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Playing with Purpose shows how a facilitator, coach, manager, people developer or trainer can invent or reinvigorate an artificial learning experience and make it so much more than a game. The authors look at a range of dilemmas, challenges and problems faced by anyone wanting to run memorable training sessions, classes and project meetings and then demonstrate how to get powerful lessons from the simplest of household and office objects and situations. The exercises and ideas outlined provide a focused examination of a range of training aims and outcomes including leadership, teamwork, communications, equality and diversity, feedback and personal effectiveness; as well as general energisers, closers and problems to be solved. Steve Hutchinson and Helen Lawrence believe that seeing their sustainable, creative approach to experiential learning explicitly laid out, will give you the confidence to develop your own solutions. Contents: Preface: why read this book and how to use it; Part I The Concept of Experiential Learning: Optimizing artificial experiential learning. Part II The Skills of Facilitation: Extracting the lesson: how to review, capture and amplify the learning. Part III The Developer's Toolbox - Specific Issues and Tactics; Helping teams work; Facilitating leadership development; Building personal effectiveness; Dealing with change; Producing creative and critical thinkers; Understanding organizational quality; Getting people talking: building productive relationships; Exploring diversity issues; Final thoughts and last words; Bibliography. After completing his PhD in Behavioural Ecology and working in academia, Dr Steve Hutchinson led development programmes at the Universities of York and Leeds. He now owns and runs his own development consultancy and has designed and led acclaimed courses and events for a huge range of organisations and institutions, both in the UK and abroad. A highly skilled facilitator and trainer, he is both a Vitae GRADschool national course director and a programme director for the Leadership Foundation for Higher Education. He is a qualified trainer, coach and practitioner of Neuro-Linguistic Programming. He writes articles and chapters on a range of topics from creativity to leadership and motivation. Playing With Purpose is his second book. Dr Helen Lawrence completed a PhD in Sociolinguistic Variation and worked in the academic sector for a number of years, publishing, teaching and lecturing. Discovering a passion for helping people realize their potential she moved into the field of training and development. For five years she worked at the University of York, taking a lead role in developing and delivering training programmes for staff and students. In 2008 she set up her own training and development business, and works with individuals, teams and institutions in the research, educational and not-for-profit sectors. Helen is also a local and national Vitae GRADschool tutor; an accredited Myers Briggs Type Indicator practitioner; and a trained Coactive Coach.

Cyberattacks endanger physical, economic, social, and political security. There have been extensive efforts in government, academia, and industry to anticipate, forecast, and mitigate such cyberattacks. A common approach is time-series forecasting of cyberattacks based on data from network telescopes, honeypots, and automated intrusion detection/prevention systems. This research has uncovered key insights such as systematicity in cyberattacks. Here, we propose an alternate perspective of this problem by performing forecasting of attacks that are “analyst-detected” and “-verified” occurrences of malware. We call these instances of malware cyber event data. Specifically, our dataset was analyst-detected incidents from a large operational Computer Security Service Provider (CSSP) for the US Department of Defense, which rarely relies only on automated systems. Our data set consists of weekly counts of cyber events over approximately 7 years. This curated dataset has characteristics that distinguish it from most datasets used in prior research on cyberattacks. Since all cyber events were validated by analysts, our dataset is unlikely to have false positives which are often endemic in other sources of data. Further, the higher-quality data could be used for a number of important tasks for CSSPs such as resource allocation, estimation of security resources, and the development of effective risk-management strategies. To quantify bursts, we used a Markov model of state transitions. For forecasting, we used a Bayesian State Space Model and found that events one week ahead could be predicted with reasonable accuracy, with the exception of bursts. Our findings of systematicity in analyst-detected cyberattacks are consistent with previous work using cyberattack data from other sources. The advanced information provided by a forecast may help with threat awareness by providing a probable value and range for future cyber events one week ahead, similar to a weather forecast. Other potential applications for cyber event forecasting include proactive allocation of resources and capabilities for cyber defense (e.g., analyst staffing and sensor configuration) in CSSPs. Enhanced threat awareness may improve cybersecurity by helping to optimize human and technical capabilities for cyber defense.

