@phdthesis{Amirkhanyan2019,
  author    = {Amirkhanyan, Aragats},
  title     = {Methods and frameworks for GeoSpatioTemporal data analytics},
  doi       = {10.25932/publishup-44168},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-441685},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xxiv, 133},
  year      = {2019},
  abstract  = {In the era of social networks, internet of things and location-based services, many online services produce a huge amount of data that have valuable objective information, such as geographic coordinates and date time. These characteristics (parameters) in the combination with a textual parameter bring the challenge for the discovery of geospatiotemporal knowledge. This challenge requires efficient methods for clustering and pattern mining in spatial, temporal and textual spaces. In this thesis, we address the challenge of providing methods and frameworks for geospatiotemporal data analytics. As an initial step, we address the challenges of geospatial data processing: data gathering, normalization, geolocation, and storage. That initial step is the basement to tackle the next challenge -- geospatial clustering challenge. The first step of this challenge is to design the method for online clustering of georeferenced data. This algorithm can be used as a server-side clustering algorithm for online maps that visualize massive georeferenced data. As the second step, we develop the extension of this method that considers, additionally, the temporal aspect of data. For that, we propose the density and intensity-based geospatiotemporal clustering algorithm with fixed distance and time radius. Each version of the clustering algorithm has its own use case that we show in the thesis. In the next chapter of the thesis, we look at the spatiotemporal analytics from the perspective of the sequential rule mining challenge. We design and implement the framework that transfers data into textual geospatiotemporal data - data that contain geographic coordinates, time and textual parameters. By this way, we address the challenge of applying pattern/rule mining algorithms in geospatiotemporal space. As the applicable use case study, we propose spatiotemporal crime analytics -- discovery spatiotemporal patterns of crimes in publicly available crime data. The second part of the thesis, we dedicate to the application part and use case studies. We design and implement the application that uses the proposed clustering algorithms to discover knowledge in data. Jointly with the application, we propose the use case studies for analysis of georeferenced data in terms of situational and public safety awareness.},
  language  = {en}
}
@phdthesis{Perlich2019,
  author    = {Perlich, Anja},
  title     = {Digital collaborative documentation in mental healthcare},
  doi       = {10.25932/publishup-44029},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-440292},
  school      = {Universit{\"a}t Potsdam},
  pages     = {x, 135},
  year      = {2019},
  abstract  = {With the growth of information technology, patient attitudes are shifting - away from passively receiving care towards actively taking responsibility for their well- being. Handling doctor-patient relationships collaboratively and providing patients access to their health information are crucial steps in empowering patients. In mental healthcare, the implicit consensus amongst practitioners has been that sharing medical records with patients may have an unpredictable, harmful impact on clinical practice. In order to involve patients more actively in mental healthcare processes, Tele-Board MED (TBM) allows for digital collaborative documentation in therapist-patient sessions. The TBM software system offers a whiteboard-inspired graphical user interface that allows therapist and patient to jointly take notes during the treatment session. Furthermore, it provides features to automatically reuse the digital treatment session notes for the creation of treatment session summaries and clinical case reports. This thesis presents the development of the TBM system and evaluates its effects on 1) the fulfillment of the therapist's duties of clinical case documentation, 2) patient engagement in care processes, and 3) the therapist-patient relationship. Following the design research methodology, TBM was developed and tested in multiple evaluation studies in the domains of cognitive behavioral psychotherapy and addiction care. The results show that therapists are likely to use TBM with patients if they have a technology-friendly attitude and when its use suits the treatment context. Support in carrying out documentation duties as well as fulfilling legal requirements contributes to therapist acceptance. Furthermore, therapists value TBM as a tool to provide a discussion framework and quick access to worksheets during treatment sessions. Therapists express skepticism, however, regarding technology use in patient sessions and towards complete record transparency in general. Patients expect TBM to improve the communication with their therapist and to offer a better recall of discussed topics when taking a copy of their notes home after the session. Patients are doubtful regarding a possible distraction of the therapist and usage in situations when relationship-building is crucial. When applied in a clinical environment, collaborative note-taking with TBM encourages patient engagement and a team feeling between therapist and patient. Furthermore, it increases the patient's acceptance of their diagnosis, which in turn is an important predictor for therapy success. In summary, TBM has a high potential to deliver more than documentation support and record transparency for patients, but also to contribute to a collaborative doctor-patient relationship. This thesis provides design implications for the development of digital collaborative documentation systems in (mental) healthcare as well as recommendations for a successful implementation in clinical practice.},
