Trust and Security of Embedded Smart Devices in Advanced Logistics Systems

VanYe, Christopher M.; Li, Beatrice E.; Koch, Andrew; Luu, Mai N.; Adekunle, Rahman O.; Moghadasi, Negin; Collier, Zachary A.; Polmateer, Thomas L.; Barnes, David; Slutzky, David; Manasco, Mark C.; Lambert, James H.

doi:10.1109/sieds52267.2021.9483779

Cited by 7 publications

(2 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ongoing work in the field of engineering systems is focused on disrupted order rather than disrupted performance. The multi-criteria preference method (Karvetski et al, 2010;Moghadasi, Collier, et al, 2022;Montibeller et al, 2006;VanYe et al, 2021) can be used to identify priorities, the most and least disruptive scenarios, emergent conditions, criteria, and initiatives (Moghadasi, Luu, et al, 2022). Examples of priorities are the importance orders of endangered species, radiological, chemical, or biological contaminants, critical infrastructure assets, future projects or investments, policies, key personnel or organizations, geographic locations, and others.…”

Section: Discussionmentioning

confidence: 99%

On Evaluating System Resilience by the Degree of Order Disruption

Moghadasi,

Lambert

2023

INCOSE International Symp

Self Cite

View full text Add to dashboard Cite

Resilience curves describe the diminished performance of a system over time following a shock, with the area integral above the curve representing the persistence of the lost performance. For example, in a power system, the lost power generation is measured in megawatts, and the persistence of the disruption is in megawatt hours; in a communications system, the performance in gigabits per second can be integrated over time as gigabits. The persistence metrics from the examples are not comparable. Ongoing engineering systems work is focused on disrupted order rather than disrupted performance. The Kendall's tau statistic is used to compare an initial, pre‐shock set of priorities with the priorities after the shock. This paper will describe complementing system performance with system order in the estimation and integration of resilience curves, thus enabling a new quantification of resilience as a disruption of system order can be used across application domains of risk analysis.

show abstract

Section: Discussionmentioning

confidence: 99%

On Evaluating System Resilience by the Degree of Order Disruption

Moghadasi,

Lambert

2023

INCOSE International Symp

Self Cite

View full text Add to dashboard Cite

show abstract

“…Te rapid development of computing and communications technology has led to the widespread use of embedded systems in smart devices. Given the increasing connectivity of systems and the difculty of providing comprehensive security, embedded systems are often attacked by malicious parties [1][2][3][4][5]. For example, application-level rootkits typically use code with Trojan characteristics to replace the binary code of a normal application, or they can use other means to modify the behavior of an existing application [6].…”

Section: Introductionmentioning

confidence: 99%

TZEAMM: An Efficient and Secure Active Measurement Method Based on TrustZone

Liu

Lai

Liu

et al. 2023

Security and Communication Networks

View full text Add to dashboard Cite

With the rapid development of computer and communication technology, embedded systems are widely used in smart devices. The increasing connectivity of these systems and the difficulties in providing comprehensive security have made such devices vulnerable to malicious attacks. Passive defense technologies and traffic-based intrusion detection technologies are not fully effective against such attacks. Trusted execution environment (TEE) technology can ensure system security against unknown attacks to some extent. Most researchers use TrustZone to implement TEE. However, the problem is that the API interface of the TEE module which provides the service is not secure. Therefore, to actively defend against attacks, we developed a trusted computing active measurement architecture based on TrustZone. To overcome the serious problem that modules in the trusted execution environment need to be passively invoked to provide services, we have proposed an active measurement closed-loop immune mechanism. To reduce the trusted computing base and reduce the performance overhead, we removed certain functional modules from the trusted execution environment. In addition, based on this architecture, we developed a trust chain and dynamic measurement method to ensure the security of the target applications. We changed the traditional attack response method, which requires the entire system to be restarted after an attack, by developing a fallback mechanism that is more suitable for the system. Finally, we verified the effectiveness of the architecture by developing an attack model. Performance testing and analysis showed that the architecture reduced the impact of the security mechanisms on the system. In the future, we will extend our research to more fine-grained measurements.

show abstract