TerraSwarm funded PI Bjoern Hartmann has been named as the interim faculty director of the Jacobs Institute for Design Innovation at UC Berkeley. PI Bjoern Hartmann is an Assistant Professor in the EECS Department and has served as the chief technology officer for the Jacobs Institute for Design Innovation since its inception. His research on Human-Computer Interaction centers on novel design,
prototyping, and implementation tools for the era of post-personal
computing.
The Jacobs Institute for Design Innovation works to educate top innovators at the intersection of design and technology, and to provide students with opportunities for hands-on experiences working in interdisciplinary teams to address real world problems. Focusing on human-centered engineering, the Jacobs Institute for Design Innovation facilitates an increased role for design in undergraduate engineering education at UC Berkeley.
The TerraSwarm Research Center Blog covers news items about the TerraSwarm Research Center at http://www.terraswarm.org. The TerraSwarm Research Center, launched on January 15, 2013, is addressing the huge potential (and associated risks) of pervasive integration of smart, networked sensors and actuators into our connected world. The center is funded by the STARnet phase of the Focus Center Research Program (FCRP) administered by the Semiconductor Research Corporation (SRC).
Monday, April 18, 2016
Thursday, April 14, 2016
TerraSwarm Funded Paper "SMT-Based Observer Design for Cyber-Physical Systems Under Sensor Attacks" Receives Best Paper Award at the IEEE International Conference on Cyber-Physical Systems (ICCPS 2016)
TerraSwarm funded paper, "SMT-Based Observer Design for Cyber-Physical Systems Under Sensor Attacks," has received best paper award at the IEEE International Conference on Cyber-Physical Systems (ICCPS 2016), held as part of CPS Week in Vienna, Austria, from April 11-14 2016.
The paper states: This work was partially sponsored by the NSF award 1136174, by DARPA under agreement number FA8750-12-2-0247, by TerraSwarm, one of six centers of STARnet, a Semiconductor Research Corporation program sponsored by MARCO and DARPA, and by the NSF project ExCAPE: Expeditions in Computer Augmented Program Engineering (award 1138996 and 1139138.)
Yasser Shoukry, Michelle Chong, Masashi Wakaiki, Pierluigi Nuzzo, Alberto Sangiovanni-Vincentelli, Sanjit A. Seshia, Joao P. Hespanha, Paulo Tabuada. "SMT-Based Observer Design for Cyber-Physical Systems Under Sensor Attacks". ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS 2016), Vienna, Austria, April 11, 2016.
Abstract:
We introduce a scalable observer architecture to estimate the states of a discrete-time linear-time-invariant (LTI) system whose sensors can be manipulated by an attacker. Given the maximum number of attacked sensors, we build on previous results on necessary and sufficient conditions for state estimation, and propose a novel multi-modal Luenberger (MML) observer based on efficient Satisfiability Modulo Theory (SMT) solving.We present two techniques to reduce the complexity of the estimation problem. As a first strategy, instead of a bank of distinct observers, we use a family of filters sharing a single dynamical equation for the states, but different output equations, to generate estimates corresponding to different subsets of sensors. Such a multi-modal observer can reduce the memory usage of the observer from an exponential to a linear function of the number of sensors. We then develop an efficient SMT-based decision procedure that is able to reason about the estimates of the MML observer, obtained out of potentially corrupted sensors, detect at runtime which sets of sensors are attack-free, and use them to obtain a correct state estimate. We provide proofs of convergence for our algorithm and report simulation results to compare its runtime performance with alternative techniques. Our algorithm scales well for large systems (including up to 5000 sensors) for which many previously proposed algorithms are not implementable due to excessive memory and time requirements. Finally, we illustrate the effectiveness of our algorithm on the design of resilient power distribution systems.
The paper states: This work was partially sponsored by the NSF award 1136174, by DARPA under agreement number FA8750-12-2-0247, by TerraSwarm, one of six centers of STARnet, a Semiconductor Research Corporation program sponsored by MARCO and DARPA, and by the NSF project ExCAPE: Expeditions in Computer Augmented Program Engineering (award 1138996 and 1139138.)
Yasser Shoukry, Michelle Chong, Masashi Wakaiki, Pierluigi Nuzzo, Alberto Sangiovanni-Vincentelli, Sanjit A. Seshia, Joao P. Hespanha, Paulo Tabuada. "SMT-Based Observer Design for Cyber-Physical Systems Under Sensor Attacks". ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS 2016), Vienna, Austria, April 11, 2016.
