Efficient real-time face detection for high resolution surveillance applications

This paper presents an efficient face detection method suitable for real-time surveillance applications. Improved efficiency is achieved by constraining the search window of an AdaBoost face detector to pre-selected regions. Firstly, the proposed method takes a sparse grid of sample pixels from the image to reduce whole image scan time. A fusion of foreground segmentation and skin colour segmentation is then used to select candidate face regions. Finally, a classifier-based face detector is applied only to selected regions to verify the presence of a face (the Viola-Jones detector is used in this paper). The proposed system is evaluated using 640 x 480 pixels test images and compared with other relevant methods. Experimental results show that the proposed method reduces the detection time to 42 ms, where the Viola-Jones detector alone requires 565 ms (on a desktop processor). This improvement makes the face detector suitable for real-time applications. Furthermore, the proposed method requires 50% of the computation time of the best competing method, while reducing the false positive rate by 3.2% and maintaining the same hit rate.

Perceived social support and community adaptation in schizophrenia

Prompted by the continuing transition to community care, mental health nurses are considering the role of social support in community adaptation. This article demonstrates the importance of distinguishing between kinds of social support and presents findings from the first round data of a longitudinal study of community adaptation in 156 people with schizophrenia conducted in Brisbane, Australia. All clients were interviewed using the relevant subscales of the Diagnostic Interview Schedule to confirm a primary diagnosis of schizophrenia. The study set out to investigate the relationship between community adaptation and social support. Community adaptation was measured with the Brief Psychiatric Rating Scale (BPRS), the Life Skills Profile (LSP) and measures of dissatisfaction with life and problems in daily living developed by the authors. Social support was measured with the Arizona Social Support Interview Schedule (ASSIS). The BPRS and ASSIS were incorporated into a client interview conducted by trained interviewers. The LSP was completed on each client by an informal carer (parent, relative or friend) or a professional carer (case manager or other health professional) nominated by the client. Hierarchical regression analysis was used to examine the relationship between community adaptation and four sets of social support variables. Given the order in which variables were entered in regression equations, a set of perceived social support variables was found to account for the largest unique variance of four measures of community adaptation in 96 people with schizophrenia for whom complete data are available from the first round of the three-wave longitudinal study. A set of the subjective experiences of the clients accounted for the largest unique variance in measures of symptomatology, life skills, dissatisfaction with life, and problems in daily living. Sets of community support, household support and functional variables accounted for less variance. Implications for mental health nursing practice are considered.

Monitoring smartphones for anomaly detection

In this paper we demonstrate how to monitor a smartphone running Symbian operating system and Windows Mobile in order to extract features for anomaly detection. These features are sent to a remote server because running a complex intrusion detection system on this kind of mobile device still is not feasible due to capability and hardware limitations. We give examples on how to compute relevant features and introduce the top ten applications used by mobile phone users based on a study in 2005. The usage of these applications is recorded by a monitoring client and visualized. Additionally, monitoring results of public and self-written malwares are shown. For improving monitoring client performance, Principal Component Analysis was applied which lead to a decrease of about 80 of the amount of monitored features.

Modeling and detection of complex attacks

A complex attack is a sequence of temporally and spatially separated legal and illegal actions each of which can be detected by various IDS but as a whole they constitute a powerful attack. IDS fall short of detecting and modeling complex attacks therefore new methods are required. This paper presents a formal methodology for modeling and detection of complex attacks in three phases: (1) we extend basic attack tree (AT) approach to capture temporal dependencies between components and expiration of an attack, (2) using enhanced AT we build a tree automaton which accepts a sequence of actions from input message streams from various sources if there is a traversal of an AT from leaves to root, and (3) we show how to construct an enhanced parallel automaton that has each tree automaton as a subroutine. We use simulation to test our methods, and provide a case study of representing attacks in WLANs.

SERS substrate for detection of explosives

A novel gold coated femtosecond laser nanostructured sapphire surface – an “optical nose” - based on surface-enhanced Raman spectroscopy (SERS) for detecting vapours of explosive substances was investigated. Four different nitroaromatic vapours at room temperature were tested. Sensor responses were unambiguous and showed response in the range of 0.05 – 15 uM at 25 °C. The laser fabricated substrate nanostructures produced up to an eight-fold increase in Raman signal over that observed on the unstructured portions of the substrate. This work demonstrates a simple sensing system that is compatible with commercial manufacturing practices to detect taggants in explosives which can undertake as part of an integrated security or investigative mission.

