Combinatorial design of key distribution mechanisms for wireless sensor networks

Key distribution is one of the most challenging security issues in wireless sensor networks where sensor nodes are randomly scattered over a hostile territory. In such a sensor deployment scenario, there will be no prior knowledge of post deployment configuration. For security solutions requiring pairwise keys, it is impossible to decide how to distribute key pairs to sensor nodes before the deployment. Existing approaches to this problem are to assign more than one key, namely a key-chain, to each node. Key-chains are randomly drawn from a key-pool. Either two neighboring nodes have a key in common in their key-chains, or there is a path, called key-path, among these two nodes where each pair of neighboring nodes on this path has a key in common. Problem in such a solution is to decide on the key-chain size and key-pool size so that every pair of nodes can establish a session key directly or through a path with high probability. The size of the key-path is the key factor for the efficiency of the design. This paper presents novel, deterministic and hybrid approaches based on Combinatorial Design for key distribution. In particular, several block design techniques are considered for generating the key-chains and the key-pools.

Diagenesis in interplanetary dust - chondritic porous aggregate w7029-star-a

In previous Analytical Electron Microscope studies of extraterrestrial Chondritic Porous Aggregate (CPA) W7029* A, we have reported on the presence of layer silicates(Rietmeijer and Mackinnon, 1984a; Mackinnon and Rietmeijer, 1983) and metal oxides (Rietmeijer and Mackinnon, 1984a; Mackinnon and Rietmeijer, 1984). We present here a continuation ofthis detailed mineralogical study and propose a scenario which may account for the variety and types of phases observed in this CPA. At least 50% ofCPA W7029*A is carbonaceous material, primarily poorly graphitised carbon (POC) with morphologies similar to POC in acid residues of carbonaceous chondrites (Smith and Busek, 1981; Lumpkin, 1983). The basal spacing of graphite in CPA W7029*A ranges from 3.47-3.52 A and compares with doo, of graphite in the Allende residues (Smith and Buseck, 1981; Lumpkin, 1983). Low-temperature phases comprise - 20% of CPA W7029*A and include layer silicates, Bi,O" a-FeOOH(Rietmeijer and Mackinnon, 1984a; Mackinnon and Rietmeijer, 1983), BaSO.,.Ti.O, plates, pentlandite-violarite and bornite. Clusters of Mg-rich olivine and pyroxene make up - 12% of the aggregate...

Robots move : bootstrapping the development of object representations using sensorimotor coordination

This paper is concerned with the unsupervised learning of object representations by fusing visual and motor information. The problem is posed for a mobile robot that develops its representations as it incrementally gathers data. The scenario is problematic as the robot only has limited information at each time step with which it must generate and update its representations. Object representations are refined as multiple instances of sensory data are presented; however, it is uncertain whether two data instances are synonymous with the same object. This process can easily diverge from stability. The premise of the presented work is that a robot's motor information instigates successful generation of visual representations. An understanding of self-motion enables a prediction to be made before performing an action, resulting in a stronger belief of data association. The system is implemented as a data-driven partially observable semi-Markov decision process. Object representations are formed as the process's hidden states and are coordinated with motor commands through state transitions. Experiments show the prediction process is essential in enabling the unsupervised learning method to converge to a solution - improving precision and recall over using sensory data alone.

Data transformations in custom digital workflows : property graphs as a data model for user-defined mappings

This paper describes the use of property graphs for mapping data between AEC software tools, which are not linked by common data formats and/or other interoperability measures. The intention of introducing this in practice, education and research is to facilitate the use of diverse, non-integrated design and analysis applications by a variety of users who need to create customised digital workflows, including those who are not expert programmers. Data model types are examined by way of supporting the choice of directed, attributed, multi-relational graphs for such data transformation tasks. A brief exemplar design scenario is also presented to illustrate the concepts and methods proposed, and conclusions are drawn regarding the feasibility of this approach and directions for further research.

Glider path-planning for optimal sampling of mesocale eddies

Ocean gliders constitute an important advance in the highly demanding ocean monitoring scenario. Their effciency, endurance and increasing robustness make these vehicles an ideal observing platform for many long term oceanographic applications. However, they have proved to be also useful in the opportunis-tic short term characterization of dynamic structures. Among these, mesoscale eddies are of particular interest due to the relevance they have in many oceano-graphic processes.

