@article{KayemMeinelWolthusen2018, author = {Kayem, Anne Voluntas dei Massah and Meinel, Christoph and Wolthusen, Stephen D.}, title = {A resilient smart micro-grid architecture for resource constrained environments}, series = {Smart Micro-Grid Systems Security and Privacy}, volume = {71}, journal = {Smart Micro-Grid Systems Security and Privacy}, publisher = {Springer}, address = {Dordrecht}, isbn = {978-3-319-91427-5}, doi = {10.1007/978-3-319-91427-5_5}, pages = {71 -- 101}, year = {2018}, abstract = {Resource constrained smart micro-grid architectures describe a class of smart micro-grid architectures that handle communications operations over a lossy network and depend on a distributed collection of power generation and storage units. Disadvantaged communities with no or intermittent access to national power networks can benefit from such a micro-grid model by using low cost communication devices to coordinate the power generation, consumption, and storage. Furthermore, this solution is both cost-effective and environmentally-friendly. One model for such micro-grids, is for users to agree to coordinate a power sharing scheme in which individual generator owners sell excess unused power to users wanting access to power. Since the micro-grid relies on distributed renewable energy generation sources which are variable and only partly predictable, coordinating micro-grid operations with distributed algorithms is necessity for grid stability. Grid stability is crucial in retaining user trust in the dependability of the micro-grid, and user participation in the power sharing scheme, because user withdrawals can cause the grid to breakdown which is undesirable. In this chapter, we present a distributed architecture for fair power distribution and billing on microgrids. The architecture is designed to operate efficiently over a lossy communication network, which is an advantage for disadvantaged communities. We build on the architecture to discuss grid coordination notably how tasks such as metering, power resource allocation, forecasting, and scheduling can be handled. All four tasks are managed by a feedback control loop that monitors the performance and behaviour of the micro-grid, and based on historical data makes decisions to ensure the smooth operation of the grid. Finally, since lossy networks are undependable, differentiating system failures from adversarial manipulations is an important consideration for grid stability. We therefore provide a characterisation of potential adversarial models and discuss possible mitigation measures.}, language = {en} } @misc{ShaabaniMeinel2018, author = {Shaabani, Nuhad and Meinel, Christoph}, title = {Improving the efficiency of inclusion dependency detection}, series = {Proceedings of the 27th ACM International Conference on Information and Knowledge Management}, journal = {Proceedings of the 27th ACM International Conference on Information and Knowledge Management}, publisher = {Association for Computing Machinery}, address = {New York}, isbn = {978-1-4503-6014-2}, doi = {10.1145/3269206.3271724}, pages = {207 -- 216}, year = {2018}, abstract = {The detection of all inclusion dependencies (INDs) in an unknown dataset is at the core of any data profiling effort. Apart from the discovery of foreign key relationships, INDs can help perform data integration, integrity checking, schema (re-)design, and query optimization. With the advent of Big Data, the demand increases for efficient INDs discovery algorithms that can scale with the input data size. To this end, we propose S-INDD++ as a scalable system for detecting unary INDs in large datasets. S-INDD++ applies a new stepwise partitioning technique that helps discard a large number of attributes in early phases of the detection by processing the first partitions of smaller sizes. S-INDD++ also extends the concept of the attribute clustering to decide which attributes to be discarded based on the clustering result of each partition. Moreover, in contrast to the state-of-the-art, S-INDD++ does not require the partition to fit into the main memory-which is a highly appreciable property in the face of the ever growing datasets. We conducted an exhaustive evaluation of S-INDD++ by applying it to large datasets with thousands attributes and more than 266 million tuples. The results show the high superiority of S-INDD++ over the state-of-the-art. S-INDD++ reduced up to 50 \% of the runtime in comparison with BINDER, and up to 98 \% in comparison with S-INDD.