  language  = {en}
}
@phdthesis{Nikaj2019,
  author    = {Nikaj, Adriatik},
  title     = {Restful choreographies},
  doi       = {10.25932/publishup-43890},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-438903},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xix, 146},
  year      = {2019},
  abstract  = {Business process management has become a key instrument to organize work as many companies represent their operations in business process models. Recently, business process choreography diagrams have been introduced as part of the Business Process Model and Notation standard to represent interactions between business processes, run by different partners. When it comes to the interactions between services on the Web, Representational State Transfer (REST) is one of the primary architectural styles employed by web services today. Ideally, the RESTful interactions between participants should implement the interactions defined at the business choreography level. The problem, however, is the conceptual gap between the business process choreography diagrams and RESTful interactions. Choreography diagrams, on the one hand, are modeled from business domain experts with the purpose of capturing, communicating and, ideally, driving the business interactions. RESTful interactions, on the other hand, depend on RESTful interfaces that are designed by web engineers with the purpose of facilitating the interaction between participants on the internet. In most cases however, business domain experts are unaware of the technology behind web service interfaces and web engineers tend to overlook the overall business goals of web services. While there is considerable work on using process models during process implementation, there is little work on using choreography models to implement interactions between business processes. This thesis addresses this research gap by raising the following research question: How to close the conceptual gap between business process choreographies and RESTful interactions? This thesis offers several research contributions that jointly answer the research question. The main research contribution is the design of a language that captures RESTful interactions between participants---RESTful choreography modeling language. Formal completeness properties (with respect to REST) are introduced to validate its instances, called RESTful choreographies. A systematic semi-automatic method for deriving RESTful choreographies from business process choreographies is proposed. The method employs natural language processing techniques to translate business interactions into RESTful interactions. The effectiveness of the approach is shown by developing a prototypical tool that evaluates the derivation method over a large number of choreography models. In addition, the thesis proposes solutions towards implementing RESTful choreographies. In particular, two RESTful service specifications are introduced for aiding, respectively, the execution of choreographies' exclusive gateways and the guidance of RESTful interactions.},
  language  = {en}
}
@phdthesis{Krentz2019,
  author    = {Krentz, Konrad-Felix},
  title     = {A Denial-of-Sleep-Resilient Medium Access Control Layer for IEEE 802.15.4 Networks},
  doi       = {10.25932/publishup-43930},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-439301},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xiv, 187},
  year      = {2019},
  abstract  = {With the emergence of the Internet of things (IoT), plenty of battery-powered and energy-harvesting devices are being deployed to fulfill sensing and actuation tasks in a variety of application areas, such as smart homes, precision agriculture, smart cities, and industrial automation. In this context, a critical issue is that of denial-of-sleep attacks. Such attacks temporarily or permanently deprive battery-powered, energy-harvesting, or otherwise energy-constrained devices of entering energy-saving sleep modes, thereby draining their charge. At the very least, a successful denial-of-sleep attack causes a long outage of the victim device. Moreover, to put battery-powered devices back into operation, their batteries have to be replaced. This is tedious and may even be infeasible, e.g., if a battery-powered device is deployed at an inaccessible location. While the research community came up with numerous defenses against denial-of-sleep attacks, most present-day IoT protocols include no denial-of-sleep defenses at all, presumably due to a lack of awareness and unsolved integration problems. After all, despite there are many denial-of-sleep defenses, effective defenses against certain kinds of denial-of-sleep attacks are yet to be found. The overall contribution of this dissertation is to propose a denial-of-sleep-resilient medium access control (MAC) layer for IoT devices that communicate over IEEE 802.15.4 links. Internally, our MAC layer comprises two main components. The first main component is a denial-of-sleep-resilient protocol for establishing session keys among neighboring IEEE 802.15.4 nodes. The