11.7 Building Resistant Systems: From Temperature Awareness to Attack Resistance

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Date: Thursday 22 March 2018
Time: 14:00 - 15:30
Location / Room: Konf. 5

Chair:
Marina Zapater, EPFL, CH

Co-Chair:
Georg Becker, ESMT Berlin, DE

This session explores new methods in building reliable and secure systems, especially in larger SoCs. Temperature-induced stress can impact the reliability of digital systems. Temperature fluctuations can also be exploited as side channels. This session first explores the two side of this coin by discussing a novel temperature-aware chiplet placing algorithm in 2.5D systems and by showing how transmission bandwidth encoded as a temperature signal can be maximized. Then, the rest of the session highlights advances in PUFs that are resistant against lastest-generation attacks, and particularly integration of PUFs in larger systems.

TimeLabelPresentation Title
Authors
14:0011.7.1LEVERAGING THERMALLY-AWARE CHIPLET ORGANIZATION IN 2.5D SYSTEMS TO RECLAIM DARK SILICON
Speaker:
Yenai Ma, Boston University, US
Authors:
Furkan Eris1, Ajay Joshi1, Andrew B. Kahng2, Yenai Ma1, Saiful Mojumder1 and Tiansheng Zhang1
1Boston University, US; 2UCSD, US
Abstract
As on-chip power densities of manycore systems continue to increase, one cannot simultaneously run all the cores due to thermal constraints. This phenomenon, known as the 'dark silicon' problem, leads to inactive regions on the chip and limits the performance of manycore systems. This paper proposes to reclaim dark silicon through a thermally-aware chiplet organization technique in 2.5D manycore systems. The proposed technique adjusts the interposer size and the spacing between adjacent chiplets to reduce the peak temperature of the overall system. In this way, a system can operate with a larger number of active cores at a higher frequency without violating thermal constraints, thereby achieving higher performance. To determine the chiplet organization that jointly maximizes performance and minimizes manufacturing cost, we formulate and solve an optimization problem that considers temperature and interposer size constraints of 2.5D systems. We design a multi-start greedy approach to find (near-)optimal solutions efficiently. Our analysis demonstrates that by using our proposed technique, an optimized 2.5D manycore system improves performance by 41% and 16% on average and by up to 87% and 39% for temperature thresholds of 85oC and 105oC, respectively, compared to a traditional single-chip system at the same manufacturing cost. When maintaining the same performance as an equivalent single-chip system, our approach is able to reduce the system manufacturing cost by 36%.

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14:3011.7.2ISING-PUF: A MACHINE LEARNING ATTACK RESISTANT PUF FEATURING LATTICE LIKE ARRANGEMENT OF ARBITER-PUFS
Speaker:
Hiromitsu Awano, The University of Tokyo, JP
Authors:
Hiromitsu Awano1 and Takashi Sato2
1The University of Tokyo, JP; 2Kyoto University, JP
Abstract
A concept of Ising-PUF, a novel PUF structure that utilizes chaotic behavior of mutually interacting small PUFs, is proposed. Ising-PUF consists of a lattice like arrangement of small PUFs, each of which contains a spin register that stores the response of the small PUF, which also serves as a challenge of its neighbors. The spin patterns that develop along time determine the 1-bit response of the Ising-PUF. Utilizing state-memorizing nature of the spin registers, Ising-PUF attains a challenge hysteresis, i.e., allowing sequence of challenge inputs that continuously stimulate its chaotic behavior, which provides the drastically large challenge-to-response space. Experimental results demonstrate nearly ideal metrics; inter-chip Hamming distance (HD) of 50.1% and inter-environment HD of 2.26%. Further, Ising-PUF is remarkably tolerant to machine learning attacks, demonstrating that, even with a deep neural network using a 50k training CRPs, the prediction accuracy remains 50%, which is comparable to a random guess.