Abstract:
We introduce a scalable observer architecture to estimate the states of a discrete-time linear-time-invariant (LTI) system whose sensors can be manipulated by an attacker. Given the maximum number of attacked sensors, we build on previous results on necessary and sufficient conditions for state estimation, and propose a novel multi-modal Luenberger (MML) observer based on efficient Satisfiability Modulo Theory (SMT) solving.We present two techniques to reduce the complexity of the estimation problem. As a first strategy, instead of a bank of distinct observers, we use a family of filters sharing a single dynamical equation for the states, but different output equations, to generate estimates corresponding to different subsets of sensors. Such a multi-modal observer can reduce the memory usage of the observer from an exponential to a linear function of the number of sensors. We then develop an efficient SMT-based decision procedure that is able to reason about the estimates of the MML observer, obtained out of potentially corrupted sensors, detect at runtime which sets of sensors are attack-free, and use them to obtain a correct state estimate. We provide proofs of convergence for our algorithm and report simulation results to compare its runtime performance with alternative techniques. Our algorithm scales well for large systems (including up to 5000 sensors) for which many previously proposed algorithms are not implementable due to excessive memory and time requirements. Finally, we illustrate the effectiveness of our algorithm on the design of resilient power distribution systems.
Monday, April 11, 2016
SRC TECHCON 2016 - Abstract Submission Deadline Wednesday, April 13, 2016
The deadline for abstract submission for TECHCON 2016 is 3pm EST on Wednesday, April 13, 2016. TECHCON 2016 will be held at the Renaissance Hotel in Austin, Texas on September 11-13, 2016.
Additional information from the Semiconductor Research Corporation's (SRC) email announcement: TECHCON is designed to foster technical interaction among SRC's academic, government, and industry communities. The TECHCON 2016 program will include technical paper sessions showcasing research funded by SRC research programs through the presentation of 160 papers and accompanying posters. Technical paper presentations will be fifteen minutes in length and will be organized according to related technologies. TechFair will feature a poster display from each presenter based on his/her presentation. TechFair sessions provide an excellent opportunity for students to discuss their research projects in a one-on-one setting.
Call for abstracts: https://www.src.org/calendar/e005107/
Additional information from the Semiconductor Research Corporation's (SRC) email announcement: TECHCON is designed to foster technical interaction among SRC's academic, government, and industry communities. The TECHCON 2016 program will include technical paper sessions showcasing research funded by SRC research programs through the presentation of 160 papers and accompanying posters. Technical paper presentations will be fifteen minutes in length and will be organized according to related technologies. TechFair will feature a poster display from each presenter based on his/her presentation. TechFair sessions provide an excellent opportunity for students to discuss their research projects in a one-on-one setting.
Call for abstracts: https://www.src.org/calendar/e005107/
Friday, April 8, 2016
TerraSwarm Funded Paper "Control Improvisation with Probabilistic Temporal Specifications" Receives Best Paper Award at 1st IEEE International Conference on Internet-of-Things Design and Implementation (IoTDI'16)
TerraSwarm funded paper "Control Improvisation with Probabilistic Temporal Specifications" received best paper award at the 1st IEEE International Conference on Internet-of-Things Design and Implementation (IoTDI'16) in Berlin, Germany.
The paper states: "This work was supported in part by TerraSwarm, one of six centers of STARnet, a Semiconductor Research Corporation program sponsored by MARCO and DARPA."
Ilge Akkaya, Daniel J. Fremont, Rafael Valle, Alexandre Donze, Edward A. Lee, Sanjit A. Seshia. "Control Improvisation with Probabilistic Temporal Specifications". IEEE International Conference on Internet-of-Things Design and Implementation (IoTDI'16), April 2-4, 2016.
Abstract:
We consider the problem of generating randomized control sequences for complex systems typically actuated by human agents. Our approach leverages a concept known as control improvisation, which is based on a combination of learning and synthesis from formal specifications. We learn from existing data a generative model (for instance, an explicit duration hidden Markov model, or EDHMM) and then supervise this model in order to guarantee that the generated sequences satisfy some desirable specifications given in Probabilistic Computation Tree Logic (PCTL). We present an implementation of our approach and apply it to the problem of mimicking the use of lighting appliances in a residential unit, with potential applications to home security and resource management. We present experimental results showing that our approach produces realistic control sequences, similar to recorded data based on human actuation, while satisfying suitable formal requirements.
