Evaluation of PTP Security Controls on gPTP

In recent years, the scientific community has been focusing on deterministic Ethernet, which has helped drive the adoption of Time-Sensitive Networking (TSN) standards. Precision Time Protocol (PTP), specified in IEEE1588, is a TSN standard that enables network devices to be synchronized with a degree of precision that is noticeably higher than other Ethernet synchronization protocols. Generic Precision Time Protocol (gPTP), a profile of PTP, is designed to have low latency and jitter, which makes it suitable for industrial applications. However, like PTP, gPTP does not have any built-in security measures. In this work, we assess the efficacy of additional security mechanisms that were suggested for inclusion in IEEE 1588 (PTP) 2019. The analysis consists of implementing these security mechanisms on a physical gPTP-capable testbed and evaluating them on several high-risk attacks against gPTP

An Intrusion Detection System Against Rogue Master Attacks on gPTP

Due to the promise of deterministic Ethernet networking, Time Sensitive Network (TSN) standards are gaining popularity in the vehicle on-board networks sector. Among these, Generalized Precision Time Protocol (gPTP) allows network devices to be synchronized with a greater degree of precision than other synchronization protocols, such as Network Time Protocol (NTP). However, gPTP was developed without security measures, making it susceptible to a variety of attacks. Adding security controls is the initial step in securing the protocol. However, due to current gPTP design limitations, this countermeasure is insufficient to protect against all types of threats. In this paper, we present a novel supervised Machine Learning (ML)-based pipeline for the detection of high-risk rogue master attacks

MK2 and ETV1 Are Prognostic Factors in Esophageal Adenocarcinomas

Background. Esophageal cancer is ranked in the top ten of diagnosed tumors worldwide. Even though improvements in survival could be noticed over the last years, prognosis remains poor. ETS translocation variant 1 (ETV1) is a member of a family of transcription factors and is phosphorylated by mitogen-activated protein kinase (MAPK)-activated protein kinase 2 (MK2). Aim of this study was to evaluate the prognostic role of MK2 and ETV1 in esophageal cancer. Methods. Consecutive patients that underwent surgical resection at the department of surgery at the Medical University of Vienna between 1991 and 2012 were included into this study. After microscopic analysis, tissue micro arrays (TMAs) were created and immunohistochemistry was performed with antibodies against MK2 and ETV1. Results. 323 patients were included in this study. Clinical data was achieved from a prospective patient data base. Nuclear overexpression of MK2 was observed in 143 (44.3%) cases for nuclear staining and in 142 (44.0%) cases a cytoplasmic overexpression of MK2 was observed. Nuclear and cytoplasmic ETV1 overexpression was detected in 20 cases (6.2%) and 30 cases (9.3%), respectively. In univariate survival analysis, cMK2 and nETV1 were found to be significantly associated with patients' overall survival. Whereas overexpression of cMK2 was associated with shorter, nETV1 was associated with longer overall survival. In multivariate survival analysis, both cMK2 and nETV1 were found to be independent prognostic factors for the subgroup of EAC as well. Discussion. Expression of MK2 and ETV1 are prognostic factors in patients, with esophageal adenocarcinoma

Assessing the Impact of Attacks on an Automotive Ethernet Time Synchronization Testbed

Time Sensitive Network (TSN) standards are gaining traction in the scientific community and automotive Original Equipment Manufacturers (OEMs) due their promise of deterministic Ethernet networking. Among these standards, Generalized Precision Time Protocol (gPTP) - IEEE 802.1AS - allows network devices to be synchronized with a precision far higher than other synchronization standards, such as Network Time Protocol (NTP). gPTP is a profile of Precision Time Protocol (PTP) which, due to its robustness to delay variations, has been designated for automotive applications. Nonetheless, gPTP was designed without security controls, which makes it vulnerable to a number of attacks. This work reveals a critical vulnerability caused by a common implementation practice that opens the door to spoofing attacks on gPTP. To assess the impact of this vulnerability, we built two real gPTP-capable testbeds. Our results show high risks of this vulnerability destabilizing the system functionality

Dynamic Maps for Highly Automated Driving - Generation, Distribution and Provision

With an ever-increasing number of vehicles roaming the streets and a general intensification of ongoing daily traffic the current vehicular safety systems are not able to reduce the number of traffic accidents further. As the majority of severe or deadly traffic accidents nowadays is caused by human error, car manufacturers and researchers alike focus on the self-driving vehicle as a promising solution to this problem, as a machine is unaffected from human conditions such as tiredness or drunk driving. To enhance the overall achievable driving safety and comfort the self-driving vehicles rely on an additional map database, besides the hardware sensor system installed onboard. The so-called High Definition Map (HD Map), a highly precise virtual model of the actual real-world provides detailed information about the ongoing traffic situation ahead of the car's sensor ranges. Otherwise critical traffic situations can be resolved by this a priori knowledge and if necessary, a handover of the driving control back to a human driver can be triggered. The maintenance of the HD Map is a major challenge, as due to the importance of the map for the self-driving vehicle map updates have to be realized in much shorter time (minutes instead of months) compared to established concepts common for human-oriented digital navigation maps. This thesis provides contributions in the areas of Distribution, Generation and Provision of such map updates, as the key communication challenges of the maintenance procedure. Our first contribution is the development, implementation and evaluation of a protocol that realizes the context-specific distribution of partial and incremental map updates. The protocol has been designed with the prerequisites and requirements of a self-driving vehicle in mind. To achieve the efficient dissemination of updates to all cars the protocol relies on infrastructure-based (cellular) and ad hoc communication (WLAN) between the vehicles. The performance of the protocol is evaluated based on realistic traffic simulations and actual map content. As our second contribution, we develop and implement an algorithm that detects changes in the road infrastructure (e.g. induced by construction sides) based solely on low-cost sensor information. This detection algorithm facilitates the succeeding update generation of the map data in the identified area. We evaluate the capabilities of the detection algorithm under a real-world data set in the example of a highway construction site scenario. To enhance the provision of map updates and vehicular sensor data via wireless communication, we conduct our third and most comprehensive contribution. We focus on the design and enhancement of a variety of different techniques and concepts to obtain broad knowledge about the serving wireless network to be provided in a subsequent step as valuable information to related transmission scheduling algorithms. These techniques and concepts include the measurement and prediction of the various performance indicators of actual deployed cellular networks, via low-cost hardware and software, as well as their further usage in simulation and network connectivity maps, always with an emphasis on easy deployability and the reutilization of existing components. Overall, this thesis presents essential contributions, which in their collectivity support the realization of a robust, dynamic and reliable maintenance cycle of an HD Map for self-driving vehicles