18915158
Revisiting random key pre-distribution schemes for wireless sensor networks
Key management is one of the fundamental building blocks of security services. In a network with resource constrained nodes like sensor networks, traditional key management techniques, such as public key cryptography or key distribution center (e.g., Kerberos), are often not effective. To solve this problem, several key pre-distribution schemes have been proposed for sensor networks based on random graph theory. In these schemes, a set of randomly chosen keys or secret information is pre-distributed to each sensor node and a network is securely formed based on this information. Most of the schemes assumed that the underlying physical network is dense enough, that is, the degree of each node is hig.
 In this paper, we revisit the random graph theory and use giant component theory by Erdos and Renyi to show that even if the node degree is small, most of the nodes in the network can be connected. Further, we use this fact to analyze the Eschenhauer et. al's, Du et. al's, and Chan et. al's key pre-distribution schemes and evaluate the relation between connectivity, memory size, and security. We show that we can reduce the amount of memory required or improve security by trading-off a very small number of isolated nodes. Our simulation results show that the communication overhead does not increase significantly even after reducing the node degree. In addition, we present an approach by which nodes can dynamically adjust their transmission power to establish secure links with the targeted networked neighbors. Finally, we propose an effcient path-key identification algorithm and compare it with the existing scheme.
6315809
On the performance of group key agreement protocols
Group key agreement is a fundamental building block for secure peer group communication systems. Several group key management techniques were proposed in the last decade, all assuming the existence of an underlying group communication infrastructure to provide reliable and ordered message delivery as well as group membership information. Despite analysis, implementation, and deployment of some of these techniques, the actual costs associated with group key management have been poorly understood so far. This resulted in an undesirable tendency: on the one hand, adopting suboptimal security for reliable group communication, while, on the other hand, constructing excessively costly group key management protocols.This paper presents a thorough performance evaluation of five notable distributed key management techniques (for collaborative peer groups) integrated with a reliable group communication system. An in-depth comparison and analysis of the five techniques is presented based on experimental results obtained in actual local- and wide-area networks. The extensive performance measurement experiments conducted for all methods offer insights into their scalability and practicality. Furthermore, our analysis of the experimental results highlights several observations that are not obvious from the theoretical analysis.
14346631
Remote Software-Based Attestation for Wireless Sensors
Wireless sensor networks are envisioned to be deployed in mission-critical applications. Detecting a compromised sensor, whose memory contents have been tampered, is crucial in these settings, as the attacker can reprogram the sensor to act on his behalf. In the case of sensors, the task of verifying the integrity of memory contents is difficult as physical access to the sensors is often infeasible. In this paper, we propose a software-based approach to verify the integrity of the memory contents of the sensors over the network without requiring physical contact with the sensor. We describe the building blocks that can be used to build a program for attestation purposes, and build our attestation program based on these primitives. The success of our approach is not dependent on accurate measurements of the execution time of the attestation program. Further, we do not require any additional hardware support for performing remote attestation. Our attestation procedure is designed to detect even small memory changes and is designed to be resistant against modifications by the attacker.
6168983
Privacy Preserving Nearest Neighbor Search
Data mining is frequently obstructed by privacy concerns. In many cases data is distributed, and bringing the data together in one place for analysis is not possible due to privacy laws (e.g. HIPAA) or policies. Privacy preserving data mining techniques have been developed to address this issue by providing mechanisms to mine the data while giving certain privacy guarantees. In this work we address the issue of privacy preserving nearest neighbor search, which forms the kernel of many data mining applications. To this end, we present a novel algorithm based on secure multiparty computation primitives to compute the nearest neighbors of records in horizontally distributed data. We show how this algorithm can be used in three important data mining algorithms, namely LOF outlier detection, SNN clustering, and kNN classification
7213506
Batch Verifications with ID-Based Signatures
An identity (ID)-based signature scheme allows any pair of users to verify each other’s signatures without exchanging public key certificates. With the advent of Bilinear maps, several ID-based signatures based on the discrete logarithm problem have been proposed. While these signatures have an advantage in the fact that the system secret can be shared by several parties using a threshold scheme (thereby overcoming the security problem of RSA-based ID-based signature schemes), they all share the same efficiency disadvantage. To overcome this, some schemes have focused on finding ways to verify multiple signatures at the same time (i.e. the batch verification problem). While they had some success in improving efficiency of verification, each had a slightly diversified definition of batch verification. In this paper, we propose a taxonomy of batch verification against which we analyze security of well-known ID-based signature schemes. We also propose a new ID-based signature scheme that allows for all types of multiple signature batch verification, and prove its security in random oracle model.
