@phdthesis{Cheng2010, author = {Cheng, Feng}, title = {Physical separation technology and its lock-keeper implementation}, address = {Potsdam}, pages = {114 S.}, year = {2010}, language = {en} } @article{RoschkeChengMeinel2012, author = {Roschke, Sebastian and Cheng, Feng and Meinel, Christoph}, title = {An alert correlation platform for memory-supported techniques}, series = {Concurrency and computation : practice \& experience}, volume = {24}, journal = {Concurrency and computation : practice \& experience}, number = {10}, publisher = {Wiley-Blackwell}, address = {Hoboken}, issn = {1532-0626}, doi = {10.1002/cpe.1750}, pages = {1123 -- 1136}, year = {2012}, abstract = {Intrusion Detection Systems (IDS) have been widely deployed in practice for detecting malicious behavior on network communication and hosts. False-positive alerts are a popular problem for most IDS approaches. The solution to address this problem is to enhance the detection process by correlation and clustering of alerts. To meet the practical requirements, this process needs to be finished fast, which is a challenging task as the amount of alerts in large-scale IDS deployments is significantly high. We identifytextitdata storage and processing algorithms to be the most important factors influencing the performance of clustering and correlation. We propose and implement a highly efficient alert correlation platform. For storage, a column-based database, an In-Memory alert storage, and memory-based index tables lead to significant improvements of the performance. For processing, algorithms are designed and implemented which are optimized for In-Memory databases, e.g. an attack graph-based correlation algorithm. The platform can be distributed over multiple processing units to share memory and processing power. A standardized interface is designed to provide a unified view of result reports for end users. The efficiency of the platform is tested by practical experiments with several alert storage approaches, multiple algorithms, as well as a local and a distributed deployment.}, language = {en} } @article{RoschkeChengMeinel2013, author = {Roschke, Sebastian and Cheng, Feng and Meinel, Christoph}, title = {High-quality attack graph-based IDS correlation}, series = {Logic journal of the IGPL}, volume = {21}, journal = {Logic journal of the IGPL}, number = {4}, publisher = {Oxford Univ. Press}, address = {Oxford}, issn = {1367-0751}, doi = {10.1093/jigpal/jzs034}, pages = {571 -- 591}, year = {2013}, abstract = {Intrusion Detection Systems are widely deployed in computer networks. As modern attacks are getting more sophisticated and the number of sensors and network nodes grow, the problem of false positives and alert analysis becomes more difficult to solve. Alert correlation was proposed to analyse alerts and to decrease false positives. Knowledge about the target system or environment is usually necessary for efficient alert correlation. For representing the environment information as well as potential exploits, the existing vulnerabilities and their Attack Graph (AG) is used. It is useful for networks to generate an AG and to organize certain vulnerabilities in a reasonable way. In this article, a correlation algorithm based on AGs is designed that is capable of detecting multiple attack scenarios for forensic analysis. It can be parameterized to adjust the robustness and accuracy. A formal model of the algorithm is presented and an implementation is tested to analyse the different parameters on a real set of alerts from a local network. To improve the speed of the algorithm, a multi-core version is proposed and a HMM-supported version can be used to further improve the quality. The parallel implementation is tested on a multi-core correlation platform, using CPUs and GPUs.}, language = {en} } @inproceedings{KurbelNowakAzodietal.2015, author = {Kurbel, Karl and Nowak, Dawid and Azodi, Amir and Jaeger, David and Meinel, Christoph and Cheng, Feng and Sapegin, Andrey and Gawron, Marian and Morelli, Frank and Stahl, Lukas and Kerl, Stefan and Janz, Mariska and Hadaya, Abdulmasih and Ivanov, Ivaylo and Wiese, Lena and Neves, Mariana and Schapranow, Matthieu-Patrick and F{\"a}hnrich, Cindy and Feinbube, Frank and Eberhardt, Felix and Hagen, Wieland and Plauth, Max and Herscheid, Lena and Polze, Andreas and Barkowsky, Matthias and Dinger, Henriette and Faber, Lukas and Montenegro, Felix and Czach{\´o}rski, Tadeusz and Nycz, Monika and Nycz, Tomasz and Baader, Galina and Besner, Veronika and Hecht, Sonja and Schermann, Michael and Krcmar, Helmut and Wiradarma, Timur Pratama and Hentschel, Christian and Sack, Harald and Abramowicz, Witold and Sokolowska, Wioletta and Hossa, Tymoteusz and Opalka, Jakub and Fabisz, Karol and Kubaczyk, Mateusz and Cmil, Milena and Meng, Tianhui and Dadashnia, Sharam and Niesen, Tim and Fettke, Peter and Loos, Peter and Perscheid, Cindy