Privacy-aware workflow management

Information security policies play an important role in achieving information security. Confidentiality, Integrity, and Availability are classic information security goals attained by enforcing appropriate security policies. Workflow Management Systems (WfMSs) also benefit from inclusion of these policies to maintain the security of business-critical data. However, in typical WfMSs these policies are designed to enforce the organisation’s security requirements but do not consider those of other stakeholders. Privacy is an important security requirement that concerns the subject of data held by an organisation. WfMSs often process sensitive data about individuals and institutions who demand that their data is properly protected, but WfMSs fail to recognise and enforce privacy policies. In this paper, we illustrate existing WfMS privacy weaknesses and introduce WfMS extensions required to enforce data privacy. We have implemented these extensions in the YAWL system and present a case scenario to demonstrate how it can enforce a subject’s privacy policy.

Genetic association of the KLK4 locus with risk of prostate cancer

The Kallikrein-related peptidase, KLK4, has been shown to be significantly overexpressed in prostate tumours in numerous studies and is suggested to be a potential biomarker for prostate cancer. KLK4 may also play a role in prostate cancer progression through its involvement in epithelial-mesenchymal transition, a more aggressive phenotype, and metastases to bone. It is well known that genetic variation has the potential to affect gene expression and/or various protein characteristics and hence we sought to investigate the possible role of single nucleotide polymorphisms (SNPs) in the KLK4 gene in prostate cancer. Assessment of 61 SNPs in the KLK4 locus (±10 kb) in approximately 1300 prostate cancer cases and 1300 male controls for associations with prostate cancer risk and/or prostate tumour aggressiveness (Gleason score <7 versus ≥7) revealed 7 SNPs to be associated with a decreased risk of prostate cancer at the Ptrend<0.05 significance level. Three of these SNPs, rs268923, rs56112930 and the HapMap tagSNP rs7248321, are located several kb upstream of KLK4; rs1654551 encodes a non-synonymous serine to alanine substitution at position 22 of the long isoform of the KLK4 protein, and the remaining 3 risk-associated SNPs, rs1701927, rs1090649 and rs806019, are located downstream of KLK4 and are in high linkage disequilibrium with each other (r2≥0.98). Our findings provide suggestive evidence of a role for genetic variation in the KLK4 locus in prostate cancer predisposition.

On robust face recognition via sparse encoding : the good, the bad, and the ugly

In the field of face recognition, Sparse Representation (SR) has received considerable attention during the past few years. Most of the relevant literature focuses on holistic descriptors in closed-set identification applications. The underlying assumption in SR-based methods is that each class in the gallery has sufficient samples and the query lies on the subspace spanned by the gallery of the same class. Unfortunately, such assumption is easily violated in the more challenging face verification scenario, where an algorithm is required to determine if two faces (where one or both have not been seen before) belong to the same person. In this paper, we first discuss why previous attempts with SR might not be applicable to verification problems. We then propose an alternative approach to face verification via SR. Specifically, we propose to use explicit SR encoding on local image patches rather than the entire face. The obtained sparse signals are pooled via averaging to form multiple region descriptors, which are then concatenated to form an overall face descriptor. Due to the deliberate loss spatial relations within each region (caused by averaging), the resulting descriptor is robust to misalignment & various image deformations. Within the proposed framework, we evaluate several SR encoding techniques: l1-minimisation, Sparse Autoencoder Neural Network (SANN), and an implicit probabilistic technique based on Gaussian Mixture Models. Thorough experiments on AR, FERET, exYaleB, BANCA and ChokePoint datasets show that the proposed local SR approach obtains considerably better and more robust performance than several previous state-of-the-art holistic SR methods, in both verification and closed-set identification problems. The experiments also show that l1-minimisation based encoding has a considerably higher computational than the other techniques, but leads to higher recognition rates.

Examination of distracted driving and yellow light running : analysis of simulator data

Driving on an approach to a signalized intersection while distracted is particularly dangerous, as potential vehicular conflicts and resulting angle collisions tend to be severe. Given the prevalence and importance of this particular scenario, the decisions and actions of distracted drivers during the onset of yellow lights are the focus of this study. Driving simulator data were obtained from a sample of 58 drivers under baseline and handheld mobile phone conditions at the University of Iowa - National Advanced Driving Simulator. Explanatory variables included age, gender, cell phone use, distance to stop-line, and speed. Although there is extensive research on drivers’ responses to yellow traffic signals, the examination has been conducted from a traditional regression-based approach, which does not necessary provide the underlying relations and patterns among the sampled data. In this paper, we exploit the benefits of both classical statistical inference and data mining techniques to identify the a priori relationships among main effects, non-linearities, and interaction effects. Results suggest that novice (16-17 years) and young drivers’ (18-25 years) have heightened yellow light running risk while distracted by a cell phone conversation. Driver experience captured by age has a multiplicative effect with distraction, making the combined effect of being inexperienced and distracted particularly risky. Overall, distracted drivers across most tested groups tend to reduce the propensity of yellow light running as the distance to stop line increases, exhibiting risk compensation on a critical driving situation.

