Resolution strategies for serverless computing in information centric networking

Named Function Networking (NFN) offers to compute and deliver results of computations in the context of Information Centric Networking (ICN). While ICN offers data delivery without specifying the location where these data are stored, NFN offers the production of results without specifying where the actual computation is executed. In NFN, computation workflows are encoded in (ICN style) Interest Messages using the lambda calculus and based on these workflows, the network will distribute computations and find execution locations. Depending on the use case of the actual network, the decision where to execute a compuation can be different: A resolution strategy running on each node decides if a computation should be forwarded, split into subcomputations or executed locally. This work focuses on the design of resolution strategies for selected scenarios and the online derivation of "execution plans" based on network status and history. Starting with a simple resolution strategy suitable for data centers, we focus on improving load distribution within the data center or even between multiple data centers. We have designed resolution strategies that consider the size of input data and the load on nodes, leading to priced execution plans from which one can select the ones with the least costs. Moreover, we use these plans to create execution templates: Templates can be used to create a resolution strategy by simulating the execution using the planning system, tailored to the specific use case at hand. Finally we designed a resolution strategy for edge computing which is able to handle mobile scenarios typical for vehicular networking. This “mobile edge computing resolution strategy” handles the problem of frequent handovers to a sequence of road-side units without creating additional overhead for the non-mobile use case. All these resolution strategies were evaluated using a simulation system and were compared to the state of the art behavior of data center execution environments and/or cloud configurations. In the case of the vehicular networking strategy, we enhanced existing road-side units and implemented our NFN-based system and plan derivation such that we were able to run and validate our solution in real world tests for mobile edge computing

Touching Space: Distributed Ledger Technology for Tracking and Tracing Certificates

Components built into space vehicles and equipment (space products) must meet different regulatory requirements; in detail, each component must be certified and sustainably traceable at all times. Space engineers have expressed the need for an interoperable system to collect, manage and route certifications for components, parts and materials that go into space products. The lack of a unified approach in the European space industry is a challenge for companies involved in product development. This research proposes an open-source, secure, fast and distributed ledger technology (DLT) based solution that fits into any IT environment and is well adapted to the needs of manufacturing companies in the space sector. The results show that a blockchain-based solution based on 'Hyperledger Fabric' combined with the InterPlanetary File System is viable. The results can guide other researchers and practitioners to consider DLTs when changing their certification management paradigm with suppliers, customers and auditors

An Adaptable Approach for Successful SIEM Adoption in Companies

In corporations around the world, the topic of cybersecurity and information security is becoming increasingly important as the number of cyberattacks on themselves continues to grow. Nowadays, it is no longer just a matter of protecting against cyberattacks, but rather of detecting such attacks at an early stage and responding accordingly. There is currently no generic methodological approach for the implementation of Security Information and Event Management (SIEM) systems that takes academic aspects into account and can be applied independently of the product or developers of the systems. Applying Hevner's design science research approach, the goal of this paper is to develop a holistic procedure model for implementing respective SIEM systems in corporations. According to the study during the validation phase, the procedure model was verified to be applicable. As desire for future research, the procedure model should be applied in various implementation projects in different enterprises to analyze its applicability and completeness.Comment: Submitted to the AC2023 Conferenc

Prediction of overall survival for patients with metastatic castration-resistant prostate cancer : development of a prognostic model through a crowdsourced challenge with open clinical trial data

Background Improvements to prognostic models in metastatic castration-resistant prostate cancer have the potential to augment clinical trial design and guide treatment strategies. In partnership with Project Data Sphere, a not-for-profit initiative allowing data from cancer clinical trials to be shared broadly with researchers, we designed an open-data, crowdsourced, DREAM (Dialogue for Reverse Engineering Assessments and Methods) challenge to not only identify a better prognostic model for prediction of survival in patients with metastatic castration-resistant prostate cancer but also engage a community of international data scientists to study this disease. Methods Data from the comparator arms of four phase 3 clinical trials in first-line metastatic castration-resistant prostate cancer were obtained from Project Data Sphere, comprising 476 patients treated with docetaxel and prednisone from the ASCENT2 trial, 526 patients treated with docetaxel, prednisone, and placebo in the MAINSAIL trial, 598 patients treated with docetaxel, prednisone or prednisolone, and placebo in the VENICE trial, and 470 patients treated with docetaxel and placebo in the ENTHUSE 33 trial. Datasets consisting of more than 150 clinical variables were curated centrally, including demographics, laboratory values, medical history, lesion sites, and previous treatments. Data from ASCENT2, MAINSAIL, and VENICE were released publicly to be used as training data to predict the outcome of interest-namely, overall survival. Clinical data were also released for ENTHUSE 33, but data for outcome variables (overall survival and event status) were hidden from the challenge participants so that ENTHUSE 33 could be used for independent validation. Methods were evaluated using the integrated time-dependent area under the curve (iAUC). The reference model, based on eight clinical variables and a penalised Cox proportional-hazards model, was used to compare method performance. Further validation was done using data from a fifth trial-ENTHUSE M1-in which 266 patients with metastatic castration-resistant prostate cancer were treated with placebo alone. Findings 50 independent methods were developed to predict overall survival and were evaluated through the DREAM challenge. The top performer was based on an ensemble of penalised Cox regression models (ePCR), which uniquely identified predictive interaction effects with immune biomarkers and markers of hepatic and renal function. Overall, ePCR outperformed all other methods (iAUC 0.791; Bayes factor >5) and surpassed the reference model (iAUC 0.743; Bayes factor >20). Both the ePCR model and reference models stratified patients in the ENTHUSE 33 trial into high-risk and low-risk groups with significantly different overall survival (ePCR: hazard ratio 3.32, 95% CI 2.39-4.62, p Interpretation Novel prognostic factors were delineated, and the assessment of 50 methods developed by independent international teams establishes a benchmark for development of methods in the future. The results of this effort show that data-sharing, when combined with a crowdsourced challenge, is a robust and powerful framework to develop new prognostic models in advanced prostate cancer.Peer reviewe

