scholarly journals Security-Related Hardware Cost Optimization for CAN FD-Based Automotive Cyber-Physical Systems

Sensors ◽  
2021 ◽  
Vol 21 (20) ◽  
pp. 6807
Author(s):  
Yong Xie ◽  
Yili Guo ◽  
Sheng Yang ◽  
Jian Zhou ◽  
Xiaobai Chen
Keyword(s):  
Heuristic Algorithm ◽  
Design Space Exploration ◽  
State Of The Art ◽  
Real Data ◽  
Cyber Physical Systems ◽  
Data Sets ◽  
Efficient Design ◽  
Delay Constraint ◽  
Hardware Cost ◽  
Physical Systems

The introduction of various networks into automotive cyber-physical systems (ACPS) brings great challenges on security protection of ACPS functions, the auto industry recommends to adopt the hardware security module (HSM)-based multicore ECU to secure in-vehicle networks while meeting the delay constraint. However, this approach incurs significant hardware cost. Consequently, this paper aims to reduce security enhancing-related hardware cost by proposing two efficient design space exploration (DSE) algorithms, namely, stepwise decreasing-based heuristic algorithm (SDH) and interference balancing-based heuristic algorithm (IBH), which explore the task assignment, task scheduling, and message scheduling to minimize the number of required HSMs. Experiments on both synthetical and real data sets show that the proposed SDH and IBH are superior than state-of-the-art algorithm, and the advantage of SDH and IBH becomes more obvious as the increase about the percentage of security-critical tasks. For synthetic data sets, the hardware cost can be reduced by 61.4% and 45.6% averagely for IBH and SDH, respectively; for real data sets, the hardware cost can be reduced by 64.3% and 54.4% on average for IBH and SDH, respectively. Furthermore, IBH is better than SDH in most cases, and the runtime of IBH is two or three orders of magnitude smaller than SDH and state-of-the-art algorithm.

scholarly journals ARCH-COMP 2019 Category Report: Falsification

10.29007/68dk ◽  
2019 ◽  
Author(s):  
Gidon Ernst ◽  
Paolo Arcaini ◽  
Alexandre Donzé ◽  
Georgios Fainekos ◽  
Logan Mathesen ◽  
...  
Keyword(s):  
Temporal Logic ◽  
State Of The Art ◽  
Cyber Physical Systems ◽  
The State ◽  
Base Line ◽  
Physical Systems ◽  
The Future ◽  
Friendly Competition ◽  
Initial Base

This report presents the results from the 2019 friendly competition in the ARCH workshop for the falsification of temporal logic specifications over Cyber-Physical Systems. We describe the organization of the competition and how it differs from previous years. We give background on the participating teams and tools and discuss the selected benchmarks and results. The benchmarks are available on the ARCH website1, as well as in the competition’s gitlab repository2. The main outcome of the 2019 competition is a common benchmark repository, and an initial base-line for falsification, with results from multiple tools, which will facilitate comparisons and tracking of the state-of-the-art in falsification in the future.

scholarly journals Medical Cyber-Physical Systems: A Solution to Smart Health and the State of the Art

2021 ◽  
pp. 1-28
Author(s):  
Fulong Chen ◽  
Yuqing Tang ◽  
Canlin Wang ◽  
Jing Huang ◽  
Cheng Huang ◽  
...  
Keyword(s):  
State Of The Art ◽  
Cyber Physical Systems ◽  
The State ◽  
Physical Systems ◽  
Smart Health

scholarly journals Constructing a Lightweight Key-Value Store Based on the Windows Native Features

2019 ◽  
Vol 9 (18) ◽  
pp. 3801 ◽  
Author(s):  
Hyuk-Yoon Kwon
Keyword(s):  
State Of The Art ◽  
Main Idea ◽  
Real Data ◽  
Data Sets ◽  
Parameter Setting ◽  
Data Set ◽  
Multi Level ◽  
Windows Registry ◽  
Best Parameter ◽  
Better Than

In this paper, we propose a method to construct a lightweight key-value store based on the Windows native features. The main idea is providing a thin wrapper for the key-value store on top of a built-in storage in Windows, called Windows registry. First, we define a mapping of the components in the key-value store onto the components in the Windows registry. Then, we present a hash-based multi-level registry index so as to distribute the key-value data balanced and to efficiently access them. Third, we implement basic operations of the key-value store (i.e., Get, Put, and Delete) by manipulating the Windows registry using the Windows native APIs. We call the proposed key-value store WR-Store. Finally, we propose an efficient ETL (Extract-Transform-Load) method to migrate data stored in WR-Store into any other environments that support existing key-value stores. Because the performance of the Windows registry has not been studied much, we perform the empirical study to understand the characteristics of WR-Store, and then, tune the performance of WR-Store to find the best parameter setting. Through extensive experiments using synthetic and real data sets, we show that the performance of WR-Store is comparable to or even better than the state-of-the-art systems (i.e., RocksDB, BerkeleyDB, and LevelDB). Especially, we show the scalability of WR-Store. That is, WR-Store becomes much more efficient than the other key-value stores as the size of data set increases. In addition, we show that the performance of WR-Store is maintained even in the case of intensive registry workloads where 1000 processes accessing to the registry actively are concurrently running.

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