@article{ChujfiLaRocheMeinel2017, author = {Chujfi-La-Roche, Salim and Meinel, Christoph}, title = {Matching cognitively sympathetic individual styles to develop collective intelligence in digital communities}, series = {AI \& society : the journal of human-centred systems and machine intelligence}, volume = {35}, journal = {AI \& society : the journal of human-centred systems and machine intelligence}, number = {1}, publisher = {Springer}, address = {New York}, issn = {0951-5666}, doi = {10.1007/s00146-017-0780-x}, pages = {5 -- 15}, year = {2017}, abstract = {Creation, collection and retention of knowledge in digital communities is an activity that currently requires being explicitly targeted as a secure method of keeping intellectual capital growing in the digital era. In particular, we consider it relevant to analyze and evaluate the empathetic cognitive personalities and behaviors that individuals now have with the change from face-to-face communication (F2F) to computer-mediated communication (CMC) online. This document proposes a cyber-humanistic approach to enhance the traditional SECI knowledge management model. A cognitive perception is added to its cyclical process following design thinking interaction, exemplary for improvement of the method in which knowledge is continuously created, converted and shared. In building a cognitive-centered model, we specifically focus on the effective identification and response to cognitive stimulation of individuals, as they are the intellectual generators and multiplicators of knowledge in the online environment. Our target is to identify how geographically distributed-digital-organizations should align the individual's cognitive abilities to promote iteration and improve interaction as a reliable stimulant of collective intelligence. The new model focuses on analyzing the four different stages of knowledge processing, where individuals with sympathetic cognitive personalities can significantly boost knowledge creation in a virtual social system. For organizations, this means that multidisciplinary individuals can maximize their extensive potential, by externalizing their knowledge in the correct stage of the knowledge creation process, and by collaborating with their appropriate sympathetically cognitive remote peers.}, language = {en} } @misc{MalchowRenzBaueretal.2017, author = {Malchow, Martin and Renz, Jan and Bauer, Matthias and Meinel, Christoph}, title = {Embedded smart home}, series = {11th Annual IEEE International Systems Conference (SysCon)}, journal = {11th Annual IEEE International Systems Conference (SysCon)}, publisher = {IEEE}, address = {New York}, isbn = {978-1-5090-4623-2}, issn = {1944-7620}, doi = {10.1109/SYSCON.2017.7934728}, pages = {195 -- 200}, year = {2017}, abstract = {The popularity of MOOCs has increased considerably in the last years. A typical MOOC course consists of video content, self tests after a video and homework, which is normally in multiple choice format. After solving this homeworks for every week of a MOOC, the final exam certificate can be issued when the student has reached a sufficient score. There are also some attempts to include practical tasks, such as programming, in MOOCs for grading. Nevertheless, until now there is no known possibility to teach embedded system programming in a MOOC course where the programming can be done in a remote lab and where grading of the tasks is additionally possible. This embedded programming includes communication over GPIO pins to control LEDs and measure sensor values. We started a MOOC course called "Embedded Smart Home" as a pilot to prove the concept to teach real hardware programming in a MOOC environment under real life MOOC conditions with over 6000 students. Furthermore, also students with real hardware have the possibility to program on their own real hardware and grade their results in the MOOC course. Finally, we evaluate our approach and analyze the student acceptance of this approach to offer a course on embedded programming. We also analyze the hardware usage and working time of students solving tasks to find out if real hardware programming is an advantage and motivating achievement to support students learning success.}, language = {en} } @misc{AlibabaieGhasemzadehMeinel2017, author = {Alibabaie, Najmeh and Ghasemzadeh, Mohammad and Meinel, Christoph}, title = {A variant of genetic algorithm for non-homogeneous population}, series = {International Conference Applied Mathematics, Computational Science and Systems Engineering 2016}, volume = {9}, journal = {International Conference Applied Mathematics, Computational Science and Systems Engineering 2016}, publisher = {EDP Sciences}, address = {Les Ulis}, issn = {2271-2097}, doi = {10.1051/itmconf/20170902001}, pages = {8}, year = {2017}, abstract = {Selection of initial points, the number of clusters and finding proper clusters centers are still the main challenge in clustering processes. In this paper, we suggest genetic algorithm based method which searches several solution spaces simultaneously. The solution spaces are population groups consisting of elements with similar structure. Elements in a group have the same size, while elements in different groups are of different sizes. The proposed algorithm processes the population in groups of chromosomes with one gene, two genes to k genes. These genes hold corresponding information about the cluster centers. In the proposed method, the crossover and mutation operators can accept parents with different sizes; this can lead to versatility in population and information transfer among sub-populations. We implemented the proposed method and evaluated its performance against some random datasets and the Ruspini dataset as well. The experimental results show that the proposed method could effectively determine the appropriate number of clusters and recognize their centers. Overall this research implies that using heterogeneous population in the genetic algorithm can lead to better results.