239370
SIA: secure information aggregation in sensor networks
Sensor networks promise viable solutions to many monitoring problems. However, the practical deployment of sensor networks faces many challenges imposed by real-world demands. Sensor nodes often have limited computation and communication resources and battery power. Moreover, in many applications sensors are deployed in open environments, and hence are vulnerable to physical attacks, potentially compromising the sensor's cryptographic keys.One of the basic and indispensable functionalities of sensor networks is the ability to answer queries over the data acquired by the sensors. The resource constraints and security issues make designing mechanisms for information aggregation in large sensor networks particularly challenging.In this paper, we propose a novel framework for secure information aggregation in large sensor networks. In our framework certain nodes in the sensor network, called aggregators, help aggregating information requested by a query, which substantially reduces the communication overhead. By constructing efficient random sampling mechanisms and interactive proofs, we enable the user to verify that the answer given by the aggregator is a good approximation of the true value even when the aggregator and a fraction of the sensor nodes are corrupted. In particular, we present efficient protocols for secure computation of the median and the average of the measurements, for the estimation of the network size, and for finding the minimum and maximum sensor reading. Our protocols require only sublinear communication between the aggregator and the user. To the best of our knowledge, this paper is the first on secure information aggregation in sensor networks that can handle a malicious aggregator and sensor nodes.
987821
Using Clustering Information for Sensor Network Localization
Sensor network localization continues to be an important research challenge. The goal of localization is to assign geographic coordinates to each node in the sensor network. Localization schemes for sensor network systems should work with inexpensive off-the-shelf hardware, scale to large networks, and also achieve good accuracy in the presence of irregularities and obstacles in the deployment area. 
 
We present a novel approach for localization that can satisfy all of these desired properties. Recent developments in sensor network clustering algorithms have resulted in distributed algorithms that produce highly regular clusters. We propose to make use of this regularity to inform our localization algorithm. The main advantages of our approach are that our protocol requires only three randomly-placed nodes that know their geographic coordinates, and does not require any ranging or positioning equipment (i.e., no signal strength measurement, ultrasound ranging, or directional antennas are needed). So far, only the DV-Hop localization mechanism worked with the same assumptions [1]. We show that our proposed approach may outperform DV-Hop in certain scenarios, in particular when there exist large obstacles in the deployment field, or when the deployment area is free of obstacles but the number of anchors is limited.
15483673
Process Isolation for Reconfigurable Hardware
One of the pillars of trust-worthy computing is process isolation, the ability to keep process data private from other processes running on the same device. While embedded operating systems provide isolation for the software part of these processes, there is no commonly accepted isolation mechanism for the hardware resources. As a result, systems may remain vulnerable to hardware-based attacks. This paper presents a secure coprocessor interface that extends the concept of process isolation into reconfigurable hardware. In the resulting coprocessor design, context information for different processes concurrently accessing the coprocessor is physically kept private. The coprocessor interface can handle context switches between different processes without assistance of the operating system. Because of this, reconfiguration of computation units can occur independent of the main processor. Moreover, it does so with greater efficiency than what is possible using software only.
257219
On the Revision of Probabilistic Beliefs using Uncertain Evidence
We revisit the problem of revising probabilistic beliefs using uncertain evidence, and report results on several major issues relating to this problem: how should one specify uncertain evidence? How should one revise a probability distribution? How should one interpret informal evidential statements? Should, and do, iterated belief revisions commute? And what guarantees can be offered on the amount of belief change induced by a particular revision? Our discussion is focused on two main methods for probabilistic revision: Jeffrey's rule of probability kinematics and Pearl's method of virtual evidence, where we analyze and unify these methods from the perspective of the questions posed above.
2499858
Location updates and probabilistic tracking algorithms for mobile cellular networks
In this paper, we develop a novel mathematical model to analyze different location update protocols for mobile cellular network. Our model can capture many important features of user movements, such as geographically dependent movement, directional movement and non-exponential distribution of cell dwell times. We propose to use the transient method to predict the location of a mobile user. This method is efficient and, more importantly, able to address the temporal change in the current location of a mobile user. Therefore, the accuracy of the prediction of the location of a user can be enhanced. We also propose a new location update protocol which can attain a lower trading cost and also adapt to different mobility patterns. Transient performance analysis is also carried out and the results are compared with other protocols.
5672538
When do Numbers Really Matter?
Common wisdom has it that small distinctions in the probabilities quantifying a belief network do not matter much for the results of probabilistic queries. Yet, one can develop realistic scenarios under which small variations in network probabilities can lead to significant changes in computed queries. A pending theoretical question is then to analytically characterize parameter changes that do or do not matter. In this paper, we study the sensitivity of probabilistic queries to changes in network parameters and prove some tight bounds on the impact that such parameters can have on queries. Our analytical results pinpoint some interesting situations under which parameter changes do or do not matter. These results are important for knowledge engineers as they help them identify influential network parameters. They also help explain some of the previous experimental results and observations with regards to network robustness against parameter changes.
5337517
Throughput Optimized SHA-1 Architecture Using Unfolding Transformation
In this paper, the authors analyze the theoretical delay bound of the SHA-1 algorithm and propose architectures to achieve high throughput hardware implementations which approach this bound. According to the results of FPGA implementations, 3,541 Mbps with a pipeline and 893 Mbps without a pipeline were achieved. Moreover, synthesis results using 0.18mum CMOS technology showed that 10.4 Gbps with a pipeline and 3.1 Gbps without a pipeline can be achieved. These results are much faster than previously published results. The high throughputs are due to the unfolding transformation, which reduces the number of required cycles for one block hash. The authors reduced the required number of cycles to 12 cycles for a 512 bit block and showed that 12 cycles is the optimal in our design