nodes during message routing), which significantly reduces the communication overhead. Some researchers also proposed algorithms to securely compute a few aggregates, such as Sum (the sum of the sensed values), Count (number of nodes) and Average. However, to the best of our knowledge, there is no prior work which securely computes the Median, although the Median is considered to be an important aggregate. The contribution of this chapter is twofold. We first propose a protocol to compute an approximate Median and verify if it has been falsified by an adversary. Then, we design an attack-resilient algorithm to compute the Median even in the presence of a few compromised nodes. We evaluate the performance and cost of our approach via both analysis and simulation. Our results show that our approach is scalable and efficient.
Mauro Conti
Chapter 6. Privacy in Data Aggregation
Abstract
We started addressing the security of in-network data aggregation in the previous chapter, where we addressed the problem of the Median computation where attacker nodes can be present. In this chapter we address another security problem related to the data aggregation: The node’s privacy. In fact, in the data aggregation technique, some sensor nodes need to send their individual sensed values to an aggregator node, empowered with the capability to decrypt the received data to perform a partial aggregation. This scenario raises privacy concerns in applications like personal health care and the military surveillance. The contributions of this chapter are two-fold: first, we design a private data aggregation protocol that does not leak individual sensed values during the data aggregation process. In particular, neither the base station nor the other nodes are able to compromise the privacy of an individual node’s sensed value.
Mauro Conti
Chapter 7. Conclusions and Future Works
Abstract
The number of areas and problems to which Wireless Sensor Networks are applied continuously grow while known and unknown threats affect this technology. Researchers are called to address the design of efficient protocols that are secure against possible attacks.
Mauro Conti
Backmatter
Metadata
Title
Secure Wireless Sensor Networks
Author
Mauro Conti
Copyright Year
2015
Publisher
Springer New York
Electronic ISBN
978-1-4939-3460-7
Print ISBN
978-1-4939-3458-4
DOI
https://doi.org/10.1007/978-1-4939-3460-7

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