Excellence in Research and Innovation for Humanity

International Science Index

Commenced in January 1999 Frequency: Monthly Edition: International Paper Count: 7

7
10007209
ParkedGuard: An Efficient and Accurate Parked Domain Detection System Using Graphical Locality Analysis and Coarse-To-Fine Strategy
Abstract:
As world wild internet has non-stop developments, making profit by lending registered domain names emerges as a new business in recent years. Unfortunately, the larger the market scale of domain lending service becomes, the riskier that there exist malicious behaviors or malwares hiding behind parked domains will be. Also, previous work for differentiating parked domain suffers two main defects: 1) too much data-collecting effort and CPU latency needed for features engineering and 2) ineffectiveness when detecting parked domains containing external links that are usually abused by hackers, e.g., drive-by download attack. Aiming for alleviating above defects without sacrificing practical usability, this paper proposes ParkedGuard as an efficient and accurate parked domain detector. Several scripting behavioral features were analyzed, while those with special statistical significance are adopted in ParkedGuard to make feature engineering much more cost-efficient. On the other hand, finding memberships between external links and parked domains was modeled as a graph mining problem, and a coarse-to-fine strategy was elaborately designed by leverage the graphical locality such that ParkedGuard outperforms the state-of-the-art in terms of both recall and precision rates.
6
10004328
Impact of Stack Caches: Locality Awareness and Cost Effectiveness
Abstract:

Treating data based on its location in memory has received much attention in recent years due to its different properties, which offer important aspects for cache utilization. Stack data and non-stack data may interfere with each other’s locality in the data cache. One of the important aspects of stack data is that it has high spatial and temporal locality. In this work, we simulate non-unified cache design that split data cache into stack and non-stack caches in order to maintain stack data and non-stack data separate in different caches. We observe that the overall hit rate of non-unified cache design is sensitive to the size of non-stack cache. Then, we investigate the appropriate size and associativity for stack cache to achieve high hit ratio especially when over 99% of accesses are directed to stack cache. The result shows that on average more than 99% of stack cache accuracy is achieved by using 2KB of capacity and 1-way associativity. Further, we analyze the improvement in hit rate when adding small, fixed, size of stack cache at level1 to unified cache architecture. The result shows that the overall hit rate of unified cache design with adding 1KB of stack cache is improved by approximately, on average, 3.9% for Rijndael benchmark. The stack cache is simulated by using SimpleScalar toolset.

5
10003998
A Survey on Data-Centric and Data-Aware Techniques for Large Scale Infrastructures
Abstract:
Large scale computing infrastructures have been widely developed with the core objective of providing a suitable platform for high-performance and high-throughput computing. These systems are designed to support resource-intensive and complex applications, which can be found in many scientific and industrial areas. Currently, large scale data-intensive applications are hindered by the high latencies that result from the access to vastly distributed data. Recent works have suggested that improving data locality is key to move towards exascale infrastructures efficiently, as solutions to this problem aim to reduce the bandwidth consumed in data transfers, and the overheads that arise from them. There are several techniques that attempt to move computations closer to the data. In this survey we analyse the different mechanisms that have been proposed to provide data locality for large scale high-performance and high-throughput systems. This survey intends to assist scientific computing community in understanding the various technical aspects and strategies that have been reported in recent literature regarding data locality. As a result, we present an overview of locality-oriented techniques, which are grouped in four main categories: application development, task scheduling, in-memory computing and storage platforms. Finally, the authors include a discussion on future research lines and synergies among the former techniques.
4
10003344
Pattern Recognition Based Prosthesis Control for Movement of Forearms Using Surface and Intramuscular EMG Signals
Abstract:

Myoelectric control system is the fundamental component of modern prostheses, which uses the myoelectric signals from an individual’s muscles to control the prosthesis movements. The surface electromyogram signal (sEMG) being noninvasive has been used as an input to prostheses controllers for many years. Recent technological advances has led to the development of implantable myoelectric sensors which enable the internal myoelectric signal (MES) to be used as input to these prostheses controllers. The intramuscular measurement can provide focal recordings from deep muscles of the forearm and independent signals relatively free of crosstalk thus allowing for more independent control sites. However, little work has been done to compare the two inputs. In this paper we have compared the classification accuracy of six pattern recognition based myoelectric controllers which use surface myoelectric signals recorded using untargeted (symmetric) surface electrode arrays to the same controllers with multichannel intramuscular myolectric signals from targeted intramuscular electrodes as inputs. There was no significant enhancement in the classification accuracy as a result of using the intramuscular EMG measurement technique when compared to the results acquired using the surface EMG measurement technique. Impressive classification accuracy (99%) could be achieved by optimally selecting only five channels of surface EMG.

3
9999125
SC-LSH: An Efficient Indexing Method for Approximate Similarity Search in High Dimensional Space
Abstract:

Locality Sensitive Hashing (LSH) is one of the most promising techniques for solving nearest neighbour search problem in high dimensional space. Euclidean LSH is the most popular variation of LSH that has been successfully applied in many multimedia applications. However, the Euclidean LSH presents limitations that affect structure and query performances. The main limitation of the Euclidean LSH is the large memory consumption. In order to achieve a good accuracy, a large number of hash tables is required. In this paper, we propose a new hashing algorithm to overcome the storage space problem and improve query time, while keeping a good accuracy as similar to that achieved by the original Euclidean LSH. The Experimental results on a real large-scale dataset show that the proposed approach achieves good performances and consumes less memory than the Euclidean LSH.

2
6704
Loop-free Local Path Repair Strategy for Directed Diffusion
Abstract:
This paper proposes an implementation for the directed diffusion paradigm aids in studying this paradigm-s operations and evaluates its behavior according to this implementation. The directed diffusion is evaluated with respect to the loss percentage, lifetime, end-to-end delay, and throughput. From these evaluations some suggestions and modifications are proposed to improve the directed diffusion behavior according to this implementation with respect to these metrics. The proposed modifications reflect the effect of local path repair by introducing a technique called Loop-free Local Path Repair (LLPR) which improves the directed diffusion behavior especially with respect to packet loss percentage by about 92.69%. Also LLPR improves the throughput and end-to-end delay by about 55.31% and 14.06% respectively, while the lifetime decreases by about 29.79%.
1
11933
Improving Cache Memory Utilization
Abstract:

In this paper, an efficient technique is proposed to manage the cache memory. The proposed technique introduces some modifications on the well-known set associative mapping technique. This modification requires a little alteration in the structure of the cache memory and on the way by which it can be referenced. The proposed alteration leads to increase the set size virtually and consequently to improve the performance and the utilization of the cache memory. The current mapping techniques have accomplished good results. In fact, there are still different cases in which cache memory lines are left empty and not used, whereas two or more processes overwrite the lines of each other, instead of using those empty lines. The proposed algorithm aims at finding an efficient way to deal with such problem.

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