Ali Saman Tosun

Efficient multi-layer coding and encryption of MPEG video streams

This paper introduces a novel, light-weight video encryption algorithm that supports light-weight, multi-layered encryption. The objectives of this encryption algorithm are to reduce the total amount of data encrypted (while providing reasonable privacy and security) and to allow for the playback of the encrypted stream in the presence of network packet loss and bit-errors. The latter property allows for the easy adaptation of encrypted video over best-effort networks, such as the Internet. This algorithm partitions the stream into three layers and provides encryption on the lower two layers. An adaptive algorithm is provided that shows how to adaptively partition the video data so that the user can ensure a maximum peak signal to noise ratio in the base layer. Our results show that we can provide security by encrypting only a fraction of the data depending on the level of security the user requires.

Lightweight security mechanisms for wireless video transmission

The paper introduces lightweight video encryption algorithms for transmission over wireless networks. The objective of these encryption algorithms is to reduce the total amount of data encrypted (while providing reasonable privacy and security) and to use multiple FEC codes to reduce the expected number of bit errors left in the data after decoding. The goal of this work is to provide encryption of video data while increasing the decodeability of the stream in the presence of network bit error. The first algorithm uses multi-layer video coding (which also helps to increase PSNR) for security and encrypts only a base layer. The second algorithm extends video encryption algorithms to deduce the amount of data encrypted and uses different BCH codes for each level.

Optimal parallel I/O using replication

There has been a lot of interest in declustering spatial data for efficient parallel I/O. Declustering is used to distribute blocks of data among multiple devices, thus enabling parallel I/O access and reducing query response times. A strictly optimal declustering, or disk allocation, technique is the one that achieves optimal performance for all possible queries. We propose to use replication to reach optimal parallel I/O in multidisk/processor architectures. Replication is a well-known and effective solution for several problems in a database context, especially for availability and load balancing problems. Intelligent replication is considered. We especially focus on allocations based on latin squares and derive several nice properties for replication and declustering purposes. Three different replication strategies are proposed and evaluated. Using the proposed schemes, strict optimality is reached, even with a single replication, for all possible range queries and for several number of disks. We first show this for m-by-m grid on m disks, and then generalize it to any arbitrary a-by-b grids. We also show how to efficiently find optimal disk accesses for a given arbitrary query by storing minimal information.

On error preserving encryption algorithms for wireless video transmission

In this paper, we describe error preserving encryption mechanisms for transmission of vido over wireless networks. One of the main problems with the secure transmission of data over wireless networks is that the bit errors that occur need to typically be sesolved before decryption can begin. For vido straming applications, this is unacceptable due to the general requirement that video be presented to the user in a continuous manner with low latency. In this paper, we describe a systematic approach to understanding error preserving encryption algorithms. That is, encryption algorithms designed specifically for video to solve this problem. The main objective of this work is to ensure that the basic encryption of the stream can survive bit errors and that the errors are then passed to the application. We make use of the fact that video compression typically results in random byte distribution. Error preserving encryption algorithms are secure against ciphertext only attacks but vulnerable against known plaintext attacks. We limit this vulnerabillity by requiring a key exchange for each session.

Analysis and Comparison of Replicated Declustering Schemes

Declustering distributes data among parallel disks to reduce the retrieval cost using I/O parallelism. Many schemes were proposed for the single-copy declustering of spatial data. Recently, declustering using replication gained a lot of interest and several schemes with different properties were proposed. An in-depth comparison of major schemes is necessary to understand replicated declustering better. In this paper, we analyze the proposed schemes, tune some of the parameters, and compare them for different query types and under different loads. We propose a three-step retrieval algorithm for the compared schemes. For arbitrary queries, the dependent and partitioned allocation schemes perform poorly; others perform close to each other. For range queries, they perform similarly with the exception of smaller queries in which random duplicate allocation (RDA) performs poorly and dependent allocation performs well. For connected queries, partitioned allocation performs poorly and dependent allocation performs well under a light load.