8456310
Detecting Phantom Nodes in Wireless Sensor Networks
In an adversarial environment, various kinds of security attacks become possible if malicious nodes could claim fake locations that are different from where they are physically located. In this paper, we propose a secure localization mechanism that detects the existence of these nodes, termed as phantom nodes, without relying on any trusted entities, an approach significantly different from the existing ones. The proposed mechanism enjoys a set of nice features. First, it does not have any central point of attack. All nodes play the role of verifier, by generating local map, i.e. a view constructed based on ranging information from its neighbors. Second, this distributed and localized construction results in quite strong results: even when the number of phantom nodes is greater than that of honest nodes, we can Alter out most phantom nodes. Our analysis and simulations under realistic noisy settings demonstrate our scheme is effective in the presence of a large number of phantom nodes.
6826338
Geometric crossover for multiway graph partitioning
Geometric crossover is a representation-independent generalization of the traditional crossover defined using the distance of the solution space. Using a distance tailored to the problem at hand, the formal definition of geometric crossover allows to design new problem-specific crossovers that embed problem-knowledge in the search. The standard encoding for multiway graph partitioning is highly redundant: each solution has a number of representations, one for each way of labeling the represented partition. Traditional crossover does not perform well on redundant encodings. We propose a new geometric crossover for graph partitioning based on a labeling-independent distance that filters the redundancy of the encoding. A correlation analysis of the fitness landscape based on this distance shows that it is well suited to graph partitioning. Our new genetic algorithm outperforms existing ones.
7564297
Problem-Independent Schema Synthesis for Genetic Algorithms
As a preprocessing for genetic algorithms, static reordering helps genetic algorithms effectively create and preserve high-quality schemata, and consequently improves the performance of genetic algorithms. In this paper, we propose a static reordering method independent of problem-specific knowledge. One of the novel features of our reordering method is that it is applicable to any problem with no information about the problem. The proposed method constructs a weighted complete graph from the gene distances calculated from solutions with relatively high fitnesses, transforms them into a gene-interaction graph, and finds a gene rearrangement. Extensive experimental results showed significant improvement for a number of applications.
61949387
Quantizer design and distributed encoding algorithm for source localization in sensor networks
In this paper, we propose a quantizer design algorithm that is optimized for source localization in sensor networks. For this application, the goal is to minimize the amount of information that the sensor nodes have to exchange in order to achieve a certain source localization accuracy. We show that this goal can be achieved more efficiently when "application-specific" quantizers are used. Our proposed quantizer design algorithm uses a cost function that takes into account the distance between the actual source position and the position estimated based on quantized data. We also propose a distributed encoding algorithm that is applied after quantization and achieves rate savings by merging quantization bins without any degradation of localization performance. The merging technique in the encoding algorithm exploits the fact that certain combinations of quantization bins at each node cannot occur because the corresponding spatial regions have an empty intersection. We apply these algorithms to a system where an acoustic sensor model is employed for localization. For this case, we introduce the equally distance-divided quantizer (EDQ), designed so that quantizer partitions correspond to a uniform partitioning in terms of distance. Our simulations show the improved performance of our quantizer over traditional quantizer designs. In addition, they show rate savings (32.8%, 5 nodes, 4 bits per node) when our novel bin-merging algorithms are used. Our results also show that an optimized bit allocation leads to significant improvements in localization performance with respect to a bit allocation that uses the same number of bits for each node.
44579377
Head Detection and Tracking for the Car Occupant's Pose Recognition
This paper describes a Vision-based Occupant Pose Recognition (VOPR) system, which can ensure a safe airbag deployment. Head detection and its tracking are necessary for occupant’s pose recognition in the car, since the position of occupant’s head provides valuable information, such as his pose, size, position, and so on. We use the stereo cameras to extract a disparity map. Against variable lighting conditions including the night drive, we adopt infrared illumination as well as normal one. Results suggest that VOPR system is reliable and performs reasonably well.
28723686
Implementation of ECC/ECDSA cryptography algorithms based on Java card
This paper describes the implementations and test results of elliptic curve cryptography (ECC) and elliptic curve digital signature algorithm (ECDSA) algorithms based on Java card. A 163-bit ECC guarantees as secure as the 1024-bit Rivest-Shamir-Adleman (RSA) public key algorithm, which has been frequently used until now. According to our test results, the 163-bit ECC processing time is about five times faster compared with the 1024-bit RSA, and the amount of resource usages of ECC is smaller than RSA. Therefore, ECC is more appropriate for use on secure devices such as smart cards and wireless devices with constrained computational power consumption and memory resources.