3,592 research outputs found
Structural Analysis of Network Traffic Matrix via Relaxed Principal Component Pursuit
The network traffic matrix is widely used in network operation and
management. It is therefore of crucial importance to analyze the components and
the structure of the network traffic matrix, for which several mathematical
approaches such as Principal Component Analysis (PCA) were proposed. In this
paper, we first argue that PCA performs poorly for analyzing traffic matrix
that is polluted by large volume anomalies, and then propose a new
decomposition model for the network traffic matrix. According to this model, we
carry out the structural analysis by decomposing the network traffic matrix
into three sub-matrices, namely, the deterministic traffic, the anomaly traffic
and the noise traffic matrix, which is similar to the Robust Principal
Component Analysis (RPCA) problem previously studied in [13]. Based on the
Relaxed Principal Component Pursuit (Relaxed PCP) method and the Accelerated
Proximal Gradient (APG) algorithm, we present an iterative approach for
decomposing a traffic matrix, and demonstrate its efficiency and flexibility by
experimental results. Finally, we further discuss several features of the
deterministic and noise traffic. Our study develops a novel method for the
problem of structural analysis of the traffic matrix, which is robust against
pollution of large volume anomalies.Comment: Accepted to Elsevier Computer Network
Understanding Android Obfuscation Techniques: A Large-Scale Investigation in the Wild
In this paper, we seek to better understand Android obfuscation and depict a
holistic view of the usage of obfuscation through a large-scale investigation
in the wild. In particular, we focus on four popular obfuscation approaches:
identifier renaming, string encryption, Java reflection, and packing. To obtain
the meaningful statistical results, we designed efficient and lightweight
detection models for each obfuscation technique and applied them to our massive
APK datasets (collected from Google Play, multiple third-party markets, and
malware databases). We have learned several interesting facts from the result.
For example, malware authors use string encryption more frequently, and more
apps on third-party markets than Google Play are packed. We are also interested
in the explanation of each finding. Therefore we carry out in-depth code
analysis on some Android apps after sampling. We believe our study will help
developers select the most suitable obfuscation approach, and in the meantime
help researchers improve code analysis systems in the right direction
States, trends, and future of aquaponics research
As an environmentally-friendly aquaculture and planting system, aquaponics has attracted attention in various fields, such as fisheries, agriculture, and ecology. The existing review qualitatively described the development and challenges of aquaponics but lacked data support. This study selected 513 related documents (2000-2019) in the Web of Science database (WOS) to mine and quantitatively analyze its text data. The keyword co-occurrence network shows that the current aquaponics research mainly focuses on the system components, wastewater treatment, nutrient management, and system production. Research areas reflect obvious regional characteristics. China, the United States and Europe are dedicated to the application of new technologies, the optimization of system production, and the exploration of multiple roles. At present, the aquaponics development is facing many pressures from management and market. Future research requires more in-depth research in the system construction, nutrient management, and microbial community structure to provide a theoretical basis. Moreover, the identity construction within the conceptual framework of green infrastructure is a research direction worth exploring to solve low social recognition for aquaponics
- …