TLS-Level Security for Low Power Industrial IoT Network Infrastructures

Mades, J.; Ebelt, Gerd; Janjic, Boris; Lauer, Frederik; Rheinländer, Carl C.; Wehn, Norbert

doi:10.23919/date48585.2020.9116285

Cited by 9 publications

(6 citation statements)

References 5 publications

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“…The figure shows that the cryptographic calculations of most KEMs account for a very small fraction of the total handshake latency. This observation is contrary to the investigations of conventional handshakes, where it was shown that the (software-based) computation of ECDHE has a significant impact on latency [ 1 ]. In contrast, as shown by the yellow bar, the larger public keys and ciphertexts of the KEMs cause a medium to large increase in handshake latency.…”

Section: Resultscontrasting

confidence: 65%

“…Secure communication is essential for many IIoT applications, as the data that is exchanged via the internet may contain safety-critical, infrastructural information as well as industrial secrets [ 1 ]. In the vast majority, this security is established through cryptographic protocols such as Transport Layer Security (TLS) and relies on the combination of symmetric cryptography and Public Key Cryptography (PKC).…”

Section: Introductionmentioning

confidence: 99%

“…Although these are worst-case scenarios, the meaning of privacy, integrity and authenticity in IoT is hard to overestimate. Even lightweight sensor devices collect sensitive data when they are deployed in sensible, private environments, in industrial applications or in critical infrastructure [ 1 ]. Therefore, the usage of cryptography to provide this security should be considered essential.…”

Section: Introductionmentioning

confidence: 99%

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Secure IoT in the Era of Quantum Computers—Where Are the Bottlenecks?

Schöffel

Lauer

Rheinländer

et al. 2022

Sensors

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Recent progress in quantum computers severely endangers the security of widely used public-key cryptosystems and of all communication that relies on it. Thus, the US NIST is currently exploring new post-quantum cryptographic algorithms that are robust against quantum computers. Security is seen as one of the most critical issues of low-power IoT devices—even with pre-quantum public-key cryptography—since IoT devices have tight energy constraints, limited computational power and strict memory limitations. In this paper, we present, to the best of our knowledge, the first in-depth investigation of the application of potential post-quantum key encapsulation mechanisms (KEMs) and digital signature algorithms (DSAs) proposed in the related US NIST process to a state-of-the-art, TLS-based, low-power IoT infrastructure. We implemented these new KEMs and DSAs in such a representative infrastructure and measured their impact on energy consumption, latency and memory requirements during TLS handshakes on an IoT edge device. Based on our investigations, we gained the following new insights. First, we show that the main contributor to high TLS handshake latency is the higher bandwidth requirement of post-quantum primitives rather than the cryptographic computation itself. Second, we demonstrate that a smart combination of multiple DSAs yields the most energy-, latency- and memory-efficient public key infrastructures, in contrast to NIST’s goal to standardize only one algorithm. Third, we show that code-based, isogeny-based and lattice-based algorithms can be implemented on a low-power IoT edge device based on an off-the-shelf Cortex M4 microcontroller while maintaining viable battery runtimes. This is contrary to much research that claims dedicated hardware accelerators are mandatory.

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Section: Resultscontrasting

confidence: 65%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Secure IoT in the Era of Quantum Computers—Where Are the Bottlenecks?

Schöffel

Lauer

Rheinländer

et al. 2022

Sensors

Self Cite

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“…The types of encryption algorithms employed for the security enhancement of cloud data was discussed along with their drawbacks. Authors in [25][26][27] proposed a scheme for the attainment of security in the low power IoT devices. The main focus was to ensure the transport layer security.…”

Section: Related Workmentioning

confidence: 99%

Optimized Energy Efficient Strategy for Data Reduction Between Edge Devices in Cloud-IoT

Mukherjee¹,

Ghosh²,

Pal³

et al. 2022

Computers, Materials &Amp; Continua

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Numerous Internet of Things (IoT) systems produce massive volumes of information that must be handled and answered in a quite short period. The growing energy usage related to the migration of data into the cloud is one of the biggest problems. Edge computation helps users unload the workload again from cloud near the source of the information that must be handled to save time, increase security, and reduce the congestion of networks. Therefore, in this paper, Optimized Energy Efficient Strategy (OEES) has been proposed for extracting, distributing, evaluating the data on the edge devices. In the initial stage of OEES, before the transmission state, the data gathered from edge devices are supported by a fast error like reduction that is regarded as the largest energy user of an IoT system. The initial stage is followed by the reconstructing and the processing state. The processed data is transmitted to the nodes through controlled deep learning techniques. The entire stage of data collection, transmission and data reduction between edge devices uses less energy. The experimental results indicate that the volume of data transferred decreases and does not impact the professional data performance and predictive accuracy. Energy consumption of 7.38 KJ and energy conservation of 55.57 kJ was found in the proposed OEES scheme. Predictive accuracy is 97.5 percent, data performance rate was 97.65 percent, and execution time is 14.49 ms.

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“…First we present a general summary of security protocols in all layers and later focus on the taxonomies and prior research applying specifically to Physical Layer Security. [7], [8], [9], [10] [11], [12], [13], [14] Network Layer [15], [16], [17] [18], [19] [20], [21], [22] Transport Layer [23], [24], [25], [26] [27], [28], [29], [30] App. Layer [31], [32], [33] [34], [35], [36] Protocol stack security occurs at multiple layers of the OSI models as illustrated in Table I.…”

Section: Introductionmentioning

confidence: 99%

Physical Layer Security for Beyond 5G: Ultra Secure Low Latency Communications

Yerrapragada

Eisman

Kelley

2021

IEEE Open J. Commun. Soc.

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If Beyond-5G(B5G)/6G is to support critical infrastructure worldwide, there must be an effort to jointly integrate low latency and privacy into wireless protocols. This research analyzes new schemes for securing applications at low latency by extending Physical Layer Security (PLS) algorithms to B5G/6G systems. We design protocols that advance a specific form of Physical Layer Security, known as Key-based Physical Layer Security, from the theoretical realm into the practical. One form of a Key-based algorithm obscures information from eavesdroppers by mapping it to cleverly rotated reference signals. For such a scheme, prior work has found that the two-way exchange of completely private information involves six OFDM symbol times, not including synchronization. By developing a protocol that makes the most optimum use of time-frequency resources, we show that it is possible to achieve two-way private exchange and synchronization in only four symbol times -the least latency possible. A significant simulation result indicates that our improved protocol achieves sub-1 ms two-way latency, including re-transmissions. We also illustrate a protocol that shows how Key-based Physical Layer Security can privatize critical PHY layer functions such as cell search. Lastly, additional results show the performance of the PLS algorithm in terms of Key Bit Error Rates and secret key transmission rates.

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TLS-Level Security for Low Power Industrial IoT Network Infrastructures

Cited by 9 publications

References 5 publications

Secure IoT in the Era of Quantum Computers—Where Are the Bottlenecks?

Secure IoT in the Era of Quantum Computers—Where Are the Bottlenecks?

Optimized Energy Efficient Strategy for Data Reduction Between Edge Devices in Cloud-IoT

Physical Layer Security for Beyond 5G: Ultra Secure Low Latency Communications

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