N-opcode analysis for android malware classification and categorization

Malware detection is a growing problem particularly on the Android mobile platform due to its increasing popularity and accessibility to numerous third party app markets. This has also been made worse by the increasingly sophisticated detection avoidance techniques employed by emerging malware families. This calls for more effective techniques for detection and classification of Android malware. Hence, in this paper we present an n-opcode analysis based approach that utilizes machine learning to classify and categorize Android malware. This approach enables automated feature discovery that eliminates the need for applying expert or domain knowledge to define the needed features. Our experiments on 2520 samples that were performed using up to 10-gram opcode features showed that an f-measure of 98% is achievable using this approach.

Dynalog: an automated dynamic analysis framework for characterizing android applications

Android is becoming ubiquitous and currently has the largest share of the mobile OS market with billions of application downloads from the official app market. It has also become the platform most targeted by mobile malware that are becoming more sophisticated to evade state-of-the-art detection approaches. Many Android malware families employ obfuscation techniques in order to avoid detection and this may defeat static analysis based approaches. Dynamic analysis on the other hand may be used to overcome this limitation. Hence in this paper we propose DynaLog, a dynamic analysis based framework for characterizing Android applications. The framework provides the capability to analyse the behaviour of applications based on an extensive number of dynamic features. It provides an automated platform for mass analysis and characterization of apps that is useful for quickly identifying and isolating malicious applications. The DynaLog framework leverages existing open source tools to extract and log high level behaviours, API calls, and critical events that can be used to explore the characteristics of an application, thus providing an extensible dynamic analysis platform for detecting Android malware. DynaLog is evaluated using real malware samples and clean applications demonstrating its capabilities for effective analysis and detection of malicious applications.

Towards automated Android app collusion detection

Android OS supports multiple communication methods between apps. This opens the possibility to carry out threats in a collaborative fashion, c.f. the Soundcomber example from 2011. In this paper we provide a concise definition of collusion and report on a number of automated detection approaches, developed in co-operation with Intel Security.

A cross-sectional evaluation of community pharmacists’ perceptions of intermediate care and medicines management across the healthcare interface

Background Despite the importance placed on the concept of the multidisciplinary team in relation to intermediate care (IC), little is known about community pharmacists’ (CPs) involvement. 
Objective To determine CPs’ awareness of and involvement with IC services, perceptions of the transfer of patients’ medication information between healthcare settings and views of the development of a CP–IC service. 
Setting Community pharmacies in Northern Ireland. 
Methods A postal questionnaire, informed by previous qualitative work was developed and piloted. 
Main outcome measure CPs’ awareness of and involvement with IC. Results The response rate was 35.3 % (190/539). Under half (47.4 %) of CPs ‘agreed/strongly agreed’ that they understood the term ‘intermediate care’. Three quarters of respondents were either not involved or unsure if they were involved with providing services to IC. A small minority (1.2 %) of CPs reported that they received communication regarding medication changes made in hospital or IC settings ‘all of the time’. Only 9.5 and 0.5 % of respondents ‘strongly agreed’ that communication from hospital and IC, respectively, was sufficiently detailed. In total, 155 (81.6 %) CPs indicated that they would like to have greater involvement with IC services. ‘Current workload’ was ranked as the most important barrier to service development.
Conclusion It was revealed that CPs had little awareness of, or involvement with, IC. Communication of information relating to patients’ medicines between settings was perceived as insufficient, especially between IC and community pharmacy settings. CPs demonstrated willingness to be involved with IC and services aimed at bridging the communication gap between healthcare settings.

The role of Lean at the interface with between operations management and applied services within a large aerospace organisation: a boundary spanning perspective

Increased complexity in large design and manufacturing organisations requires improvements at the operations management (OM)–applied service (AS) interface areas to improve project effectiveness. The aim of this paper is explore the role of Lean in improving the longitudinal efficiency of the OM–AS interface within a large aerospace organisation using Lean principles and boundary spanning theory. The methodology was an exploratory longitudinal case approach including exploratory interviews (n = 21), focus groups (n = 2), facilitated action-research workshops (n = 2) and two trials or experiments using longitudinal data involving both OM and AS personnel working at the interface. The findings draw upon Lean principles and boundary spanning theory to guide and interpret the findings. It was found that misinterpretation, and forced implementation, of OM-based Lean terminology and practice in the OM–AS interface space led to delays and misplaced resources. Rather both OM and AS staff were challenged to develop a cross boundary understanding of Lean-based boundary (knowledge) objects in interpreting OM requests. The longitudinal findings from the experiments showed that the development of Lean Performance measurements and lean Value Stream constructs was more successful when these Lean constructs were treated as boundary (knowledge) objects requiring transformation over time to orchestrate improved effectiveness and in leading to consistent terminology and understanding between the OM–AS boundary spanning team.