Mining permission patterns for contrasting clean and malicious android applications

An Android application uses a permission system to regulate the access to system resources and users' privacy-relevant information. Existing works have demonstrated several techniques to study the required permissions declared by the developers, but little attention has been paid towards used permissions. Besides, no specific permission combination is identified to be effective for malware detection. To fill these gaps, we have proposed a novel pattern mining algorithm to identify a set of contrast permission patterns that aim to detect the difference between clean and malicious applications. A benchmark malware dataset and a dataset of 1227 clean applications has been collected by us to evaluate the performance of the proposed algorithm. Valuable findings are obtained by analyzing the returned contrast permission patterns. © 2013 Elsevier B.V. All rights reserved.

Contrasting permission patterns between clean and malicious android applications

The Android platform uses a permission system model to allow users and developers to regulate access to private information and system resources required by applications. Permissions have been proved to be useful for inferring behaviors and characteristics of an application. In this paper, a novel method to extract contrasting permission patterns for clean and malicious applications is proposed. Contrary to existing work, both required and used permissions were considered when discovering the patterns. We evaluated our methodology on a clean and a malware dataset, each comprising of 1227 applications. Our empirical results suggest that our permission patterns can capture key differences between clean and malicious applications, which can assist in characterizing these two types of applications.

Orientation integration in detection and discrimination of contrast-modulated patterns

Orientation detection and discrimination thresholds were measured for Gabor ‘envelopes’ formed from contrast-modulation of luminance ‘carriers’. Consistent with previous research differences between carrier and envelope orientation had no effect on sensitivity to envelopes. Using plaid carriers in which the proportion of contrast modulation ‘carried’ by each plaid component was systematically manipulated, it was shown that this tolerance to carrier-envelope orientation difference reflects linear summation across orientation indicative of a single second-stage channel coding for contrast-defined structure. That contrast envelopes did not exhibit linear summation across spatial-frequency, nor across combinations of orientation and spatial-frequency differences, suggests that these second-order channels operate only within certain spatial scales. Using arrays of Gabor micropatterns as carriers in which the orientation distribution of the carriers was manipulated independently of the difference between envelope orientation and mean carrier orientation, it was further demonstrated that the locus of orientation integration must occur prior to envelope detection. In the context of two-stage models that incorporate a non-linearity between the stages, the pattern of results obtained is consistent with the operation of an orientation pooling process between first-stage and second-stage channels, analogous to having all filters of the first-stage feed into all filters of the second-stage within the same spatial-frequency band.

An agent-based hybrid framework for database mining

While knowledge discovery in databases (KDD) is defined as an iterative sequence of the following steps: data pre-processing, data mining, and post data mining, a significant amount of research in data mining has been done, resulting in a variety of algorithms and techniques for each step. However, a single data-mining technique has not been proven appropriate for every domain and data set. Instead, several techniques may need to be integrated into hybrid systems and used cooperatively during a particular data-mining operation. That is, hybrid solutions are crucial for the success of data mining. This paper presents a hybrid framework for identifying patterns from databases or multi-databases. The framework integrates these techniques for mining tasks from an agent point of view. Based on the experiments conducted, putting different KDD techniques together into the agent-based architecture enables them to be used cooperatively when needed. The proposed framework provides a highly flexible and robust data-mining platform and the resulting systems demonstrate emergent behaviors although it does not improve the performance of individual KDD techniques.

The role of local grouping and global orientation contrast in perception of orientation-modulated textures

We explored the contribution to perception of orientation-modulated textures of visual processes selective either for orientation contrast or orientation grouping. To distinguish between these two processes we manipulated the axis of local grouping of texture elements independently of the direction of global orientation modulation. The general question posed was whether visibility of texture structure (measured as threshold for discriminating spatial-frequency of texture structure) is dependent on the magnitude of orientation contrast, strength and direction of local grouping, or some combination of the two. We demonstrated that the factor of primary importance is the amplitude of global orientation contrast rather than the presence of local grouping content. Using orientation-interleaved textures (containing two superimposed textures modulated around orthogonal orientations), we further showed that orientation single-opponent processes are a more likely candidate for detecting orientation contrast than double-opponent processes.

The right to convert exploration licences to mining leases in Australia: a proposed national uniform model

In this article, the authors raise an important proposal for reform to Australia's mining legislation: a nationally-consistent model providing exploration licence holders with a legislative right to be granted a mining lease. This proposed national model will be designed to reflect the present Western Australian system - Western Australia being the only jurisdiction to provide exploration licence holders with the express right to be granted a mining lease on application. The authors believe that the Western Australian system should provide the basis for a national legislative model, given that it is designed to balance appropriately the interests of companies wanting a right to mine to recoup the costs involved in exploring for minerals, and the interests of the public in ensuring that exploration and mining is conducted
reasonably.

Chromatic and luminance losses with multiple sclerosis and optic neuritis measured using dynamic random luminance contrast noise

We measured thresholds for detecting changes in colour and in luminance contrast in observers with multiple sclerosis (MS) and/or optic neuritis (ON) to determine whether reduced sensitivity occurs principally in red-green or blue-yellow second-stage chromatic channels or in an achromatic channel. Colour thresholds for the observers with MS/ON were higher in the red-green direction than in the blue-yellow direction, indicating greater levels of red-green loss than blue-yellow loss. Achromatic thresholds were raised less than either red-green or blue-yellow thresholds, showing less luminance-contrast loss than chromatic loss. With the MS/ON observers, blue-yellow and red-green thresholds were positively correlated but increasing impairment was associated with more rapid changes in red-green thresholds than blue-yellow thresholds. These findings indicate that demyelinating disease selectively reduces sensitivity to colour vision over luminance vision and red-green colours over blue-yellow colours.