A Serious Game for Simulating Cyberattacks to Teach Cybersecurity

With the rising number of cyberattacks, such as ransomware attacks and cyber espionage, educating non-cybersecurity professionals to recognize threats has become more important than ever before. However, traditional training methods, such as phishing awareness campaigns, training videos and assessments have proven to be less effective over time. Therefore, it is time to rethink the approach on how to train cyber awareness. In this paper we suggest an alternative approach -- a serious game -- to educate awareness for common cyberattacks. While many serious games for cybersecurity education exist, all follow a very similar approach: showing people the effects of a cyber attack on their own system or company network. For example, one of the main tasks in these games is to sort out phishing mails. We developed and evaluated a new type of cybersecurity game: an attack simulator, which shows the entire setting from a different perspective. Instead of sorting out phishing mails the players should write phishing mails to trick potential victims and use other forms of cyberattacks. Our game explains the intention of each attack and shows the consequences of a successful attack. This way, we hope, players will get a better understanding on how to detect cyberattacks.Comment: Master Thesis @ FHN

ICN Adaptation to LowPAN Networks (ICN LoWPAN)

In this document, a convergence layer for CCNx and NDN over IEEE 802.15.4 LoWPAN networks is defined. A new frame format is specified to adapt CCNx and NDN packets to the small MTU size of IEEE 802.15.4. For that, syntactic and semantic changes to the TLV-based header formats are described. To support compatibility with other LoWPAN technologies that may coexist on a wireless medium, the dispatching scheme provided by 6LoWPAN is extended to include new dispatch types for CCNx and NDN. Additionally, the link fragmentation component of the 6LoWPAN dispatching framework is applied to ICN chunks. In its second part, the document defines stateless and stateful compression schemes to improve efficiency on constrained links. Stateless compression reduces TLV expressions to static header fields for common use cases. Stateful compression schemes elide state local to the LoWPAN and replace names in data packets by short local identifiers

CCN Packet Adaptation to IEEE 802.15.4 Networks

Prevalent TLV-based CCN packet formats such as CCNx and NDN are designed to be generic and extensible. This leads to header verbosity which is not acceptable in constrained environments where small-sized MTU link-layers like IEEE 802.15.4 are deployed. This document presents an adaptation layer for IEEE 802.15.4 that reduces CCNx and NDN packet header sizes for an increased payload size. Further, a link fragmentation on this adaptation layer is described

Information-Centric Networking (ICN) Adaptation to Low-Power Wireless Personal Area Networks (LoWPANs)

This document defines a convergence layer for Content-Centric Networking (CCNx) and Named Data Networking (NDN) over IEEE 802.15.4 Low-Power Wireless Personal Area Networks (LoWPANs). A new frame format is specified to adapt CCNx and NDN packets to the small MTU size of IEEE 802.15.4. For that, syntactic and semantic changes to the TLV-based header formats are described. To support compatibility with other LoWPAN technologies that may coexist on a wireless medium, the dispatching scheme provided by IPv6 over LoWPAN (6LoWPAN) is extended to include new dispatch types for CCNx and NDN. Additionally, the fragmentation component of the 6LoWPAN dispatching framework is applied to Information-Centric Network (ICN) chunks. In its second part, the document defines stateless and stateful compression schemes to improve efficiency on constrained links. Stateless compression reduces TLV expressions to static header fields for common use cases. Stateful compression schemes elide states local to the LoWPAN and replace names in Data packets by short local identifiers. This document is a product of the IRTF Information-Centric Networking Research Group (ICNRG)

Femoral Shape and Size Variability from segmented CT datasets for patient-specific THA planning

Biomechanical functionality of artificial hips strongly correlates with quality of life of patients after total hip arthroplasty. As the numbers of total hip arthroplasty are growing due to increasing life expectancy, biomechanical research is of utmost importance to improve the implants used and the operative procedures applied. Multibody simulation is used to predict forces and moments inside the human body. Generic scaling is usually performed to adapt the human models used in multibody simulation to individual patients. However, since the shape and size of the bones can vary considerably, this type of scaling often is not sufficient. In this work various CT datasets were used to quantify differences of individual femoral shapes, especially with regard to important biomechanical hip parameters, such as the CCD angle or the femoral offset. Our results prove that multibody simulations should be modeled more patientspecific to be able to calculate articular forces and moments more precisely, and thus, to improve surgical planning