Secure Data Communication in Autonomous V2X Systems

In Vehicle-to-Everything (V2X) communication systems, vehicles as well as infrastructure devices can interact and exchange data with each other. This capability is used to implement intelligent transportation systems applications. Data confidentiality and integrity need to be preserved in unverified and untrusted environments. In this paper, we propose a solution that provides (a) role-based and attribute-based access control to encrypted data and (b) encrypted search over encrypted data. Vehicle Records contain sensitive information about the owners and vehicles in encrypted form with attached access control policies and policy enforcement engine. Our solution supports decentralized and distributed data exchange, which is essential in V2X systems, where a Central Authority is not required to enforce access control policies. Furthermore, we facilitate querying encrypted Vehicle Records through Structured Query Language (SQL) queries. Vehicle Records are stored in a database in untrusted V2X cloud environment that is prone to provide the attackers with a large attack surface. Big datasets, stored in cloud, can be used for data analysis, such as traffic pattern analysis. Our solution protects sensitive vehicle and owner information from curious or malicious information cloud administrators. Support of indexing improves performance of queries that are forwarded to relevant encrypted Vehicle Records, which are stored in the cloud. We measure the performance overhead of our security solution based on self-protecting Vehicle Records with encrypted search capabilities in V2X communication systems and analyze the effect of security over safety

Data Protection in Transit and at Rest with Leakage Detection

In service-oriented architecture, services can communicate and share data among themselves. This thesis presents a solution that allows detecting several types of data leakages made by authorized insiders to unauthorized services. My solution provides role-based and attribute-based access control for data so that each service can access only those data subsets for which the service is authorized, considering a context and service’s attributes such as security level of the web browser and trust level of service. My approach provides data protection in transit and at rest for both centralized and peer-to-peer service architectures. The methodology ensures confidentiality and integrity of data, including data stored in untrusted cloud. In addition to protecting data against malicious or curious cloud or database administrators, the capability of running a search through encrypted data, using SQL queries, and building analytics over encrypted data is supported. My solution is implemented in the “WAXEDPRUNE” (Web-based Access to Encrypted Data Processing in Untrusted Environments) project, funded by Northrop Grumman Cybersecurity Research Consortium. WAXEDPRUNE methodology is illustrated in this thesis for two use cases, including a Hospital Information System with secure storage and exchange of Electronic Health Records and a Vehicle-to-Everything communication system with secure exchange of vehicle’s and drivers’ data, as well as data on road events and road hazards. To help with investigating data leakage incidents in service-oriented architecture, integrity of provenance data needs to be guaranteed. For that purpose, I integrate WAXEDPRUNE with IBM Hyperledger Fabric blockchain network, so that every data access, transfer or update is recorded in a public blockchain ledger, is non-repudiatable and can be verified at any time in the future. The work on this project, called “Blockhub,” is in progress

End-to-End Database Software Security

End-to-end security is essential for relational database software. Most database management software provide data protection at the server side and in transit, but data are no longer protected once they arrive at the client software. In this paper, we present a methodology that, in addition to server-side security, protects data in transit and at rest on the application client side. Our solution enables flexible attribute-based and role-based access control, such that, for a given role or user with a given set of attributes, access can be granted to a relation, a column, or even to a particular data cell of the relation, depending on the data content. Our attribute-based access control model considers the client’s attributes, such as versions of the operating system and the web browser, as well as type of the client’s device. The solution supports decentralized data access and peer-to-peer data sharing in the form of an encrypted and digitally signed spreadsheet container that stores data retrieved by SQL queries from a database, along with data privileges. For extra security, keys for data encryption and decryption are generated on the fly. We show that our solution is successfully integrated with the PostgreSQL® database management system and enables more flexible access control for added security

Machine Learning Models to Enhance the Science of Cognitive Autonomy

Intelligent Autonomous Systems (IAS) are highly cognitive, reflective, multitask-able, and effective in knowledge discovery. Examples of IAS include software systems that are capable of automatic reconfiguration, autonomous vehicles, network of sensors with reconfigurable sensory platforms, and an unmanned aerial vehicle (UAV) respecting privacy by deciding to turn off its camera when pointing inside a private residence. Research is needed to build systems that can monitor their environment and interactions, learn their capabilities and limitations, and adapt to meet the mission objectives with limited or no human intervention. The systems should be fail-safe and should allow for graceful degradations while continuing to meet the mission objectives. In this paper, we provide an overview of our proposed new methodologies and workflows, and survey the existing approaches and new ones that can advance the science of autonomy in smart systems through enhancements in real-time control, auto-reconfigurability, monitoring, adaptability, and trust. This paper also provides the theoretical framework behind IAS

Secure Data Communication in Autonomous V2X Systems

In Vehicle-to-Everything (V2X) communication systems, vehicles as well as infrastructure devices can interact and exchange data with each other. This capability is used to implement intelligent transportation systems applications. Data confidentiality and integrity need to be preserved in unverified and untrusted environments. In this paper, we propose a solution that provides (a) role-based and attribute-based access control to encrypted data and (b) encrypted search over encrypted data. Vehicle Records contain sensitive information about the owners and vehicles in encrypted form with attached access control policies and policy enforcement engine. Our solution supports decentralized and distributed data exchange, which is essential in V2X systems, where a Central Authority is not required to enforce access control policies. Furthermore, we facilitate querying encrypted Vehicle Records through Structured Query Language (SQL) queries. Vehicle Records are stored in a database in untrusted V2X cloud environment that is prone to provide the attackers with a large attack surface. Big datasets, stored in cloud, can be used for data analysis, such as traffic pattern analysis. Our solution protects sensitive vehicle and owner information from curious or malicious information cloud administrators. Support of indexing improves performance of queries that are forwarded to relevant encrypted Vehicle Records, which are stored in the cloud. We measure the performance overhead of our security solution based on self-protecting Vehicle Records with encrypted search capabilities in V2X communication systems and analyze the effect of security over safety.This is a manuscript of a proceeding published as Ulybyshev, Denis, Aala Oqab Alsalem, Bharat Bhargava, Savvas Savvides, Ganapathy Mani, and Lotfi ben Othmane. "Secure data communication in autonomous v2x systems." In 2018 IEEE International Congress on Internet of Things (ICIOT), (2018): 156-163. DOI: 10.1109/ICIOT.2018.00029. Posted with permission.</p