}, language = {en} } @misc{SianiparSukmanaMeinel2019, author = {Sianipar, Johannes Harungguan and Sukmana, Muhammad Ihsan Haikal and Meinel, Christoph}, title = {Moving sensitive data against live memory dumping, spectre and meltdown attacks}, series = {26th International Conference on Systems Engineering (ICSEng)}, journal = {26th International Conference on Systems Engineering (ICSEng)}, publisher = {IEEE}, address = {New York}, isbn = {978-1-5386-7834-3}, pages = {8}, year = {2019}, abstract = {The emergence of cloud computing allows users to easily host their Virtual Machines with no up-front investment and the guarantee of always available anytime anywhere. But with the Virtual Machine (VM) is hosted outside of user's premise, the user loses the physical control of the VM as it could be running on untrusted host machines in the cloud. Malicious host administrator could launch live memory dumping, Spectre, or Meltdown attacks in order to extract sensitive information from the VM's memory, e.g. passwords or cryptographic keys of applications running in the VM. In this paper, inspired by the moving target defense (MTD) scheme, we propose a novel approach to increase the security of application's sensitive data in the VM by continuously moving the sensitive data among several memory allocations (blocks) in Random Access Memory (RAM). A movement function is added into the application source code in order for the function to be running concurrently with the application's main function. Our approach could reduce the possibility of VM's sensitive data in the memory to be leaked into memory dump file by 2 5\% and secure the sensitive data from Spectre and Meltdown attacks. Our approach's overhead depends on the number and the size of the sensitive data.}, language = {en} } @article{KayemWolthusenMeinel2018, author = {Kayem, Anne Voluntas dei Massah and Wolthusen, Stephen D. and Meinel, Christoph}, title = {Power Systems}, series = {Smart Micro-Grid Systems Security and Privacy}, volume = {71}, journal = {Smart Micro-Grid Systems Security and Privacy}, publisher = {Springer}, address = {Dordrecht}, isbn = {978-3-319-91427-5}, doi = {10.1007/978-3-319-91427-5_1}, pages = {1 -- 8}, year = {2018}, abstract = {Studies indicate that reliable access to power is an important enabler for economic growth. To this end, modern energy management systems have seen a shift from reliance on time-consuming manual procedures, to highly automated management, with current energy provisioning systems being run as cyber-physical systems. Operating energy grids as a cyber-physical system offers the advantage of increased reliability and dependability, but also raises issues of security and privacy. In this chapter, we provide an overview of the contents of this book showing the interrelation between the topics of the chapters in terms of smart energy provisioning. We begin by discussing the concept of smart-grids in general, proceeding to narrow our focus to smart micro-grids in particular. Lossy networks also provide an interesting framework for enabling the implementation of smart micro-grids in remote/rural areas, where deploying standard smart grids is economically and structurally infeasible. To this end, we consider an architectural design for a smart micro-grid suited to low-processing capable devices. We model malicious behaviour, and propose mitigation measures based properties to distinguish normal from malicious behaviour.}, language = {en} } @misc{StaubitzMeinel2018, author = {Staubitz, Thomas and Meinel, Christoph}, title = {Collaborative Learning in MOOCs - Approaches and Experiments}, series = {2018 IEEE Frontiers in Education (FIE) Conference}, journal = {2018 IEEE Frontiers in Education (FIE) Conference}, publisher = {IEEE}, address = {New York}, isbn = {978-1-5386-1174-6}, issn = {0190-5848}, pages = {9}, year = {2018}, abstract = {This Research-to-Practice paper examines the practical application of various forms of collaborative learning in MOOCs. Since 2012, about 60 MOOCs in the wider context of Information Technology and Computer Science have been conducted on our self-developed MOOC platform. The platform is also used by several customers, who either run their own platform instances or use our white label platform. We, as well as some of our partners, have experimented with different approaches in collaborative learning in these courses. Based on the results of early experiments, surveys amongst our participants, and requests by our business partners we have integrated several options to offer forms of collaborative learning to the system. The results of our experiments are directly fed back to the platform development, allowing to fine tune existing and to add new tools where necessary. In the paper at hand, we discuss the benefits and disadvantages of decisions in the design of a MOOC with regard to the various forms of collaborative learning. While the focus of the paper at hand is on forms of large group collaboration, two types of small group collaboration on our platforms are briefly introduced.}, language = {en} } @misc{KayemMeinelWolthusen2018, author = {Kayem, Anne Voluntas dei Massah and Meinel, Christoph and Wolthusen, Stephen D.