Design theoretic approach to replicated declustering

Declustering techniques reduce query response times through parallel I/O by distributing data among multiple devices. Most of the research on declustering is targeted at spatial range queries and investigates schemes with low additive error. Recently, declustering using replication is proposed to reduce the additive overhead. Replication significantly reduces retrieval cost of arbitrary queries. In this paper, we propose a disk allocation and retrieval mechanism for arbitrary queries based on design theory. Using proposed c-copy replicated declustering scheme, (c - 1)k/sup 2/ + ck buckets can be retrieved using at most k disk accesses. Retrieval algorithm is very efficient and is asymptotically optimal with /spl Theta/(|Q|) complexity for a query Q. In addition to the deterministic worst-case bound and efficient retrieval, proposed algorithm handles nonuniform data, high dimensions, supports incremental declustering and has good fault-tolerance property.

Constrained declustering

Declustering have attracted a lot of interest over the last few years. Except for a few cases it is not possible to find declustering schemes that are optimal for all spatial range queries. As a result of this, most of the research on declustering have focused on finding schemes with low worst case additive error. However, additive error based schemes have many limitations including lack of progressive guarantees and existence of small nonoptimal queries. In this paper, we take a different approach and investigate schemes that provide progressive guarantees. We investigate the threshold k such that all spatial range queries with /spl les/ k buckets are optimal. By dividing a query into nonoverlapping rectangles each with /spl les/ k buckets the guarantees of threshold can be extended to larger queries. Theoretical analysis shows that threshold k is bounded above by N/2 for N-by-N declustering system with N disks. We propose a number-theoretic threshold algorithm. Experimental results show that proposed algorithm returns schemes with high threshold and low worst-case additive error.

Integrated Maximum Flow Algorithm for Optimal Response Time Retrieval of Replicated Data

Efficient retrieval of replicated data from multiple disks is a challenging problem. Traditional retrieval techniques assume that replication is done at a single site using homogeneous disk arrays having no initial load or network delay. Recently, generalized retrieval algorithms are proposed to cover heterogeneous disk arrays, initial loads, and network delays. Generalized retrieval algorithms achieve the optimal response time retrieval schedule by performing multiple runs of a maximum flow algorithm. Since the maximum flow algorithm is used as a black box technique, flow values of the previous runs cannot be conserved to speed up the process. In this paper, we propose integrated maximum flow algorithms for the generalized optimal response time retrieval problem. Our first algorithm uses Ford-Fulkerson method and the second algorithm uses Push-relabel algorithm. Besides the sequential implementations, a multi-threaded version of the push-relabel algorithm is also implemented. Proposed algorithms are investigated using various replication schemes, query types, query loads, disk specifications, and system delays. Experimental results show that the sequential integrated push-relabel algorithm runs up to 2.5X faster than the black box version. Furthermore, parallel integrated push-relabel implementation achieves up to 1.7X speed up (~1.2X on average) over the sequential algorithm using two threads, which makes the integrated algorithm up to 4.25X (~3X on average) faster than its black box counterpart.

Approximating the Number of Active Nodes Behind a NAT Device

Network Address Translation (NAT) is used for various reasons on the Internet and hides the IP address and number of nodes behind the NAT device. Although many applications benefit from the knowledge of number of active nodes behind a NAT device, existing schemes are limited. In this paper, we use TCP timestamp option to count the number of active nodes. Timestamp option includes current timestamp of the machine in the TCP packet. We propose an efficient scheme that counts the number of machines approximately using clustering of timestamps. We use least-squares line fit of timestamp values and convex hulls to efficiently maintain the crucial information about existing clusters. Proposed scheme is online and requires minimal resources. We have investigated various aspects of the scheme to improve its performance. Using a developed tool to send packets, we have observed that the proposed scheme approximates the number of machines that send more than threshold number of packets well. Real experiments validate the proposed scheme.

Equivalent Disk Allocations

Declustering techniques reduce query response times through parallel I/O by distributing data among multiple devices. Except for a few cases, it is not possible to find declustering schemes that are optimal for all spatial range queries. As a result of this, most of the research on declustering have focused on finding schemes with low worst case additive error. Number-theoretic declustering techniques provide low additive error and high threshold. In this paper, we investigate equivalent disk allocations and focus on number-theoretic declustering. Most of the number-theoretic disk allocations are equivalent and provide the same additive error and threshold. Investigation of equivalent allocations simplifies schemes to find allocations with desirable properties. By keeping one of the equivalent disk allocations, we can reduce the complexity of searching for good disk allocations under various criteria such as additive error and threshold. Using proposed scheme, we were able to collect the most extensive experimental results on additive error and threshold in 2, 3, and 4 dimensions.