Smart Ticket Protection: An Architecture for Cyber-Protecting Physical Tickets Using Digitally Signed Random Pattern Markers

In order to counter forgeries of tickets for public transport or mass events, a method to validate them, using printed unique random pattern markers was developed. These markers themselves are unforgeable by their physically random distribution. To assure their authenticity, however, they have to be cryptographically protected and equipped with an environment for successful validation, combining physical and cyber security protection. This paper describes an architecture for cryptographically protecting these markers, which are stored in Aztec codes on physical tickets, in order to assure that only an authorized printer can generate a valid Aztec code of such a pattern, thus providing forge protection in combination with the randomness and uniqueness of the pattern. Nevertheless, the choice of the signature algorithm is heavily constrained by the sizes of the pattern, ticket provider data, metadata and the signature confronted by the data volume the code hold. Therefore, this paper also defines an example for a signature layout for the proposed architecture. This allows for a lightweight ticket validation system that is both physically and cryptographically secured to form a smart solution for mass access verification for both shorter to longer periods at relatively low cost.Comment: 4 pages, 2 figure

Best practices for HPM-assisted performance engineering on modern multicore processors

Many tools and libraries employ hardware performance monitoring (HPM) on modern processors, and using this data for performance assessment and as a starting point for code optimizations is very popular. However, such data is only useful if it is interpreted with care, and if the right metrics are chosen for the right purpose. We demonstrate the sensible use of hardware performance counters in the context of a structured performance engineering approach for applications in computational science. Typical performance patterns and their respective metric signatures are defined, and some of them are illustrated using case studies. Although these generic concepts do not depend on specific tools or environments, we restrict ourselves to modern x86-based multicore processors and use the likwid-perfctr tool under the Linux OS.Comment: 10 pages, 2 figure

Understanding Android Obfuscation Techniques: A Large-Scale Investigation in the Wild

In this paper, we seek to better understand Android obfuscation and depict a holistic view of the usage of obfuscation through a large-scale investigation in the wild. In particular, we focus on four popular obfuscation approaches: identifier renaming, string encryption, Java reflection, and packing. To obtain the meaningful statistical results, we designed efficient and lightweight detection models for each obfuscation technique and applied them to our massive APK datasets (collected from Google Play, multiple third-party markets, and malware databases). We have learned several interesting facts from the result. For example, malware authors use string encryption more frequently, and more apps on third-party markets than Google Play are packed. We are also interested in the explanation of each finding. Therefore we carry out in-depth code analysis on some Android apps after sampling. We believe our study will help developers select the most suitable obfuscation approach, and in the meantime help researchers improve code analysis systems in the right direction