}, title = {Smart micro-grid systems security and privacy preface}, series = {Smart micro-grid systems security and privacy}, volume = {71}, journal = {Smart micro-grid systems security and privacy}, publisher = {Springer}, address = {Dordrecht}, isbn = {978-3-319-91427-5}, doi = {10.1007/978-3-319-91427-5_1}, pages = {VII -- VIII}, year = {2018}, abstract = {Studies indicate that reliable access to power is an important enabler for economic growth. To this end, modern energy management systems have seen a shift from reliance on time-consuming manual procedures , to highly automated management , with current energy provisioning systems being run as cyber-physical systems . Operating energy grids as a cyber-physical system offers the advantage of increased reliability and dependability , but also raises issues of security and privacy. In this chapter, we provide an overview of the contents of this book showing the interrelation between the topics of the chapters in terms of smart energy provisioning. We begin by discussing the concept of smart-grids in general, proceeding to narrow our focus to smart micro-grids in particular. Lossy networks also provide an interesting framework for enabling the implementation of smart micro-grids in remote/rural areas, where deploying standard smart grids is economically and structurally infeasible. To this end, we consider an architectural design for a smart micro-grid suited to low-processing capable devices. We model malicious behaviour, and propose mitigation measures based properties to distinguish normal from malicious behaviour .}, language = {en} } @misc{SukmanaTorkuraChengetal.2018, author = {Sukmana, Muhammad Ihsan Haikal and Torkura, Kennedy A. and Cheng, Feng and Meinel, Christoph and Graupner, Hendrik}, title = {Unified logging system for monitoring multiple cloud storage providers in cloud storage broker}, series = {32ND International Conference on Information Networking (ICOIN)}, journal = {32ND International Conference on Information Networking (ICOIN)}, publisher = {IEEE}, address = {New York}, isbn = {978-1-5386-2290-2}, doi = {10.1109/ICOIN.2018.8343081}, pages = {44 -- 49}, year = {2018}, abstract = {With the increasing demand for personal and enterprise data storage service, Cloud Storage Broker (CSB) provides cloud storage service using multiple Cloud Service Providers (CSPs) with guaranteed Quality of Service (QoS), such as data availability and security. However monitoring cloud storage usage in multiple CSPs has become a challenge for CSB due to lack of standardized logging format for cloud services that causes each CSP to implement its own format. In this paper we propose a unified logging system that can be used by CSB to monitor cloud storage usage across multiple CSPs. We gather cloud storage log files from three different CSPs and normalise these into our proposed log format that can be used for further analysis process. We show that our work enables a coherent view suitable for data navigation, monitoring, and analytics.}, language = {en} } @article{AmbassaKayemWolthusenetal.2018, author = {Ambassa, Pacome L. and Kayem, Anne Voluntas dei Massah and Wolthusen, Stephen D. and Meinel, Christoph}, title = {Inferring private user behaviour based on information leakage}, series = {Smart Micro-Grid Systems Security and Privacy}, volume = {71}, journal = {Smart Micro-Grid Systems Security and Privacy}, publisher = {Springer}, address = {Dordrecht}, isbn = {978-3-319-91427-5}, doi = {10.1007/978-3-319-91427-5_7}, pages = {145 -- 159}, year = {2018}, abstract = {In rural/remote areas, resource constrained smart micro-grid (RCSMG) architectures can provide a cost-effective power supply alternative in cases when connectivity to the national power grid is impeded by factors such as load shedding. RCSMG architectures can be designed to handle communications over a distributed lossy network in order to minimise operation costs. However, due to the unreliable nature of lossy networks communication data can be distorted by noise additions that alter the veracity of the data. In this chapter, we consider cases in which an adversary who is internal to the RCSMG, deliberately distorts communicated data to gain an unfair advantage over the RCSMG's users. The adversary's goal is to mask malicious data manipulations as distortions due to additive noise due to communication channel unreliability. Distinguishing malicious data distortions from benign distortions is important in ensuring trustworthiness of the RCSMG. Perturbation data anonymisation algorithms can be used to alter transmitted data to ensure that adversarial manipulation of the data reveals no information that the adversary can take advantage of. However, because existing data perturbation anonymisation algorithms operate by using additive noise to anonymise data, using these algorithms in the RCSMG context is challenging. This is due to the fact that distinguishing benign noise additions from malicious noise additions is a difficult problem. In this chapter, we present a brief survey of cases of privacy violations due to inferences drawn from observed power consumption patterns in RCSMGs centred on inference, and propose a method of mitigating these risks. The lesson here is that while RCSMGs give users more control over power management and distribution, good anonymisation is essential to protecting personal information on RCSMGs.