Yuichi Sei

Distributed detection of node replication attacks resilient to many compromised nodes in wireless sensor networks

In large-scale sensor networks, sensor nodes are at high risk of being captured and compromised. Once a sensor node is compromised, all the secret keys, data, and code stored on it are exposed to the attacker. The attacker can insert arbitrary malicious code in the compromised node. Moreover, he can easily replicate it in a large number of clones and deploy them on the network. This node replication attack can form the basis of a variety of attacks such as DoS attacks, and Sybil attacks. Previous studies of node replication attacks have had some drawbacks; they need a central trusted entity or they become vulnerable when many nodes are compromised. Therefore, we propose a distributed protocol for detecting node replication attacks that is resilient to many compromised nodes. Our method does not need any reliable entities and has a high detection rate of replicated nodes. Our analysis and simulations demonstrate our protocol is effective even when there are a large number of compromised nodes.

Reporter node determination of replicated node detection in wireless sensor networks

In large-scale sensor networks, sensor nodes are at high risk of being captured and compromised. Once a sensor node is compromised, all the secret keys, data, and code stored on it are exposed to the attacker. The attacker can insert arbitrary malicious code in the compromised node. Moreover, he can easily replicate such code in a large number of clones and deploy them on the network. This node replication attack can form the basis of a variety of attacks such as DoS attacks and Sybil attacks. In the related studies, as a means of detecting compromised nodes, each node reports its neighbors ID and location to a witness node with some probability p. The value of p is determined beforehand or from only the number of neighbor nodes. In this paper, we change p according to the locations of nodes. We aim to increase the detection rate of replicated node attacks and decrease the amount of messages. Our analysis and simulations demonstrate that using our protocol in combination with the methods of other studies is more effective than using the methods of the related studies by themselves.

Distributed Arrays: A P2P Data Structure for Efficient Logical Arrays

Distributed hash tables (DHT) are used for data management in P2P environments. However, since most hash functions ignore relations between items, DHTs are not efficient for operations on related items. In this paper, we modify a DHT into a distributed array (DA) that enables efficient operations on logical arrays. The array elements of a DA are placed in a P2P overlay network according to a simple rule such that the load is balanced and the number of messages required to access elements sequentially is reduced. The number of messages required for array operations is much smaller than that for operations on DHTs. We demonstrate this theoretically and experimentally.

Resilient security for false event detection without loss of legitimate events in wireless sensor networks

When large-scale wireless sensor networks are deployed in hostile environments, the adversary may compromise some sensor nodes and use them to generate false sensing reports or to modify the reports sent by other nodes. Such false events can cause the user to make bad decisions. They can also waste a significant amount of network resources. Unfortunately, most current security designs have drawbacks; they either require their own routing protocols to be used, or lose legitimate events stochastically and completely break down when more than a fixed threshold number of nodes are compromised. We propose a new method for detecting false events that does not suffer from these problems. When we set the probability of losing legitimate events to 1%, our proposal method can detect more false events than related method can. We demonstrate this by mathematical analysis and simulation.

Ringed Filters for Peer-to-Peer Keyword Searching

Distributed hash tables (DHTs) are a class of decentralized distributed systems that can efficiently search for objects desired by the user. However, a lot of communication traffic comes from multi-word searches. A lot of work has been done to reduce this traffic by using bloom filters, which are space-efficient probabilistic data structures. There are two kinds of bloom filters: fixed-size and variable-size bloom filters. We cannot use variable- size bloom filters because doing so would mean wasting time to calculating hash values. On the other hand, when using fixed- size bloom filters, all the nodes in a DHT are unable to adjust their false positive rate parameters. Therefore, the reduction of traffic is limited because the best false positive rate differs from one node to another. Moreover, in related works, the authors took only two-word searches into consideration. In this paper, we present a method for determining the best false positive rate for three- or more word searches. We also used a new filter called a ringed filter, in which each node can set the approximately best false positive rate. Experiments showed that the ringed filter was able to greatly reduce the traffic.

Flexible Bloom Filters for Searching Textual Objects

Efficient object searching mechanisms are essential in large-scale networks. Many studies have been done on distributed hash tables (DHTs), which are a kind of peer-to-peer system. In DHT networks, we can certainly get the desired objects if they exist. However, multi-word searches generate much communication traffic. Many studies have tried to reduce this traffic by using bloom filters, which are space-efficient probabilistic data structures. In using such filters, all nodes in a DHT must share their false positive rate parameter. However, the best false positive rate differs from one node to another. In this paper, we provide a method of determining the best false positive rate, and we use a new filter called a flexible bloom filter, to which each node can set the approximately best false positive rate. Experiments showed that the flexible bloom filter was able to greatly reduce the traffic.

Managing difference-based objects with sub-networks in peer-to-peer environments

P2P systems are currently being used all over the world. However, existing P2P technology is not able to modify shared objects efficiently. Naive approaches to support modification result in large amounts of traffic and load concentrations. In our study, this issue is being addressed by representing shared objects by their differences. These are stored in a sub-network that is generated for each object. The object is accessed by retrieving and adding the differences stored in the sub-network. A simple simulation demonstrates the effectiveness of this technique in regard to traffic amount and load balancing properties.

Reduction of the Communication Traffic for Multi-word Searches in DHTs

In large-scale wireless networks, efficient file searching mechanisms are essential for users. Many studies have been done on a distributed hash tables (DHTs) which are one kind of peer-to-peer system. In DHT networks, we can certainly and effectively get the desired files if they exist. However, much communication traffic comes from multi-word searches. If we increase the storage redundancy, we can reduce the traffic. However, storage constrains of mobile devices make doing so impossible. In our previous work, we proposed a divided bloom filter to reduce the traffic in DHTs. However, the effect of divided bloom filters depends strongly on their parameters, and optimizing them is difficult. Hence, we have developed and tested the method to determine optimum parameters of divided bloom filters.