Effect of carbohydrate ingestion and ambient temperature on muscle fatigue development in endurance-trained male cyclists

The aim of the present study was to determine the effect of carbohydrate (CHO; sucrose) ingestion and environmental heat on the development of fatigue and the distribution of power output during a 16.1-km cycling time trial. Ten male cyclists (Vo(2max) = 61.7 +/- 5.0 ml.kg(-1).min(-1), mean +/- SD) performed four 90-min constant-pace cycling trials at 80% of second ventilatory threshold (220 +/- 12 W). Trials were conducted in temperate (18.1 +/- 0.4 degrees C) or hot (32.2 +/- 0.7 degrees C) conditions during which subjects ingested either CHO (0.96 g.kg(-1).h(-1)) or placebo (PLA) gels. All trials were followed by a 16.1-km time trial. Before and immediately after exercise, percent muscle activation was determined using superimposed electrical stimulation. Power output, integrated electromyography (iEMG) of vastus lateralis, rectal temperature, and skin temperature were recorded throughout the trial. Percent muscle activation significantly declined during the CHO and PLA trials in hot (6.0 and 6.9%, respectively) but not temperate conditions (1.9 and 2.2%, respectively). The decline in power output during the first 6 km was significantly greater during exercise in the heat. iEMG correlated significantly with power output during the CHO trials in hot and temperate conditions (r = 0.93 and 0.73; P < 0.05) but not during either PLA trial. In conclusion, cyclists tended to self-select an aggressive pacing strategy (initial high intensity) in the heat.

Games for change and transformative learning : an ethnographic case study

This thesis aims to contribute to a better understanding of how serious games/games for change function as learning frameworks for transformative learning in an educational setting. This study illustrates how the meaning-making processes and learning with and through computer gameplay are highly contingent, and are significantly influenced by the uncertainties of the situational context. The study focuses on SCAPE, a simulation game that addresses urban planning and sustainability. SCAPE is based on the real-world scenario of Kelvin Grove Urban Village, an inner city redevelopment area in Brisbane, Queensland, Australia. The game is embedded within an educational program, and I thus account for the various gameplay experiences of different school classes participating in this program. The networks emerging from the interactions between students/players, educators, facilitators, the technology, the researcher, as well as the setting, result in unanticipated, controversial, and sometimes unintended gameplay experiences and outcomes. To unpack play, transformative learning and games, this study adopts an ecological approach that considers the magic circle of gameplay in its wider context. Using Actor-Network Theory as the ontological lens for inquiry, the methods for investigation include an extensive literature review, ethnographic participant observation of SCAPE, as well as student and teacher questionnaires, finishing with interviews with the designers and facilitators of SCAPE. Altogether, these methods address my research aim to better understand how the heterogeneous actors engage in the relationships in and around gameplay, and illustrate how their conflicting understandings enable, shape or constrain the (transformative) learning experience. To disentangle these complexities, my focus continuously shifts between the following modes of inquiry into the aims „h To describe and analyse the game as a designed artefact. „h To examine the gameplay experiences of players/students and account for how these experiences are constituted in the relationships of the network. „h To trace the meaning-making processes emerging from the various relations of players/students, facilitators, teachers, designers, technology, researcher, and setting, and consider how the boundaries of the respective ecology are configured and negotiated. „h To draw out the implications for the wider research area of game-based learning by using the simulation game SCAPE as an example for introducing gameplay to educational settings. Accounting in detail for five school classes, these accounts represent, each in its own right, distinct and sometimes controversial forms of engagement in gameplay. The practices and negotiations of all the assembled human and non-human actors highlight the contingent nature of gameplay and learning. In their sum, they offer distinct but by no means exhaustive examples of the various relationships that emerge from the different assemblages of human and non-human actors. This thesis, hence, illustrates that game-based learning in an educational setting is accompanied by considerable unpredictability and uncertainty. As ordinary life spills and leaks into gameplay experiences, group dynamics and the negotiations of technology, I argue that overly deterministic assertions of the game¡¦s intention, as well as a too narrowly defined understanding of the transformative learning outcome, can constrain our inquiries and hinder efforts to further elucidate and understand the evolving uncertainties around game-based learning. Instead, this thesis posits that playing and transformative learning are relational effects of the respective ecology, where all actors are networked in their (partial) enrolment in the process of translation. This study thus attempts to foreground the rich opportunities for exploring how game-based learning is assembled as a network of practices.