Risk factors for moderate and severe microbial keratitis in daily wear contact lens users

Objective: To establish risk factors for moderate and severe microbial keratitis among daily contact lens (CL) wearers in Australia. Design: A prospective, 12-month, population-based, case-control study. Participants: New cases of moderate and severe microbial keratitis in daily wear CL users presenting in Australia over a 12-month period were identified through surveillance of all ophthalmic practitioners. Case detection was augmented by record audits at major ophthalmic centers. Controls were users of daily wear CLs in the community identified using a national telephone survey. Testing: Cases and controls were interviewed by telephone to determine subject demographics and CL wear history. Multiple binary logistic regression was used to determine independent risk factors and univariate population attributable risk percentage (PAR%) was estimated for each risk factor.; Main Outcome Measures: Independent risk factors, relative risk (with 95% confidence intervals [CIs]), and PAR%. Results: There were 90 eligible moderate and severe cases related to daily wear of CLs reported during the study period. We identified 1090 community controls using daily wear CLs. Independent risk factors for moderate and severe keratitis while adjusting for age, gender, and lens material type included poor storage case hygiene 6.4× (95% CI, 1.9-21.8; PAR, 49%), infrequent storage case replacement 5.4× (95% CI, 1.5-18.9; PAR, 27%), solution type 7.2× (95% CI, 2.3-22.5; PAR, 35%), occasional overnight lens use (<1 night per week) 6.5× (95% CI, 1.3-31.7; PAR, 23%), high socioeconomic status 4.1× (95% CI, 1.2-14.4; PAR, 31%), and smoking 3.7× (95% CI, 1.1-12.8; PAR, 31%). Conclusions: Moderate and severe microbial keratitis associated with daily use of CLs was independently associated with factors likely to cause contamination of CL storage cases (frequency of storage case replacement, hygiene, and solution type). Other factors included occasional overnight use of CLs, smoking, and socioeconomic class. Disease load may be considerably reduced by attention to modifiable risk factors related to CL storage case practice.

SAIVT-QUT@TRECVid 2012 : interactive surveillance event detection

In this paper, we propose an approach which attempts to solve the problem of surveillance event detection, assuming that we know the definition of the events. To facilitate the discussion, we first define two concepts. The event of interest refers to the event that the user requests the system to detect; and the background activities are any other events in the video corpus. This is an unsolved problem due to many factors as listed below: 1) Occlusions and clustering: The surveillance scenes which are of significant interest at locations such as airports, railway stations, shopping centers are often crowded, where occlusions and clustering of people are frequently encountered. This significantly affects the feature extraction step, and for instance, trajectories generated by object tracking algorithms are usually not robust under such a situation. 2) The requirement for real time detection: The system should process the video fast enough in both of the feature extraction and the detection step to facilitate real time operation. 3) Massive size of the training data set: Suppose there is an event that lasts for 1 minute in a video with a frame rate of 25fps, the number of frames for this events is 60X25 = 1500. If we want to have a training data set with many positive instances of the event, the video is likely to be very large in size (i.e. hundreds of thousands of frames or more). How to handle such a large data set is a problem frequently encountered in this application. 4) Difficulty in separating the event of interest from background activities: The events of interest often co-exist with a set of background activities. Temporal groundtruth typically very ambiguous, as it does not distinguish the event of interest from a wide range of co-existing background activities. However, it is not practical to annotate the locations of the events in large amounts of video data. This problem becomes more serious in the detection of multi-agent interactions, since the location of these events can often not be constrained to within a bounding box. 5) Challenges in determining the temporal boundaries of the events: An event can occur at any arbitrary time with an arbitrary duration. The temporal segmentation of events is difficult and ambiguous, and also affected by other factors such as occlusions.

Community interventions for physical activity : the role of a new Cochrane systematic review

