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LEFT Lab

leftlab@left.engr.usu.edu

Workshop: Trustworthy Computing and Digital Democracy

LEFT Lab

Sat, 27 Aug 2022 11:18:26 -0600 last edited: Sat, 27 Aug 2022 11:20:58 -0600

Our public workshop event, "Trustworthy Computing and Digital Democracy," is happening today! The topics are Electronic Reliability, Voting and Finance Technologies, Fault Tolerance and Error Correction, and Novelty Bias in Technology.

#^Click here for registration and event details.

To access the discussion slides, follow the link below...

#^Discussion Slides: Digital Democracy

Workshop: Treading in a Sea of Data

LEFT Lab

Tue, 23 Aug 2022 10:23:38 -0600

LEFT Lab

Thu, 21 Nov 2019 14:25:53 -0700

Winstead wrote the following post Thu, 21 Nov 2019 14:23:46 -0700

Congratulations to Rejoy Mathews on his thesis defense
Rejoy Mathews passed his thesis defense today. He demonstrated a new framework for probabilistic decoding in Low Density Parity Check Codes. We extend our congratulations to Rejoy and thanks to his committee members @Zhen Zhang and Ryan Davidson!

Rejoy Mathews

Thu, 21 Nov 2019 15:04:24 -0700

Thank you for your guidance @Winstead

Paper: International Symposium on Turbo Codes (to appear)

LEFT Lab

Tue, 04 Sep 2018 01:09:01 -0600 last edited: Tue, 04 Sep 2018 18:43:51 -0600

Our survey paper on error correction with stochastic and noise enhanced decoding algorithms has been accepted for presentation at the 2018 Intl Symp on Turbo Codes (ISTC) in Hong Kong. This work was authored with LEFT student Tasnuva Tithi and collaborators Emmanuel Boutillon (Lab-STICC, Univeriste de Bretagne Sud, France) and Fakhreddine Ghaffari (ETIS Lab, Université Cergy-Pontoise, France).

Recent Advances on Stochastic and Noise Enhanced Methods in Error Correction Decoders

This paper offers a review of recent developments in non-deterministic error correction decoding methods, which can be described in two broad classes. The first class uses stochastic computation to emulate the arithmetic operations of conventional decoding algorithms. The second class achieves noise enhancement by randomly perturbing the calculations of a standard decoder. Stochastic decoders inherit analysis techniques from the conventional algorithms they emulate, but the noise-enhanced algorithms are newer, more difficult to explain, and not yet fully understood. We describe a Markov chain analysis technique to both explain and optimize noise enhancement in these algorithms. Circuit implementation is also discussed, including both conventional hardware architectures and circuits based on memristor threshold logic, where memristor non-determinism can be exploited for noise enhancement.

#publications #GDBF #LDPC #BitFlipping #NoiseEnhancement #StochasticResonance

Paper: IEEE Trans. on Circuits and Systems I

LEFT Lab

Fri, 31 Aug 2018 21:24:32 -0600

This paper, led by our collaborators at the ETIS lab in France, represents our latest work in probabilistic bit-flipping algorithms for Low-Density Parity-Check (LDPC) codes used in telecommunications and solid-state memory applications. The paper has been accepted to appear in a future issue of the journal, and is now available via IEEE Early Access.

#^A Probabilistic Parallel Bit-Flipping Decoder for Low-Density Parity-Check Codes - IEEE Journals & Magazine

This paper presents a new bit flipping (BF) decoder, called the probabilistic parallel BF (PPBF) for low-density parity-check codes on the binary symmetric channel. In the PPBF, the flipping operation is performed in a probabilistic manner which is shown to significantly improve the error correction performance. The advantage of the PPBF also comes from the fact that no global computation is required during the decoding process and that all the computations can be executed in the local computing units and in parallel. The PPBF provides a considerable improvement of the operating frequency and complexity, compared to other known BF decoders, while obtaining a significant gain in error correction. An improved version of the PPBF, called non-syndrome PPBF is also introduced, in which the global syndrome check is moved out of the critical path and a new terminating mechanism is proposed. In order to show the superiority of the new decoders in terms of hardware efficiency and decoding throughput, the corresponding hardware architectures are presented in Section II. The application-specific integrated circuit synthesis results confirm that the operating frequency of the proposed decoders is significantly improved, compared to that of the BF decoders in the literature while requiring lower complexity to be efficiently implemented.