established session keys serve the dual purpose of implementing (i) basic wireless security and (ii) complementary denial-of-sleep defenses that belong to the second main component. The second main component is a denial-of-sleep-resilient MAC protocol. Notably, this MAC protocol not only incorporates novel denial-of-sleep defenses, but also state-of-the-art mechanisms for achieving low energy consumption, high throughput, and high delivery ratios. Altogether, our MAC layer resists, or at least greatly mitigates, all denial-of-sleep attacks against it we are aware of. Furthermore, our MAC layer is self-contained and thus can act as a drop-in replacement for IEEE 802.15.4-compliant MAC layers. In fact, we implemented our MAC layer in the Contiki-NG operating system, where it seamlessly integrates into an existing protocol stack.},
  language  = {en}
}
@book{BeckmannHildebrandJascheketal.2019,
  author    = {Beckmann, Tom and Hildebrand, Justus and Jaschek, Corinna and Krebs, Eva and L{\"o}ser, Alexander and Taeumel, Marcel and Pape, Tobias and Fister, Lasse and Hirschfeld, Robert},
  title     = {The font engineering platform},
  number    = {128},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-464-7},
  issn      = {1613-5652},
  doi       = {10.25932/publishup-42748},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-427487},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {viii, 115},
  year      = {2019},
  abstract  = {Creating fonts is a complex task that requires expert knowledge in a variety of domains. Often, this knowledge is not held by a single person, but spread across a number of domain experts. A central concept needed for designing fonts is the glyph, an elemental symbol representing a readable character. Required domains include designing glyph shapes, engineering rules to combine glyphs for complex scripts and checking legibility. This process is most often iterative and requires communication in all directions. This report outlines a platform that aims to enhance the means of communication, describes our prototyping process, discusses complex font rendering and editing in a live environment and an approach to generate code based on a user's live-edits.},
  language  = {en}
}
@phdthesis{Batoulis2019,
  author    = {Batoulis, Kimon},
  title     = {Sound integration of process and decision models},
  doi       = {10.25932/publishup-43738},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-437386},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xviii, 155},
  year      = {2019},
  abstract  = {Business process management is an established technique for business organizations to manage and support their processes. Those processes are typically represented by graphical models designed with modeling languages, such as the Business Process Model and Notation (BPMN). Since process models do not only serve the purpose of documentation but are also a basis for implementation and automation of the processes, they have to satisfy certain correctness requirements. In this regard, the notion of soundness of workflow nets was developed, that can be applied to BPMN process models in order to verify their correctness. Because the original soundness criteria are very restrictive regarding the behavior of the model, different variants of the soundness notion have been developed for situations in which certain violations are not even harmful. All of those notions do only consider the control-flow structure of a process model, however. This poses a problem, taking into account the fact that with the recent release and the ongoing development of the Decision Model and Notation (DMN) standard, an increasing number of process models are complemented by respective decision models. DMN is a dedicated modeling language for decision logic and separates the concerns of process and decision logic into two different models, process and decision models respectively. Hence, this thesis is concerned with the development of decisionaware soundness notions, i.e., notions of soundness that build upon the original soundness ideas for process models, but additionally take into account complementary decision models. Similar to the various notions of workflow net soundness, this thesis investigates different notions of decision soundness that can be applied depending on the desired degree of restrictiveness. Since decision tables are a standardized means of DMN to represent decision logic, this thesis also puts special focus on decision tables, discussing how they can be translated into an unambiguous format and how their possible output values can be efficiently determined. Moreover, a prototypical implementation is described that supports checking a basic version of decision soundness. The decision soundness notions were also empirically evaluated on models from participants of an online course on process and decision modeling as well as from a process management project of a large insurance company. The evaluation demonstrates that violations of decision soundness indeed occur and can be detected with our approach.},
  language  = {en}
}
@phdthesis{Krejca2019,
  author    = {Krejca, Martin Stefan},
  title     = {Theoretical analyses of univariate estimation-of-distribution algorithms},
  doi       = {10.25932/publishup-43487},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-434870},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xii, 243},
  year      = {2019},