}, language = {en} } @misc{TorkuraSukmanaMeinigetal.2018, author = {Torkura, Kennedy A. and Sukmana, Muhammad Ihsan Haikal and Meinig, Michael and Kayem, Anne V. D. M. and Cheng, Feng and Meinel, Christoph and Graupner, Hendrik}, title = {Securing cloud storage brokerage systems through threat models}, series = {Proceedings IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA)}, journal = {Proceedings IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA)}, publisher = {IEEE}, address = {New York}, isbn = {978-1-5386-2195-0}, issn = {1550-445X}, doi = {10.1109/AINA.2018.00114}, pages = {759 -- 768}, year = {2018}, abstract = {Cloud storage brokerage is an abstraction aimed at providing value-added services. However, Cloud Service Brokers are challenged by several security issues including enlarged attack surfaces due to integration of disparate components and API interoperability issues. Therefore, appropriate security risk assessment methods are required to identify and evaluate these security issues, and examine the efficiency of countermeasures. A possible approach for satisfying these requirements is employment of threat modeling concepts, which have been successfully applied in traditional paradigms. In this work, we employ threat models including attack trees, attack graphs and Data Flow Diagrams against a Cloud Service Broker (CloudRAID) and analyze these security threats and risks. Furthermore, we propose an innovative technique for combining Common Vulnerability Scoring System (CVSS) and Common Configuration Scoring System (CCSS) base scores in probabilistic attack graphs to cater for configuration-based vulnerabilities which are typically leveraged for attacking cloud storage systems. This approach is necessary since existing schemes do not provide sufficient security metrics, which are imperatives for comprehensive risk assessments. We demonstrate the efficiency of our proposal by devising CCSS base scores for two common attacks against cloud storage: Cloud Storage Enumeration Attack and Cloud Storage Exploitation Attack. These metrics are then used in Attack Graph Metric-based risk assessment. Our experimental evaluation shows that our approach caters for the aforementioned gaps and provides efficient security hardening options. Therefore, our proposals can be employed to improve cloud security.}, language = {en} } @misc{MalchowBauerMeinel2018, author = {Malchow, Martin and Bauer, Matthias and Meinel, Christoph}, title = {Embedded smart home — remote lab MOOC with optional real hardware experience for over 4000 students}, series = {Proceedings of 2018 IEEE Global Engineering Education Conference (EDUCON)}, journal = {Proceedings of 2018 IEEE Global Engineering Education Conference (EDUCON)}, publisher = {IEEE}, address = {New York}, isbn = {978-1-5386-2957-4}, issn = {2165-9567}, doi = {10.1109/EDUCON.2018.8363353}, pages = {1104 -- 1111}, year = {2018}, abstract = {MOOCs (Massive Open Online Courses) become more and more popular for learners of all ages to study further or to learn new subjects of interest. The purpose of this paper is to introduce a different MOOC course style. Typically, video content is shown teaching the student new information. After watching a video, self-test questions can be answered. Finally, the student answers weekly exams and final exams like the self test questions. Out of the points that have been scored for weekly and final exams a certificate can be issued. Our approach extends the possibility to receive points for the final score with practical programming exercises on real hardware. It allows the student to do embedded programming by communicating over GPIO pins to control LEDs and measure sensor values. Additionally, they can visualize values on an embedded display using web technologies, which are an essential part of embedded and smart home devices to communicate with common APIs. Students have the opportunity to solve all tasks within the online remote lab and at home on the same kind of hardware. The evaluation of this MOOCs indicates the interesting design for students to learn an engineering technique with new technology approaches in an appropriate, modern, supporting and motivating way of teaching.}, language = {en} }