#publications #LDPC #StochasticResonance #NoiseEnhancement #BitFlipping #GDBF

Paper: American Controls Conference (2)

LEFT Lab

Fri, 31 Aug 2018 21:17:19 -0600

This is the second of two papers authored by LEFT Lab PhD student Soodeh Dadras which appeared in the proceedings of the 2018 American Controls Conference.

#^Reachable Set Analysis of Vehicular Platooning in Adversarial Environment - IEEE Conference Publication

In this paper, we propose a method based on reachable set theory to investigate adversarial behavior in automated vehicle platoons. Vehicular platoons have been developed to increase highway throughput and safety, and to enhance driving comfort. The resulting deployment of cyber-physical technology in critical infrastructure is increasingly attractive to both hackers and security researchers. To ensure safety and privacy of vehicle occupants, it is essential to identify the vulnerabilities of platoon systems. In this paper, we study the attacker's capabilities under input constraints during two types of attack: motion modification and integral attacks. Using ellipsoidal techniques, we investigate the extent of an attacker's ability to manipulate the control variables and states of a platoon resulting in oscillatory motion or collision. The outcomes of our analysis are demonstrated by an example.

#publications #AutonomousVehicles #CPS #security

Paper: American Controls Conference

LEFT Lab

Fri, 31 Aug 2018 21:14:48 -0600

This is the first of two papers authored by LEFT Lab PhD student Soodeh Dadras which appeared in the proceedings of the 2018 American Controls Conference.

#^Identification of the Attacker in Cyber-Physical Systems with an Application to Vehicular Platooning in Adversarial Environment - IEEE Conference Publication

Cyber-Physical Systems (CPS) are systems with tight coupling between integration of physical, computational and networking components. Control systems play an important role to help these systems to adhere to their desired performance. Having a reliable and secure control system which can cope with high risk situations and various attacks is one of the bottlenecks for real world cyber-physical systems. It has been proven that using control modification attack, where the adversary modifies the sensor information or the control law, can disrupt the desired performance of the system. In this paper, a novel scheme is presented to detect and identify the attacker in control systems. The detection algorithm is the combination of the system identification method and machine learning technique which effectively recognizes the malicious actors. The proposed algorithm is efficient, viable, and simply adequate to address the challenges posed by complex cyber-physical systems. Finally, the efficiency of the presented method is verified with the case of platooning in an adversarial environment.

#publications #AutonomousVehicles #CPS #security

Paper: IEEE Trans. on Vehicular Technology

LEFT Lab

Thu, 30 Aug 2018 22:33:18 -0600 last edited: Fri, 31 Aug 2018 21:15:19 -0600

LEFT Lab PhD student Tasnuva Tithi was the lead author of this study, which included collaborators at Virginia Tech and the University of Arizona. The paper appeared in the Transactions' May 2018 issue. This article is an example of our work on threat detection for cyberphysical security.

#^Analysis of Friendly Jamming for Secure Location Verification of Vehicles for Intelligent Highways - IEEE Journals & Magazine

Abstract:
In this paper, we present friendly jamming for secure location verification of vehicles in Intelligent Transportation Systems (ITS). In friendly jamming confidential information is obscured from eavesdroppers through the use of opportunistic jamming on the part of the parties engaged in communication. Secure location verification enables the infrastructure in an ITS to verify the position claims of a vehicle in an adversarial setting. We present a method for effectively using friendly jamming and distance bounding together to verify the location and velocity of vehicles, and detect any deviation of claims by a “prover” vehicle that is trying to prove its position and velocity to the infrastructure. The technique can be used to verify velocity and position claim of a vehicle, while keeping the feasible velocity and position lie by an attacker in a negligible range. Our analysis shows that in realistic traffic, friendly jamming is an improvement over comparable work, reducing position falsification by 86.66% to 92% for a typical attacker. The proposed technique also outperforms existing localization techniques for multiple colluding attackers, providing security against up to three colluding attackers, where colluders coordinate their movement and report information to help a single attacker achieve its goal.

#publications #AutonomousVehicles #CPS #security

LEFT Lab

Thu, 30 Aug 2018 21:48:51 -0600

Left Lab updated their cover photo

LEFT Lab

Thu, 30 Aug 2018 21:17:22 -0600

Left Lab updated their profile photo

LEFT Lab

Thu, 30 Aug 2018 03:37:00 -0600

Left Lab updated their profile photo