and Schwarz, Christian and Schmidt, Christopher and Scholz, Matthias and Bock, Nikolai and Piller, Gunther and B{\"o}hm, Klaus and Norkus, Oliver and Clark, Brian and Friedrich, Bj{\"o}rn and Izadpanah, Babak and Merkel, Florian and Schweer, Ilias and Zimak, Alexander and Sauer, J{\"u}rgen and Fabian, Benjamin and Tilch, Georg and M{\"u}ller, David and Pl{\"o}ger, Sabrina and Friedrich, Christoph M. and Engels, Christoph and Amirkhanyan, Aragats and van der Walt, Est{\´e}e and Eloff, J. H. P. and Scheuermann, Bernd and Weinknecht, Elisa}, title = {HPI Future SOC Lab}, editor = {Meinel, Christoph and Polze, Andreas and Oswald, Gerhard and Strotmann, Rolf and Seibold, Ulrich and Schulzki, Bernhard}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-102516}, pages = {iii, 154}, year = {2015}, abstract = {Das Future SOC Lab am HPI ist eine Kooperation des Hasso-Plattner-Instituts mit verschiedenen Industriepartnern. Seine Aufgabe ist die Erm{\"o}glichung und F{\"o}rderung des Austausches zwischen Forschungsgemeinschaft und Industrie. Am Lab wird interessierten Wissenschaftlern eine Infrastruktur von neuester Hard- und Software kostenfrei f{\"u}r Forschungszwecke zur Verf{\"u}gung gestellt. Dazu z{\"a}hlen teilweise noch nicht am Markt verf{\"u}gbare Technologien, die im normalen Hochschulbereich in der Regel nicht zu finanzieren w{\"a}ren, bspw. Server mit bis zu 64 Cores und 2 TB Hauptspeicher. Diese Angebote richten sich insbesondere an Wissenschaftler in den Gebieten Informatik und Wirtschaftsinformatik. Einige der Schwerpunkte sind Cloud Computing, Parallelisierung und In-Memory Technologien. In diesem Technischen Bericht werden die Ergebnisse der Forschungsprojekte des Jahres 2015 vorgestellt. Ausgew{\"a}hlte Projekte stellten ihre Ergebnisse am 15. April 2015 und 4. November 2015 im Rahmen der Future SOC Lab Tag Veranstaltungen vor.}, language = {en} } @article{AzodiChengMeinel2015, author = {Azodi, Amir and Cheng, Feng and Meinel, Christoph}, title = {Event Driven Network Topology Discovery and Inventory Listing Using REAMS}, series = {Wireless personal communications : an international journal}, volume = {94}, journal = {Wireless personal communications : an international journal}, publisher = {Springer}, address = {New York}, issn = {0929-6212}, doi = {10.1007/s11277-015-3061-3}, pages = {415 -- 430}, year = {2015}, abstract = {Network Topology Discovery and Inventory Listing are two of the primary features of modern network monitoring systems (NMS). Current NMSs rely heavily on active scanning techniques for discovering and mapping network information. Although this approach works, it introduces some major drawbacks such as the performance impact it can exact, specially in larger network environments. As a consequence, scans are often run less frequently which can result in stale information being presented and used by the network monitoring system. Alternatively, some NMSs rely on their agents being deployed on the hosts they monitor. In this article, we present a new approach to Network Topology Discovery and Network Inventory Listing using only passive monitoring and scanning techniques. The proposed techniques rely solely on the event logs produced by the hosts and network devices present within a network. Finally, we discuss some of the advantages and disadvantages of our approach.}, language = {en} } @article{SapeginJaegerChengetal.2017, author = {Sapegin, Andrey and Jaeger, David and Cheng, Feng and Meinel, Christoph}, title = {Towards a system for complex analysis of security events in large-scale networks}, series = {Computers \& security : the international journal devoted to the study of the technical and managerial aspects of computer security}, volume = {67}, journal = {Computers \& security : the international journal devoted to the study of the technical and managerial aspects of computer security}, publisher = {Elsevier Science}, address = {Oxford}, issn = {0167-4048}, doi = {10.1016/j.cose.2017.02.001}, pages = {16 -- 34}, year = {2017}, abstract = {After almost two decades of development, modern Security Information and Event Management (SIEM) systems still face issues with normalisation of heterogeneous data sources, high number of false positive alerts and long analysis times, especially in large-scale networks with high volumes of security events. In this paper, we present our own prototype of SIEM system, which is capable of dealing with these issues. For efficient data processing, our system employs in-memory data storage (SAP HANA) and our own technologies from the previous work, such as the Object Log Format (OLF) and high-speed event normalisation. We analyse normalised data using a combination of three different approaches for security analysis: misuse detection, query-based analytics, and anomaly detection. Compared to the previous work, we have significantly improved our unsupervised