Bit-Level Automotive Controller Area Network Message Reverse Framework Based on Linear Regression.

Modern intelligent and networked vehicles are increasingly equipped with electronic control units (ECUs) with increased computing power. These electronic devices form an in-vehicle network via the Controller Area Network (CAN) bus, the de facto standard for modern vehicles. Although many ECUs provide convenience to drivers and passengers, they also increase the potential for cyber security threats in motor vehicles. Numerous attacks on vehicles have been reported, and the commonality among these attacks is that they inject malicious messages into the CAN network. To close the security holes of CAN, original equipment manufacturers (OEMs) keep the Database CAN (DBC) file describing the content of CAN messages, confidential. This policy is ineffective against cyberattacks but limits in-depth investigation of CAN messages and hinders the development of in-vehicle intrusion detection systems (IDS) and CAN fuzz testing. Current research reverses CAN messages through tokenization, machine learning, and diagnostic information matching to obtain details of CAN messages. However, the results of these algorithms yield only a fraction of the information specified in the DBC file regarding CAN messages, such as field boundaries and message IDs associated with specific functions. In this study, we propose multiple linear regression-based frameworks for bit-level inversion of CAN messages that can approximate the inversion of DBC files. The framework builds a multiple linear regression model for vehicle behavior and CAN traffic, filters the candidate messages based on the decision coefficients, and finally locates the bits describing the vehicle behavior to obtain the data length and alignment based on the model parameters. Moreover, this work shows that the system has high reversion accuracy and outperforms existing systems in boundary delineation and filtering relevant messages in actual vehicles.

B(C6F5)3-Catalyzed C3-Selective C-H Borylation of Indoles: Synthesis, Intermediates, and Reaction Mechanism.

Without the addition of any additives and production of any small molecules, C3-borylated indoles and transfer hydrogenated indolines have been simultaneously achieved by a B(C6F5)3-catalyzed disproportionation reaction of a broad range of indoles with catecholborane. This catalyst system exhibits excellent catalytic performance for practical applications, such as easy scale-up under solvent-free conditions and long catalytic lifetime over ten sequential additions of starting materials. A combined mechanistic study, including isolation and characterization of key reaction intermediates, analysis of the disproportionation nature of the reaction, in situ NMR of the reaction, and analysis of detailed experimental data, has led to a possible reaction mechanism which illustrates pathways for the formation of both major products and byproducts. Understanding the reaction mechanism enables us to successfully suppress side reactions by choosing appropriate substrates and adjusting the amount of catecholborane needed. More importantly, with an elevated reaction temperature, we could achieve the convergent disproportionation reaction of indoles, in which indolines were continuously oxidized to indoles for the next disproportionation catalytic cycle. Near quantitative conversions and up to 98% yields of various C3-selective borylated indoles were achieved, without any additives or H2 acceptors.

B(C6F5)3-Catalyzed (Convergent) Disproportionation Reaction of Indoles.

A metal-free B(C6F5)3-catalyzed approach is developed for the disproportionation reaction of a series of indoles with various hydrosilanes, without any additives such as base and production of any small molecule such as dihydrogen. This boron catalyst system also exhibits excellent catalytic performance for practical application, such as catalyst loading as low as 0.01 mol % under solvent-free conditions, and a long-life catalytic performance highlighted by a constant catalytic activity being maintained and excellent yields being achieved for the desired products over 10 sequential additions of starting materials. On the basis of characterization of key intermediates through a series of in situ NMR reactions and detailed experimental data, we proposed a reaction mechanism which illustrated pathways for the formation of different products, including both major products and byproducts. Additional control experiments were conducted to support our proposed mechanism. Understanding the mechanism enables us to successfully suppress side reactions by choosing appropriate substrates and hydrosilanes. More importantly, the use of an elevated reaction temperature for continuous oxidation of the resulting indoline to indole makes the convergent disproportionation reaction an ideal atom-economical process. Near-quantitative conversions and up to 99% yields of C3-silylated indoles were achieved for various indoles with trisubstituted silanes, Ph3SiH (2b) or Ph2MeSiH (2d).