Analyzing security protocols using association rule mining

Current studies to analyzing security protocols using formal methods require users to predefine authentication goals. Besides, they are unable to discover potential correlations between secure messages. This research attempts to analyze security protocols using data mining. This is done by extending the idea of association rule mining and converting the verification of protocols into computing the frequency and confidence of inconsistent secure messages. It provides a novel and efficient way to analyze security protocols and find out potential correlations between secure messages. The conducted experiments demonstrate our approaches.

Spatio-temporal selectivity of loss of colour and luminance contrast sensitivity with mutiple sclerosis and optic neuritis

Colour and luminance-contrast thresholds were measured in the presence of dynamic Random Luminance-contrast Masking (RLM) in individuals who had had past diagnoses of optic neuritis (ON) some of whom have progressed to a diagnosis of multiple sclerosis (MS). To explore the spatio-temporal selectivity of chromatic and luminance losses in MS/ON, thresholds were measured using three different sizes and modulation rates of the RLM displays: small checks modulating slowly, medium-sized checks with moderate modulation and large checks modulating rapidly. The colour of the chromatic stimuli used were specified in a cone-excitation space to measure relative impairments in red–green and blue–yellow chromatic channels. These observers showed chromatic thresholds along the L/(L + M) axis that were higher than those along the S-cone axis for all display sizes/modulation rates and both red-green and blue-yellow colour thresholds were higher than luminance-contrast thresholds. The principal change in thresholds with spatio-temporal changes in the display was a reduction in thresholds for L/(L + M) and S-cones with increasing check size and modulation rate. However, luminance contrast thresholds did not change with display size/rate. These results are consistent with MS/ON selectively affecting processing in colour pathways rather than in the magnocellular pathway, and that within the colour pathways neurones with opposed L- and M-cone inputs are more damaged than colour-opponent neurons with input from S-cones.

An incremental FP-growth web content mining and its application in preference identification

This paper presents a real application of Web-content mining using an incremental FP-Growth approach. We firstly restructure the semi-structured data retrieved from the web pages of Chinese car market to fit into the local database, and then employ an incremental algorithm to discover the association rules for the identification of car preference. To find more general regularities, a method of attribute-oriented induction is also utilized to find customer’s consumption preferences. Experimental results show some interesting consumption preference patterns that may be beneficial for the government in making policy to encourage and guide car consumption.

Agents and stream data mining: a new perspective

Many organizations struggle with the massive amount of data they collect. Today, data does more than serve as the ingredients for churning out statistical reports. They help support efficient operations in many organizations, and to some extent, data provide the competitive intelligence organizations need to survive in today's economy. Data mining can't always deliver timely and relevant results because data are constantly changing. However, stream-data processing might be more effective, judging by the Matrix project.

Mining frequent patterns for AMP-activated protein kinase regulation on skeletal muscle

Background
AMP-activated protein kinase (AMPK) has emerged as a significant signaling intermediary that regulates metabolisms in response to energy demand and supply. An investigation into the degree of activation and deactivation of AMPK subunits under exercise can provide valuable data for understanding AMPK. In particular, the effect of AMPK on muscle cellular energy status makes this protein a promising pharmacological target for disease treatment. As more AMPK regulation data are accumulated, data mining techniques can play an important role in identifying frequent patterns in the data. Association rule mining, which is commonly used in market basket analysis, can be applied to AMPK regulation.

Results
This paper proposes a framework that can identify the potential correlation, either between the state of isoforms of α, β and γ subunits of AMPK, or between stimulus factors and the state of isoforms. Our approach is to apply item constraints in the closed interpretation to the itemset generation so that a threshold is specified in terms of the amount of results, rather than a fixed threshold value for all itemsets of all sizes. The derived rules from experiments are roughly analyzed. It is found that most of the extracted association rules have biological meaning and some of them were previously unknown. They indicate direction for further research.

Conclusion
Our findings indicate that AMPK has a great impact on most metabolic actions that are related to energy demand and supply. Those actions are adjusted via its subunit isoforms under specific physical training. Thus, there are strong co-relationships between AMPK subunit isoforms and exercises. Furthermore, the subunit isoforms are correlated with each other in some cases. The methods developed here could be used when predicting these essential relationships and enable an understanding of the functions and metabolic pathways regarding AMPK.

Mining frequent itemsets for protein kinase regulation

Protein kinases, a family of enzymes, have been viewed as an important signaling intermediary by living organisms for regulating critical biological processes such as memory, hormone response and cell growth. The
unbalanced kinases are known to cause cancer and other diseases. With the increasing efforts to collect, store and disseminate information about the entire kinase family, it not only leads to valuable data set to understand cell regulation but also poses a big challenge to extract valuable knowledge about metabolic pathway from the data. Data mining techniques that have been widely used to find frequent patterns in large datasets can be extended and adapted to kinase data as well. This paper proposes a framework for mining frequent itemsets from the collected kinase dataset. An experiment using AMPK regulation data demonstrates that our approaches are useful and efficient in analyzing kinase regulation data.

Foreign debt and financial hedging : evidence from Australia

We investigate the role of foreign currency denominated debt (FCDD) as a natural hedging instrument using a sample of Australian firms. Our results show that the incidence of foreign debt use among industrial sector firms is associated with a lower level of exchange rate exposure. The practice of issuing foreign debt within the industrial sector also conforms better to the hypothesis that firms do so to satisfy a demand for hedging. In contrast, although the incidence of foreign debt issues is higher in the resource/mining sector, the underlying motive for such arises from a demand for financing.