Introduction: Systematic reviews are essential in summarising the results of a range of research studies on a specific topic into a single report. They serve as a key source of evidence-based information to support and develop policy and practice for healthy communities. This presentation will examine a new review of community-wide strategies to increase population levels of physical activity and compare it to an earlier Community Guide Review (CGR) of Community-wide campaigns to increase physical activity which recommended community wide interventions. Methods: We registered a Cochrane Systematic Review (CSR) title, published a protocol and recently completed the review of Community-wide interventions to increase physical activity. We compared the definitions, design and findings of the CSR to the CGR. Results: The two reviews differed remarkably in their conclusions with the CGR recommending “strong evidence exists that community-wide campaigns are effective in increasing levels of physical activity”, and the new CSR stating “The body of evidence in this review does not support the hypothesis that multi-component community wide interventions effectively increase population levels of physical activity”. We observed that both reviews examined multi-component interventions as a “combined package”. Possible explanations for the different conclusions may be due to the definition of community (CSR defined community as “comprising those persons residing in a geographically defined community, such as a village, town, or city”, excluding interventions which were whole of state or country, and CGR as “a group of individuals who share one or more characteristics. The CSR utilised a logic model at various stages of the review process and explicitly defined a combination of strategies encompassed within the intervention. The CSR included 25 and CGR 10 studies, respectively. Six of the 10 studies that were included in CGR were excluded from the CSR due to issues relating to study design, intervention definition or duration. The two reviews also differ in function as the CSR seeks to summarise global evidence and included 7 studies in low-income countries, where as the CGR contained only studies deemed relevant to the USA context. Discussion: Differences in the findings between older and newer reviews can be due to a variety of factors. For example, in updating a review the definition of an intervention can be changed. Further, differences may also be due to improvements in the standards and methodologies for systematic reviews as well as the inclusion of newer studies. These factors need to be understood whenever differences between newer and older reviews are considered.

Methodological challenges in conducting a systematic review of community wide interventions to increase physical activity

Introduction: Evaluating the effectiveness of interventions designed to increase the physical activity in communities is often a difficult and complex task, requiring considerable expertise and investment, and often constrained by methodological limitations. These limitations, in turn, create additional challenges when these studies are used in systematic reviews as they hinder the confidence, precision and interpretation of results. The objective of this paper is to summarise the methodological challenges posed in conducting a systematic review of community-wide physical activity interventions to help inform those conducting future primary research and systematic reviews. Methods: We conducted a Cochrane systematic review of community-wide interventions to increase physical activity. We assessed the methodological quality of the included studies. We will investigate these in greater detail, particularly in relation to the potential impact on measures of effect, confidence in results, generalizability of results and general interpretation. Results: The systematic review was conducted and has been published in the Cochrane Library. A logic model was helpful in defining and interpreting the studies. Many studies of unsuitable study design were excluded; however several important methodological limitations of the primary studies evaluating community-wide physical activity interventions emerged. These included: - the failure to use validated tools to measure physical activity; - issues associated with pre and post test designs; - inadequate sampling of populations; - poor control groups; and - intervention and measurement protocols of inadequate duration. Although it is challenging to undertake rigorous evaluations of complex interventions, these issues result in significant uncertainty over the effectiveness of these interventions, and the possible factors required for a community-wide intervention to be successful. In particular, the combination of several of these limitations (e.g. un-validated tools, inadequate sampling, and short duration) is that studies may lack the sensitivity to detect any meaningful change. Multiple publications of findings for the same study also made interpretation difficult; however, interventions with parallel qualitative publications were helpful. Discussion: Evaluating community wide interventions to increase physical activity in a rigorous way is incredibly challenging. These findings reflect these challenges but have important ramifications for researchers conducting primary studies to determine the efficacy of such interventions, as well as for researchers conducting systematic reviews. This new review shows that the inadequacies of design and evaluation are continuing. It is hoped that the adoption of such suggestions may aid in the development of systematic reviews, but more importantly, in enabling translation of such findings into policy and practice.

Wife abuse : are we detecting it?

Our objective was to measure the prevalence of wife abuse in an urban teaching hospital family practice unit and compare this to the frequency of documentation by family physicians. A modified Conflicts Tactics Scale Questionnaire was administered to all female patients either married or common-law older than 16 years during the study period. The respective patients' charts were reviewed for documentation of wife abuse. Three hundred eighty-three charts were reviewed, and 275 surveys were completed (72% response rate). Physical and mental abuse were reported in 8% and 23%, respectively, of the respondents. Four percent of respondents had considered suicide. One percent of the charts had wife assault documented (p = 0.0001). Wife abuse is reported in at least 8% of our patients. There appear to be significant health risks to these women, including homicide, suicide, and rape. Family physician documentation of wife abuse was poor.

Static analysis of executables for collaborative malware detection on Android

Smartphones are getting increasingly popular and several malwares appeared targeting these devices. General countermeasures to smartphone malwares are currently limited to signature-based antivirus scanners which efficiently detect known malwares, but they have serious shortcomings with new and unknown malwares creating a window of opportunity for attackers. As smartphones become host for sensitive data and applications, extended malware detection mechanisms are necessary complying with the corresponding resource constraints. The contribution of this paper is twofold. First, we perform static analysis on the executables to extract their function calls in Android environment using the command readelf. Function call lists are compared with malware executables for classifying them with PART, Prism and Nearest Neighbor Algorithms. Second, we present a collaborative malware detection approach to extend these results. Corresponding simulation results are presented.