Little is known of the ability of baldcypress ( Taxodium distichum (L.) L.C. Rich.) in a suppressed sub-canopy position to respond to increases in light. We measured 3 years of diameter growth response of long-suppressed baldcypress saplings to canopy gap creation in a hydrologically altered, water tupelo-dominated backswamp of the lower Roanoke River floodplain in eastern North Carolina. Baldcypress saplings responded strongly to gap creation. Saplings showed a significant positive growth trend, with mean basal area growth in gaps expanding from 2.5 cm 2 in year one, 4 times that of control saplings, to 8.5 cm 2 in year three, 20 times that of control saplings. Within canopy gaps, a positive trend between growth and initial sapling diameter was evident, while such a trend among controls was non-existent. Mortality was similar between gap and control saplings after 1 year, but by year three gap sapling mortality had declined to 2 %, while control mortality increased to 16 %. It is clear that long-suppressed baldcypress, sometimes at the brink of death, are able to respond vigorously to an increase in light from canopy gaps with decreased mortality and increased growth. This has important implications for wetlands requiring restoration or baldcypress management within the framework of two-age or uneven-aged silvicultural systems.

Postfire succesion of the temporary herbaceous and suffrutescent cover was studied after chaparral fires in San Diego County, California, USA. Four categories of species make up the temporary cover. (1) @'Generalized herbaceous perennials@' are present before and after fire. Populations of these herbs are sparse under the shrub canopy. They resprout after fire from bulbs or other underground parts and postfire populations are sparse. (2) @'Generalized annuals@' are present in openings before fire but produce their peak population size in the first few years after fire. (3) Specialized @'fire-annuals@' are more or less restricted to the 1st postfire yr. (4) Specialized @'fire-perennials@' (subshrubs) are uncommon before fire, establish from seed in the 1st postfire yr and reach maximum cover in the 3rd and 4th yr. Community-level changes in cover and diversity are interpreted in light of differences in population dynamics of the four groups. Specis richness was highest in the 1st yr after fire because this was the only time all four groups were present together. Throughout succession herbaceous species richness was positively related to herb cover, negatively related to elevation and unrelated to slope aspect. The number of annual species fluctuated greatly through succession at all sites, but the number of herbaceous perennials did not. Herb cover fluctuated markedly from year to year and was positively related to amount of annual precipitation and negatively related to subshrub or @'fire-perennial@' cover. Artificial seeding with annual rye grass Lolium multiflorum had not apparent effect on total herb cover since sites with poor Lolium establishment had as high or higher herb cover as sites with high Lolium establishment. Lolium success was at the expense of the native cover and this negative effect was greatest on the @'fire annuals.@'

Traditional signature-based alerting methods for intrusion detection systems are inefficient on high-traffic networks because every packet is assessed. The left-sided session approach [LSS(r)] approach developed herein rivals the alerting performance of signature-based alerting methods, with significantly fewer packets analyzed. We explored the maximum number of packets that could be filtered out of sessions for signature-based packet processing, while retaining the relatively same number of alerts generated using a traditional signature-based method. Four treatments with different numbers of sequential packets analyzed were compared to a baseline condition. The dependent measure was the percentage of the total alerts generated in each of the four treatments, compared to the baseline condition. Five Snort® rules from a community ruleset were selected and applied to an open-source data set from a computer network defense exercise held at West Point CDX in 2009. A post-test only, non-crossover, within-subjects, experimental design was conducted. The baseline condition processed 1,642,008 packets, resulting in 1,795 alerts fired in the baseline condition. For each of the 4 treatment conditions, the total number of alerts were generated. Using only the first 10 packets of a session for processing, ~99% of the total alerts were fired comparatively. Implications for this work and future research are discussed herein.

The emergence of the term \"post-truth\" demands a re-evaluation of security solutions and their underlying assumptions. The assumption of trusting security information and event data is an area that requires examination due to the potential problem of missing actual events. A proposed framework of placing security data in the environment where the data was first created allows for detection of the events within the network's operational profile, and this allows for detection of perturbations to the data alert and the corresponding environmental variables. These findings can be used to more accurately determine both the location and the nature of the perturbation, thereby countering data fidelity of security data.

In this paper, we present an algorithm for extracting packet and session features Indicative of suspicious activities on the network. We describe a new network traffic collection algorithm, the Left-sided Session (LSS), and show that with most network security analysis methods, relevant evidence Is concentrated within the first few packets of a session. Our LSS Is a collection and representation hybrid, with content Intermediate between packet-level capture, as In a PCAP file, and flow-level capture (flow-file) which only summarizes a flow. We compare the performance and Information content of PCAP, flow-file, and LSS file representations, using a small variety of signature-based detection rules and show that In our sample study, 99% of Indicator Information content Is retained while preserving only the first 10 packets of each session.