A New Android Malware Detection Method Using Bayesian Classification

Mobile malware has been growing in scale and complexity as smartphone usage continues to rise. Android has surpassed other mobile platforms as the most popular whilst also witnessing a dramatic increase in malware targeting the platform. A worrying trend that is emerging is the increasing sophistication of Android malware to evade detection by traditional signature-based scanners. As such, Android app marketplaces remain at risk of hosting malicious apps that could evade detection before being downloaded by unsuspecting users. Hence, in this paper we present an effective approach to alleviate this problem based on Bayesian classification models obtained from static code analysis. The models are built from a collection of code and app characteristics that provide indicators of potential malicious activities. The models are evaluated with real malware samples in the wild and results of experiments are presented to demonstrate the effectiveness of the proposed approach.

Smartphone and GPS technology for freeroaming dog population surveillance -a methodological study (Studio metodologico sull’applicazione di smartphone e tecnologia GPS alla sorveglianza delle popolazioni di cani vaganti)

Free-roaming dogs (FRD) represent a potential threat to the quality of life in cities from an ecological, social and public health point of view. One of the most urgent concerns is the role of uncontrolled dogs as reservoirs of infectious diseases transmittable to humans and, above all, rabies. An estimate of the FRD population size and characteristics in a given area is the first step for any relevant intervention programme. Direct count methods are still prominent because of their non-invasive approach, information technologies can support such methods facilitating data collection and allowing for a more efficient data handling. This paper presents a new framework for data collection using a topological algorithm implemented as ArcScript in ESRI® ArcGIS software, which allows for a random selection of the sampling areas. It also supplies a mobile phone application for Android® operating system devices which integrates Global Positioning System (GPS) and Google Maps™. The potential of such a framework was tested in 2 Italian regions. Coupling technological and innovative solutions associated with common counting methods facilitate data collection and transcription. It also paves the way to future applications, which could support dog population management systems.

A neural network based tool for semi-automatic code transformation

A neural network based tool has been developed to assist in the process of code transformation. The tool offers advice on appropriate transformations within a knowledge-driven, semi-automatic parallelisation environment. We have identified the essential characteristics of codes relevant to loop transformations. A Kohonen network is used to discover structure in the characterised codes thus revealing new knowledge that may be brought to bear on the mapping between codes and transformations or transformation sequences. A transform selector based on this process has been developed and successfully applied to the parallelisation of sequential codes.

Generic SoC QR Array Processor for Adaptive Beamforming

A generic architecture for implementing a QR array processor in silicon is presented. This improves on previous research by considerably simplifying the derivation of timing schedules for a QR system implemented as a folded linear array, where account has to be taken of processor cell latency and timing at the detailed circuit level. The architecture and scheduling derived have been used to create a generator for the rapid design of System-on-a-Chip (SoC) cores for QR decomposition. This is demonstrated through the design of a single-chip architecture for implementing an adaptive beamformer for radar applications. Published as IEEE Trans Circuits and Systems Part II, Analog and Digital Signal Processing, April 2003 NOT Express Briefs. Parts 1 and II of Journal reorganised since then into Regular Papers and Express briefs

Continuous MLL-ENL expression is necessary to establish a "Hox Code" and maintain immortalization of hematopoietic progenitor cells

The t[(11;19)(p22;q23)] translocation, which gives rise to the MLL-ENL fusion protein, is commonly found in infant acute leukemias of both the myeloid and lymphoid lineage. To investigate the molecular mechanism of immortalization by MLL-ENL we established a Tet-regulatable system of MLL-ENL expression in primary hematopoietic progenitor cells. Immortalized myeloid cell lines were generated, which are dependent on continued MLL-ENL expression for their survival and proliferation. These cells either terminally differentiate or die when MLL-ENL expression is turned off with doxycycline. The expression profile of all 39 murine Hox genes was analyzed in these cells by real-time quantitative PCR. This analysis showed that loss of MLL-ENL was accompanied by a reduction in the expression of multiple Hoxa genes. By comparing these changes with Hox gene expression in cells induced to differentiate with granulocyte colony-stimulating factor, we show for the first time that reduced Hox gene expression is specific to loss of MLL-ENL and is not a consequence of differentiation. Our data also suggest that the Hox cofactor Meis-2 can substitute for Meis-1 function. Thus, MLL-ENL is required to initiate and maintain immortalization of myeloid progenitors and may contribute to leukemogenesis by aberrantly sustaining the expression of a "Hox code" consisting of Hoxa4 to Hoxa11.