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15:0011.7.3EFFICIENT HELPER DATA REDUCTION IN SRAM PUFS VIA LOSSY COMPRESSION
Speaker:
Ye Wang, University of Texas at Austin, US
Authors:
Ye Wang and Michael Orshansky, University of Texas at Austin, US
Abstract
Fuzzy extractors used in PUF-based key generation require storage of helper data in non-volatile memory (NVM). The challenge of using SRAM PUF-based key generation on FPGAs is that high-capacity NVM, such as Flash, is not available on chip. Only expensive one-time-programmable (OTP) memory with limited capacity, such as e-fuses, can be utilized to store helper data. Our work allows a significant reduction of helper data size (HDS) through two innovative techniques. The first uses bit-error-rate (BER)-aware lossy compression: by treating a fraction of reliable bits as unreliable, it effectively reduces the size of the reliability mask. Considering practical costs of error characterization, the second technique permits across-temperature HDS minimization strategies based on bit-selection (with or without subsequent compression) using room-temperature only characterization. The method is based on stochastic concentration theory and allows efficiently forming confidence intervals for true worst-case BER. We use it to enable lossy compression and key reconstruction with success arbitrarily close to certainty. Results show that compared to maskless alternative, the proposed algorithm achieves an up to 4.5X HDS reduction with only 60% raw bits. Compared to lossless compression, we achieve a further 25% total HDS reduction, at the cost of doubling the number of raw PUF bits, for a 128-bit key. When bit-specific across-temperature characterization is not possible, our method achieves a significant 2.4X helper data reduction compared to the maskless alternative for extracting a 128-bit key and a 3X reduction for a 256-bit key.

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15:1511.7.4IMPROVING THE EFFICIENCY OF THERMAL COVERT CHANNELS IN MULTI-/MANY-CORE SYSTEMS
Speaker:
Zijun Long, South China University of Technology, CN
Authors:
Zijun Long1, Xiaohang Wang1, Yingtao Jiang2, Guofeng Cui1, Yiming Zhao1, Li Zhang1 and Terrence Mark3
1South China University of Technology, CN; 2university of nevada, las vegas, USA, US; 3University of Southampton,UK, GB
Abstract
In many-core chips seen in mobile computing, data center, AI, and elsewhere, thermal covert channels could be established to transmit data (e.g., passwords), supposedly to be kept secret and private. Effectiveness of a thermal covert channel, measured by its transmission rate and bit error rate (BER), is so much dependent on the thermal noise/interference imposed on the channel. In this paper, we present a few techniques to improve the capacity of thermal covert channel by overcoming the thermal interference. In particular, data in a thermal covert channel are encoded and represented following a new thermal signaling scheme where logic value, 0 or 1, modules the thermal signal's duty cycle. Next, we show in this study that proper selection of transmission frequency can significantly minimize thermal interference. In addition, we propose a robust end-to-end communication protocol for reliable communications. Our experiments have confirmed that, compared to an existing thermal covert channel attack [1] [2], a thermal covert channel enhanced with all the improvements proposed in this study is seeing significant BER reduction (by as much as 75%), and transmission rate boost (by more than threefold). Building such a strong thermal covert channel is the key step towards developing robust defense and countermeasures against information leaking over thermal covert channel.

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15:30IP5-10, 771ACCURATE PREDICTION OF SMARTPHONES' SKIN TEMPERATURE BY CONSIDERING EXOTHERMIC COMPONENTS
Speaker:
Jihoon Park, Yonsei University, KR
Authors:
Jihoon Park and Hojung Cha, Dept. of Computer Science, Yonsei University, KR
Abstract
Smartphones' surface temperature, also called skin temperature, can rapidly heat up in certain cases, and this causes a variety of safety problems. Therefore, the thermal management of smartphones should consider the skin temperature, and its accurate prediction is important. However, due to the complicated relationship among the many exothermic components in the device, predicting skin temperature is extremely difficult. In this paper, we develop a thermal prediction model that accurately predicts the skin temperature of a mobile device. In an experiment with smartphones, we show that the proposed model achieves an accuracy of 98%, with a ±0.4 °C margin of error. To the best of our knowledge, our work is the first to reveal the complex relationship between the various components inside of a smartphone and its skin temperature.

