1232413
Secure group services for storage area networks
Storage Area Networks, with their ability to offer high data availability, reliability and scalability, are a promising solution for the large scale storage needs of many enterprises. As with any distributed storage system, a major design challenge for a Storage Area Network (SAN) is to provide data integrity and confidentiality. In this paper we propose a solution which addresses these core security requirements. In particular, we focus on mechanisms that enable efficient key distribution to allow scalable data sharing. Our scheme uses strong cryptographic techniques to achieve data security and integrity. Further, we delegate the bulk of the cryptographic processing to the SAN entities (e.g., switches, routers or other network elements), thereby removing bottlenecks at the disks and causing minimal inconvenience to the hosts. By recognizing the peer nature of the group of SAN entities, we propose efficient group key mechanisms that do not involve any centralized key distribution servers. This allows our scheme to be scalable and be free from any single point of failure or attack.
260546
Realistic Sensing Area Modeling
Despite the well-known fact that sensing patterns in reality are highly irregular, researchers continue to develop protocols with simplifying assumptions about the sensing. For example, a circular 0/1 sensing model is widely used in most existing simulators and analysis. While this model provides high-level guidelines, it could cause wrong estimation of system performance in the real world. In this project, we design and implement a practical Sensing Area Modeling technique, called SAM. By injecting events through regular and hierarchical training, SAM estimates the sensing areas of individual sensor nodes accurately. Especially, this work is the first to investigate the impact of irregular sensing area on application performance, such as coverage scheduling. We evaluate SAM using outdoor experiments with XSM motes, indoor experiment with 40 MicaZ motes as well as an extensive 1000-node simulation. Our evaluation results reveal serious problems caused by circular sensing model, while demonstrating significant performance improvements in major applications when SAM is used.
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.
47302704
On the performance of group key agreement protocols
Group key agreement (GKA) is a fundamental building block for securing peer group communication systems (GCS). Several group key agreement protocols were proposed in the past, all assuming an underlying group communication infrastructure. This paper presents a performance evaluation of 5 notable GKA protocols integrated with a reliable group communication system (Spread). They are: centralized group key distribution (CKD), Burmester-Desmedt (BD), Steer et al. (STR), group Diffie-Hellman GDH) and tree-based group Diffie-Hellman (TGDH).. We present concrete results obtained in experiments on local- and wide-area networks. Our analysis of these results offers insights into their relative scalability and practicality.
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
6477815
An Affective User Interface Based on Facial Expression Recognition and Eye-Gaze Tracking
This paper describes a pipeline by which facial expression and eye-gaze of the user are tracked, and then 3D facial animation is synthesized in the remote place based upon timing information of the facial and eye movement information. The system first detects a facial area within the given image and then classifies its facial expression into 7 emotional weightings. Such weighting information, transmitted to the PDA via a mobile network, is used for non-photorealistic facial expression animation. It turns out that facial expression animation using emotional curves is more effective in expressing the timing of an expression comparing to the linear interpolation method. The emotional avatar embedded on a mobile platform has some potential in conveying emotion between peoples via Internet.
12500430
Energy-efficient file placement techniques for heterogeneous mobile storage systems
While hard disk drives are the most common secondary storage devices, their high power consumption and low shock-resistance limit them as an ideal mobile storage solution. On the other hand, flash memory devices overcome the main problems of hard disk drives, but they are still more expensive in the cost per bit over hard disk drives and can only support a limited number of erase cycles. In this paper, we show that combining the merits of a hard disk and a flash memory device can produce an energy-efficient secondary storage solution for mobile platforms. We propose an energy-efficient file placement technique for such heterogeneous storage systems. The proposed technique adapts an existing data concentration technique by separating read and write I/O requests. Experimental results show that the proposed technique reduces the energy consumption by up to 74.5% when the combination of a 1.8" disk and a flash memory is used instead of a single 2.5" disk, at the cost of small increase in the average response time.
40331728
Efficient 2-D Convolution Algorithm with the Single-Data Multiple Kernel Approach
Abstract A fast implementation of convolution operation is described. The implementation takes advantage of various properties of commonly used kernels. First, the kernel elements are analyzed and rearranged, grouping the kernel elements of the same absolute value together and arranging trivial multiplication cases separately. Then the sequence of computing convolution sums is modified so that all the kernel elements could be multiplied by the same data element at each step. This new algorithm significantly reduces the number of multiplication operations for most widely used kernels. Our experiment shows that the performance improvement of two to seven over the direct implementation is achievable for most kernels. The required overhead (extra memory and preprocessing) is proportional to the kernel size and is negligible.
12493055
A methodology for evaluation of boundary detection algorithms on medical images
Image segmentation is the partition of an image into a set of nonoverlapping regions whose union is the entire image. The image is decomposed into meaningful parts which are uniform with respect to certain characteristics, such as gray level or texture. In this paper, we propose a methodology for evaluating medical image segmentation algorithms wherein the only information available is boundaries outlined by multiple expert observers. In this case, the results of the segmentation algorithm can be evaluated against the multiple observers' outlines. We have derived statistics to enable us to find whether the computer-generated boundaries agree with the observers' hand-outlined boundaries as much as the different observers agree with each other. We illustrate the use of this methodology by evaluating image segmentation algorithms on two different applications in ultrasound imaging. In the first application, we attempt to find the epicardial and endocardial boundaries from cardiac ultrasound images, and in the second application, our goal is to find the fetal skull and abdomen boundaries from prenatal ultrasound images.
14647313
Energy-efficient disk replacement and file placement techniques for mobile systems with hard disks
Mobile systems have usually used hard disks as the secondary storage devices because of their high capacity per cost and high I/O throughput. However, their high power consumption is the main limiting factor for extending their adoptions in mobile systems. In this paper, we propose enhanced file placement techniques for mobile platforms with multiple smaller disks (instead of a single large disk). We investigate that how many smaller disks are necessary to obtain energy saving while maintaining the required performance using both a simplified energy model and a realistic trace-based simulator under the proposed multiple disk configurations. We also propose energy-efficient file placement techniques, which aggregate files with common attributes the same set of disks. By skewing I/O operations, the proposed techniques achieve additional energy saving. Experimental results show that the proposed techniques can reduce the energy consumption by up to 43% when eight 1" disks are used instead of a single 2.5" disk with an acceptable increase in the average response time.