anomaly detection algorithms. Most importantly, we have developed a novel hybrid outlier detection algorithm that returns ranked clusters of anomalies. It lets an operator of a SIEM system to concentrate on the several top-ranked anomalies, instead of digging through an unsorted bundle of suspicious events. We propose to use anomaly detection in a combination with signatures and queries, applied on the same data, rather than as a full replacement for misuse detection. In this case, the majority of attacks will be captured with misuse detection, whereas anomaly detection will highlight previously unknown behaviour or attacks. We also propose that only the most suspicious event clusters need to be checked by an operator, whereas other anomalies, including false positive alerts, do not need to be explicitly checked if they have a lower ranking. We have proved our concepts and algorithms on a dataset of 160 million events from a network segment of a big multinational company and suggest that our approach and methods are highly relevant for modern SIEM systems.}, 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{PengLiuWangetal.2018, author = {Peng, Junjie and Liu, Danxu and Wang, Yingtao and Zeng, Ying and Cheng, Feng and Zhang, Wenqiang}, title = {Weight-based strategy for an I/O-intensive application at a cloud data center}, series = {Concurrency and computation : practice \& experience}, volume = {30}, journal = {Concurrency and computation : practice \& experience}, number = {19}, publisher = {Wiley}, address = {Hoboken}, issn = {1532-0626}, doi = {10.1002/cpe.4648}, pages = {14}, year = {2018}, abstract = {Applications with different characteristics in the cloud may have different resources preferences. However, traditional resource allocation and scheduling strategies rarely take into account the characteristics of applications. Considering that an I/O-intensive application is a typical type of application and that frequent I/O accesses, especially small files randomly accessing the disk, may lead to an inefficient use of resources and reduce the quality of service (QoS) of applications, a weight allocation strategy is proposed based on the available resources that a physical server can provide as well as the characteristics of the applications. Using the weight obtained, a resource allocation and scheduling strategy is presented based on the specific application characteristics in the data center. Extensive experiments show that the strategy is correct and can guarantee a high concurrency of I/O per second (IOPS) in a cloud data center with high QoS. Additionally, the strategy can efficiently improve the utilization of the disk and resources of the data center without affecting the service quality of applications.}, language = {en} } @article{JaegerGraupnerPelchenetal.2018, author = {Jaeger, David and Graupner, Hendrik and Pelchen, Chris and Cheng, Feng and Meinel, Christoph}, title = {Fast Automated Processing and Evaluation of Identity Leaks}, series = {International journal of parallel programming}, volume = {46}, journal = {International journal of parallel programming}, number = {2}, publisher = {Springer}, address = {New York}, issn = {0885-7458}, doi = {10.1007/s10766-016-0478-6}, pages = {441 -- 470}, year = {2018}, abstract = {The relevance of identity data leaks on the Internet is more present than ever. Almost every week we read about leakage of databases with more than a million users in the news. Smaller but not less dangerous leaks happen even multiple times a day. The public availability of such leaked data is a major threat to the victims, but also creates the opportunity to learn not only about security of service providers but also the behavior of users when choosing passwords. Our goal is to analyze this data and generate knowledge that can be used to increase security awareness and security, respectively. This paper presents a novel approach to the processing and analysis of a vast majority of bigger and smaller leaks. We evolved from a semi-manual to a fully automated process that requires a minimum of human interaction. Our contribution is the concept and a prototype implementation of a leak processing workflow that includes the extraction of digital identities from structured and unstructured leak-files, the identification of hash routines and a quality control to ensure leak authenticity. By making use of parallel and distributed programming, we are able to make leaks almost immediately available for analysis and notification after they have been published. Based on the data collected, this paper reveals how easy it is for criminals to collect lots of passwords, which are plain text or only weakly hashed. We publish those results and hope to increase not only security awareness of Internet users but also security on a technical level on the service provider side.}, language = {en} }