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.

Scheduling decisions and their dynamic consequences on construction performance

Construction practitioners often experience unexpected results of their scheduling-related decisions. This is mainly due to lack of understanding of the dynamic nature of construction system. However, very little attention has been given to its significant importance and few empirical studies have been undertaken on this issue. This paper, therefore, analyzes the effect of aggressive scheduling, overtime, resource adding, and schedule slippage on construction performance, focusing on workers’ reactions to those scheduling decisions. Survey data from 102 construction practitioners in 38 construction sites are used for the analysis. The results indicate that efforts to increase work rate by working overtime, resource adding, and aggressive scheduling can be offset due to losses in productivity and quality. Based on the research findings, practical guidelines are then discussed to help site managers to effectively deal with the dynamics of scheduling and improve construction performance.

Combinatorial design of key distribution mechanisms for wireless sensor networks

Key distribution is one of the most challenging security issues in wireless sensor networks where sensor nodes are randomly scattered over a hostile territory. In such a sensor deployment scenario, there will be no prior knowledge of post deployment configuration. For security solutions requiring pair wise keys, it is impossible to decide how to distribute key pairs to sensor nodes before the deployment. Existing approaches to this problem are to assign more than one key, namely a key-chain, to each node. Key-chains are randomly drawn from a key-pool. Either two neighbouring nodes have a key in common in their key-chains, or there is a path, called key-path, among these two nodes where each pair of neighbouring nodes on this path has a key in common. Problem in such a solution is to decide on the key-chain size and key-pool size so that every pair of nodes can establish a session key directly or through a path with high probability. The size of the key-path is the key factor for the efficiency of the design. This paper presents novel, deterministic and hybrid approaches based on Combinatorial Design for key distribution. In particular, several block design techniques are considered for generating the key-chains and the key-pools. Comparison to probabilistic schemes shows that our combinatorial approach produces better connectivity with smaller key-chain sizes.

Monitoring android for collaborative anomaly detection : a first architectural draft

Our daily lives become more and more dependent upon smartphones due to their increased capabilities. Smartphones are used in various ways, e.g. for payment systems or assisting the lives of elderly or disabled people. Security threats for these devices become more and more dangerous since there is still a lack of proper security tools for protection. Android emerges as an open smartphone platform which allows modification even on operating system level and where third-party developers first time have the opportunity to develop kernel-based low-level security tools. Android quickly gained its popularity among smartphone developers and even beyond since it bases on Java on top of "open" Linux in comparison to former proprietary platforms which have very restrictive SDKs and corresponding APIs. Symbian OS, holding the greatest market share among all smartphone OSs, was even closing critical APIs to common developers and introduced application certification. This was done since this OS was the main target for smartphone malwares in the past. In fact, more than 290 malwares designed for Symbian OS appeared from July 2004 to July 2008. Android, in turn, promises to be completely open source. Together with the Linux-based smartphone OS OpenMoko, open smartphone platforms may attract malware writers for creating malicious applications endangering the critical smartphone applications and owners privacy. Since signature-based approaches mainly detect known malwares, anomaly-based approaches can be a valuable addition to these systems. They base on mathematical algorithms processing data that describe the state of a certain device. For gaining this data, a monitoring client is needed that has to extract usable information (features) from the monitored system. Our approach follows a dual system for analyzing these features. On the one hand, functionality for on-device light-weight detection is provided. But since most algorithms are resource exhaustive, remote feature analysis is provided on the other hand. Having this dual system enables event-based detection that can react to the current detection need. In our ongoing research we aim to investigates the feasibility of light-weight on-device detection for certain occasions. On other occasions, whenever significant changes are detected on the device, the system can trigger remote detection with heavy-weight algorithms for better detection results. In the absence of the server respectively as a supplementary approach, we also consider a collaborative scenario. Here, mobile devices sharing a common objective are enabled by a collaboration module to share information, such as intrusion detection data and results. This is based on an ad-hoc network mode that can be provided by a WiFi or Bluetooth adapter nearly every smartphone possesses.