}, language = {en} } @misc{GawronChengMeinel2017, author = {Gawron, Marian and Cheng, Feng and Meinel, Christoph}, title = {PVD: Passive Vulnerability Detection}, series = {8th International Conference on Information and Communication Systems (ICICS)}, journal = {8th International Conference on Information and Communication Systems (ICICS)}, publisher = {IEEE}, address = {New York}, isbn = {978-1-5090-4243-2}, issn = {2471-125X}, doi = {10.1109/IACS.2017.7921992}, pages = {322 -- 327}, year = {2017}, abstract = {The identification of vulnerabilities relies on detailed information about the target infrastructure. The gathering of the necessary information is a crucial step that requires an intensive scanning or mature expertise and knowledge about the system even though the information was already available in a different context. In this paper we propose a new method to detect vulnerabilities that reuses the existing information and eliminates the necessity of a comprehensive scan of the target system. Since our approach is able to identify vulnerabilities without the additional effort of a scan, we are able to increase the overall performance of the detection. Because of the reuse and the removal of the active testing procedures, our approach could be classified as a passive vulnerability detection. We will explain the approach and illustrate the additional possibility to increase the security awareness of users. Therefore, we applied the approach on an experimental setup and extracted security relevant information from web logs.}, language = {en} } @misc{TorkuraSukmanaChengetal.2017, author = {Torkura, Kennedy A. and Sukmana, Muhammad Ihsan Haikal and Cheng, Feng and Meinel, Christoph}, title = {Leveraging cloud native design patterns for security-as-a-service applications}, series = {IEEE International Conference on Smart Cloud (SmartCloud)}, journal = {IEEE International Conference on Smart Cloud (SmartCloud)}, publisher = {Institute of Electrical and Electronics Engineers}, address = {New York}, isbn = {978-1-5386-3684-8}, doi = {10.1109/SmartCloud.2017.21}, pages = {90 -- 97}, year = {2017}, abstract = {This paper discusses a new approach for designing and deploying Security-as-a-Service (SecaaS) applications using cloud native design patterns. Current SecaaS approaches do not efficiently handle the increasing threats to computer systems and applications. For example, requests for security assessments drastically increase after a high-risk security vulnerability is disclosed. In such scenarios, SecaaS applications are unable to dynamically scale to serve requests. A root cause of this challenge is employment of architectures not specifically fitted to cloud environments. Cloud native design patterns resolve this challenge by enabling certain properties e.g. massive scalability and resiliency via the combination of microservice patterns and cloud-focused design patterns. However adopting these patterns is a complex process, during which several security issues are introduced. In this work, we investigate these security issues, we redesign and deploy a monolithic SecaaS application using cloud native design patterns while considering appropriate, layered security counter-measures i.e. at the application and cloud networking layer. Our prototype implementation out-performs traditional, monolithic applications with an average Scanner Time of 6 minutes, without compromising security. Our approach can be employed for designing secure, scalable and performant SecaaS applications that effectively handle unexpected increase in security assessment requests.}, language = {en} } @article{OmotoshoEmuoyibofarheMeinel2017, author = {Omotosho, Adebayo and Emuoyibofarhe, Justice and Meinel, Christoph}, title = {Securing e-prescription from medical identity theft using steganography and antiphishing techniques}, series = {Journal of applied security research}, volume = {12}, journal = {Journal of applied security research}, publisher = {Routledge, Taylor \& Francis Group}, address = {Philadelphia}, issn = {1936-1610}, doi = {10.1080/19361610.2017.1315788}, pages = {447 -- 461}, year = {2017}, abstract = {Drug prescription is among the health care process that usually makes references to the patients' medical and insurance information among other personal data, because this information is very vital and delicate, it should be adequately protected from identity thieves. This article aims at securing Electronic Prescription (EP) in order to minimize patient's data theft and foster patients' trust of EP system. This paper presents a steganography and antiphishing technique for preventing medical identity theft in EP. The proposed EP system design focused on the security features in the prescriber and dispensers' modules of EP by ensuring the prescriber sends the prescription of the patient in a safe manner and to the right dispenser without the interference of fake third parties. Hexadecimal steganography image system is used to cover and secure the sent prescription details. Malicious electronic dispensing system is prevented through an authentication technique where a dispenser uses a captcha together with a one-time password, and the web server encrypted token for prescriber's device authentication. The steganography system is evaluated using Peak Signal to Noise Ratio (PSNR). The system implementation results showed that steganography and antiphishing techniques are capable of providing a secure EP systems.}, language = {en} } @misc{StaubitzWilkinsHagedornetal.2017, author = {Staubitz, Thomas and Wilkins, Christian and Hagedorn, Christiane and Meinel, Christoph}, title = {The Gamification of a MOOC Platform}, series = {Proceedings of 2017 IEEE Global Engineering Education Conference (EDUCON)}, journal = {Proceedings of 2017 IEEE Global Engineering Education Conference (EDUCON)}, publisher = {IEEE}, address = {New York}, isbn = {978-1-5090-5467-1}, issn = {2165-9567}, doi = {10.1109/EDUCON.2017.7942952}, pages = {883 -- 892}, year = {2017}, abstract = {Massive Open Online Courses (MOOCs) have left their mark on the face of education during the recent years. At the Hasso Plattner Institute (HPI) in Potsdam, Germany, we are actively developing a MOOC platform, which provides our research with a plethora of e-learning topics, such as learning analytics, automated assessment, peer assessment, team-work, online proctoring, and gamification. We run several instances of this platform. On openHPI, we provide our own courses from within the HPI context. Further instances are openSAP, openWHO, and mooc.HOUSE, which is the smallest of these platforms, targeting customers with a less extensive course portfolio. In 2013, we started to work on the gamification of our platform. By now, we have implemented about two thirds of the features that we initially have evaluated as useful for our purposes. About a year ago we activated the implemented gamification features on mooc.HOUSE. Before activating the features on openHPI as well, we examined, and re-evaluated our initial considerations based on the data we collected so far and the changes in other contexts of our platforms.}, language = {en} }