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15:31IP5-11, 735TRUSTWORTHY PROOFS FOR SENSOR DATA USING FPGA BASED PHYSICALLY UNCLONABLE FUNCTIONS
Speaker:
Urbi Chatterjee, Indian Institute of Technology Kharagpur, IN
Authors:
Urbi Chatterjee1, Durga Prasad Sahoo2, Debdeep Mukhopadhyay3 and Rajat Subhra Chakraborty1
1Indian Institute of Technology Kharagpur, IN; 2Bosch India (RBEI/ETI), IN; 3Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, IN
Abstract
The Internet of Things (IoT) is envisaged to consist of billions of connected devices coupled with sensors which generate huge volumes of data enabling control-and-command in this paradigm. However, integrity of this data is of utmost concern, and is promisingly addressed leveraging the inherent unreliability of Physically Unclonable Functions (PUFs) w.r.t. ambient parameter variations, using the concept of Virtual Proofs (VPs). Advantage of these protocols is that they do not use explicit keys and aim at proving the authenticity of the sensor. Since the existing PUF-based protocols do not use the sensor data as a part of challenge (i.e. input) to PUFs, there is no guarantee of uniqueness of PUF's challenge-response behavior over multiple levels of ambient parameters. Few of these protocols needs to sequential search in the challenge-response database. To alleviate these issues, we develop a new class of authenticated sensing protocols where the sensor data is combined with the external challenge by utilizing the Strict Avalanche Criterion of the PUF. We validate the proposed protocol through actual experiments on FPGA using Double Arbiter PUFs (DAPUFs), which are implemented with superior uniformity, uniqueness, and reliability on Xilinx Artix-7 FPGAs. According to the FPGA- based validation, the proposed protocol with DAPUF can be effectively used to authenticate wide variations of temperature from −20◦C to 80◦C.

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15:32IP5-15, 878TOWARDS INTER-VENDOR COMPATIBILITY OF TRUE RANDOM NUMBER GENERATORS FOR FPGAS
Speaker:
Miloš Grujić, imec-COSIC, KU Leuven, BE
Authors:
Miloš Grujić, Bohan Yang, Vladimir Rozic and Ingrid Verbauwhede, imec-COSIC, KU Leuven, BE
Abstract
True random number generators (TRNGs) are fundamental constituents of secure embedded cryptographic systems. In this paper, we introduce a general methodology for porting TRNG across different FPGA vendor families. In order to demonstrate our methodology, we applied it to the delay-chain based TRNG (DC-TRNG) on Intel Cyclone IV and Cyclone V FPGAs. We examine vendor-agnostic generality of the underlying DC-TRNG principle and propose modifications to address differences in structure of FPGAs. Implementation of the DC-TRNG on Cyclone IV uses 149 LEs (<0.1% of available resources) and has a throughput of 5Mbps, while on Cyclone V it occupies 230 ALMs (<1.5% of resources) with an output rate of 12.5 Mbps. The quality of the random bits produced by the DC-TRNG on Intel Cyclone IV and V is further confirmed by using NIST statistical test suite.

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15:30End of session
Coffee Break in Exhibition Area



Coffee Breaks in the Exhibition Area

On all conference days (Tuesday to Thursday), coffee and tea will be served during the coffee breaks at the below-mentioned times in the exhibition area (Terrace Level of the ICCD).

Lunch Breaks (Großer Saal + Saal 1)

On all conference days (Tuesday to Thursday), a seated lunch (lunch buffet) will be offered in the rooms "Großer Saal" and "Saal 1" (Saal Level of the ICCD) to fully registered conference delegates only. There will be badge control at the entrance to the lunch break area.

Tuesday, March 20, 2018

  • Coffee Break 10:30 - 11:30
  • Lunch Break 13:00 - 14:30
  • Awards Presentation and Keynote Lecture in "Saal 2" 13:50 - 14:20
  • Coffee Break 16:00 - 17:00

Wednesday, March 21, 2018

  • Coffee Break 10:00 - 11:00
  • Lunch Break 12:30 - 14:30
  • Awards Presentation and Keynote Lecture in "Saal 2" 13:30 - 14:20
  • Coffee Break 16:00 - 17:00

Thursday, March 22, 2018

  • Coffee Break 10:00 - 11:00
  • Lunch Break 12:30 - 14:00
  • Keynote Lecture in "Saal 2" 13:20 - 13:50
  • Coffee Break 15:30 - 16:00