An Android application sandbox system for suspicious software detection

Smartphones are steadily gaining popularity, creating new application areas as their capabilities increase in terms of computational power, sensors and communication. Emerging new features of mobile devices give opportunity to new threats. Android is one of the newer operating systems targeting smartphones. While being based on a Linux kernel, Android has unique properties and specific limitations due to its mobile nature. This makes it harder to detect and react upon malware attacks if using conventional techniques. In this paper, we propose an Android Application Sandbox (AASandbox) which is able to perform both static and dynamic analysis on Android programs to automatically detect suspicious applications. Static analysis scans the software for malicious patterns without installing it. Dynamic analysis executes the application in a fully isolated environment, i.e. sandbox, which intervenes and logs low-level interactions with the system for further analysis. Both the sandbox and the detection algorithms can be deployed in the cloud, providing a fast and distributed detection of suspicious software in a mobile software store akin to Google's Android Market. Additionally, AASandbox might be used to improve the efficiency of classical anti-virus applications available for the Android operating system.

Collaborative intrusion detection framework : characteristics, adversarial opportunities and countermeasures

Complex Internet attacks may come from multiple sources, and target multiple networks and technologies. Nevertheless, Collaborative Intrusion Detection Systems (CIDS) emerges as a promising solution by using information from multiple sources to gain a better understanding of objective and impact of complex Internet attacks. CIDS also help to cope with classical problems of Intrusion Detection Systems (IDS) such as zero-day attacks, high false alarm rates and architectural challenges, e. g., centralized designs exposing the Single-Point-of-Failure. Improved complexity on the other hand gives raise to new exploitation opportunities for adversaries. The contribution of this paper is twofold. We first investigate related research on CIDS to identify the common building blocks and to understand vulnerabilities of the Collaborative Intrusion Detection Framework (CIDF). Second, we focus on the problem of anonymity preservation in a decentralized intrusion detection related message exchange scheme. We use techniques from design theory to provide multi-path peer-to-peer communication scheme where the adversary can not perform better than guessing randomly the originator of an alert message.

Framework for evaluating collaborative intrusion detection systems

Securing IT infrastructures of our modern lives is a challenging task because of their increasing complexity, scale and agile nature. Monolithic approaches such as using stand-alone firewalls and IDS devices for protecting the perimeter cannot cope with complex malwares and multistep attacks. Collaborative security emerges as a promising approach. But, research results in collaborative security are not mature, yet, and they require continuous evaluation and testing. In this work, we present CIDE, a Collaborative Intrusion Detection Extension for the network security simulation platform ( NeSSi 2 ). Built-in functionalities include dynamic group formation based on node preferences, group-internal communication, group management and an approach for handling the infection process for malware-based attacks. The CIDE simulation environment provides functionalities for easy implementation of collaborating nodes in large-scale setups. We evaluate the group communication mechanism on the one hand and provide a case study and evaluate our collaborative security evaluation platform in a signature exchange scenario on the other.

Detection of banana bunchy top virus in virus-infected plants using polymerase chain reaction

Polymerase chain reaction (PCR) was developed for the detection of Banana bunchy top virus (BBTV) at maximum after 210 min and at minimum after 90 min using Pc-1 and Pc-2, respectively. PCR detection of BBTV in crude sap indicated that the freezing of banana tissue in liquid nitrogen (LN2) before extraction was more effective than using sand as the extraction technique. BBTV was also detected using PCR assay in 69 healthy and diseased plants using Na-PO4 buffer containing 1 % SDS. PCR detection of BBTV in nucleic acid extracts using seven different extraction buffers to adapt the use of PCR in routine detection in the field was studied. Results proved that BBTV was detected with high sensitivity in nucleic acid extracts more than in infectious sap. The results also suggested the common aetiology for the BBTV by the PCR reactions of BBTV in nucleic acid extracts from Australia, Burundi, Egypt, France, Gabon, Philippines and Taiwan. Results also proved a positive relation between the Egyptian-BBTV isolate and abaca bunchy top isolate from the Philippines, but there no relation was found with the Cucumber mosaic cucumovirus (CMV) isolates from Egypt and Philippines and Banana bract mosaic virus (BBMV) were found.