The paper states: "This work was supported in part by TerraSwarm, one of six centers of STARnet, a Semiconductor Research Corporation program sponsored by MARCO and DARPA."
Ilge Akkaya, Daniel J. Fremont, Rafael Valle, Alexandre Donze, Edward A. Lee, Sanjit A. Seshia. "Control Improvisation with Probabilistic Temporal Specifications". IEEE International Conference on Internet-of-Things Design and Implementation (IoTDI'16), April 2-4, 2016.
Abstract:
We consider the problem of generating randomized control sequences for complex systems typically actuated by human agents. Our approach leverages a concept known as control improvisation, which is based on a combination of learning and synthesis from formal specifications. We learn from existing data a generative model (for instance, an explicit duration hidden Markov model, or EDHMM) and then supervise this model in order to guarantee that the generated sequences satisfy some desirable specifications given in Probabilistic Computation Tree Logic (PCTL). We present an implementation of our approach and apply it to the problem of mimicking the use of lighting appliances in a residential unit, with potential applications to home security and resource management. We present experimental results showing that our approach produces realistic control sequences, similar to recorded data based on human actuation, while satisfying suitable formal requirements.
Wednesday, April 6, 2016
Team Led by TerraSwarm-Funded PI Jan Rabaey Awarded a Two-Year Grant from STARnet
TerraSwarm-funded PI Jan Rabaey and co-principal
investigators Ana Arias, Michel Maharbiz, Pieter Abbeel, Jose Carmena, and
Bjorn Hartmann, have been awarded a two-year $551,019 grant via the Semiconductor Research Corporation (STARnet's SRC) to
develop a first generation Human Intranet.
Conceived to take advantage of the proliferation of
connected mobile devices and the resulting data, the Human Intranet is
envisioned as an open, scalable, form fitting platform that seamlessly
integrates an ever-increasing number of sensor, actuation, computation,
storage, communication and energy nodes located on, in, or around the human
body acting in symbiosis with the functions provided by the body itself. A
heterogeneous power and data network consisting of wired and wireless links
provides the communication backbone.
This project will explore a couple of use cases including
hybrid sensory expansion, and enabling higher information output through low-SNR
actuation devices (such as pressure sensitive on-skin keyboards). Designed to
work within an environment where devices connect to each other and collaborate
to fulfill goals, the prototype systems will be built using existing as well as
emerging devices.
Monday, April 4, 2016
DARPA Announces Spectrum Collaboration Challenge (SC2)
DARPA, a sponsor of TerraSwarm through STARnet, has announced the world’s first collaborative machine-intelligence competition, a grand challenge focused on spectrum collaboration.
With the number of devices accessing the electromagnetic spectrum on the rise, this challenge seeks to take advantage of progress and inspire innovation in the fields of artificial intelligence and machine learning. Competing teams will develop smart systems to create radios with machine-learning capabilities to cooperatively optimize the use of the wireless spectrum.
The Challenge addresses a fast-growing need. With an increasing number of devices connected to the wireless spectrum, a more nimble and efficient use of the finite resources will have applications in meeting future demand in ways not possible with the current system of pre-allocation of exclusive access to designated frequencies. The development of low cost software defined radios will also make it feasible to deploy spectrum monitoring on a larger scale.
The Spectrum Collaboration Challenge (SC2) website may be found at http://spectrumcollaborationchallenge.com
With the number of devices accessing the electromagnetic spectrum on the rise, this challenge seeks to take advantage of progress and inspire innovation in the fields of artificial intelligence and machine learning. Competing teams will develop smart systems to create radios with machine-learning capabilities to cooperatively optimize the use of the wireless spectrum.
The Challenge addresses a fast-growing need. With an increasing number of devices connected to the wireless spectrum, a more nimble and efficient use of the finite resources will have applications in meeting future demand in ways not possible with the current system of pre-allocation of exclusive access to designated frequencies. The development of low cost software defined radios will also make it feasible to deploy spectrum monitoring on a larger scale.
The Spectrum Collaboration Challenge (SC2) website may be found at http://spectrumcollaborationchallenge.com
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