  abstract  = {Optimization is a core part of technological advancement and is usually heavily aided by computers. However, since many optimization problems are hard, it is unrealistic to expect an optimal solution within reasonable time. Hence, heuristics are employed, that is, computer programs that try to produce solutions of high quality quickly. One special class are estimation-of-distribution algorithms (EDAs), which are characterized by maintaining a probabilistic model over the problem domain, which they evolve over time. In an iterative fashion, an EDA uses its model in order to generate a set of solutions, which it then uses to refine the model such that the probability of producing good solutions is increased. In this thesis, we theoretically analyze the class of univariate EDAs over the Boolean domain, that is, over the space of all length-n bit strings. In this setting, the probabilistic model of a univariate EDA consists of an n-dimensional probability vector where each component denotes the probability to sample a 1 for that position in order to generate a bit string. My contribution follows two main directions: first, we analyze general inherent properties of univariate EDAs. Second, we determine the expected run times of specific EDAs on benchmark functions from theory. In the first part, we characterize when EDAs are unbiased with respect to the problem encoding. We then consider a setting where all solutions look equally good to an EDA, and we show that the probabilistic model of an EDA quickly evolves into an incorrect model if it is always updated such that it does not change in expectation. In the second part, we first show that the algorithms cGA and MMAS-fp are able to efficiently optimize a noisy version of the classical benchmark function OneMax. We perturb the function by adding Gaussian noise with a variance of σ², and we prove that the algorithms are able to generate the true optimum in a time polynomial in σ² and the problem size n. For the MMAS-fp, we generalize this result to linear functions. Further, we prove a run time of Ω(n log(n)) for the algorithm UMDA on (unnoisy) OneMax. Last, we introduce a new algorithm that is able to optimize the benchmark functions OneMax and LeadingOnes both in O(n log(n)), which is a novelty for heuristics in the domain we consider.},
  language  = {en}
}
@phdthesis{Gross2019,
  author    = {Groß, Sascha},
  title     = {Detecting and mitigating information flow threats in Android OS},
  school      = {Universit{\"a}t Potsdam},
  pages     = {93},
  year      = {2019},
  language  = {en}
}
@phdthesis{Yang2019,
  author    = {Yang, Haojin},
  title     = {Deep representation learning for multimedia data analysis},
  school      = {Universit{\"a}t Potsdam},
  pages     = {278},
  year      = {2019},
  language  = {en}
}
@phdthesis{Gawron2019,
  author    = {Gawron, Marian},
  title     = {Towards automated advanced vulnerability analysis},
  doi       = {10.25932/publishup-42635},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-426352},
  school      = {Universit{\"a}t Potsdam},
  pages     = {149},
  year      = {2019},
  abstract  = {The identification of vulnerabilities in IT infrastructures is a crucial problem in enhancing the security, because many incidents resulted from already known vulnerabilities, which could have been resolved. Thus, the initial identification of vulnerabilities has to be used to directly resolve the related weaknesses and mitigate attack possibilities. The nature of vulnerability information requires a collection and normalization of the information prior to any utilization, because the information is widely distributed in different sources with their unique formats. Therefore, the comprehensive vulnerability model was defined and different sources have been integrated into one database. Furthermore, different analytic approaches have been designed and implemented into the HPI-VDB, which directly benefit from the comprehensive vulnerability model and especially from the logical preconditions and postconditions. Firstly, different approaches to detect vulnerabilities in both IT systems of average users and corporate networks of large companies are presented. Therefore, the approaches mainly focus on the identification of all installed applications, since it is a fundamental step in the detection. This detection is realized differently depending on the target use-case. Thus, the experience of the user, as well as the layout and possibilities of the target infrastructure are considered. Furthermore, a passive lightweight detection approach was invented that utilizes existing information on corporate networks to identify applications. In addition, two different approaches to represent the results using attack graphs are illustrated in the comparison between traditional attack graphs and a simplistic graph version, which was integrated into the database as well. The implementation of those use-cases for vulnerability information especially considers the usability. Beside the analytic approaches, the high data quality of the vulnerability information had to be achieved and guaranteed. The different problems of receiving incomplete or unreliable information for the vulnerabilities are addressed with different correction mechanisms. The corrections can be carried out with correlation or lookup mechanisms in reliable sources or identifier dictionaries. Furthermore, a machine learning based verification procedure was presented that allows an automatic derivation of important characteristics from the textual description of the vulnerabilities.},
  language  = {en}
}