The Experts below are selected from a list of 315 Experts worldwide ranked by ideXlab platform

Stefano Di Carlo - One of the best experts on this subject based on the ideXlab platform.

  • Performance Monitor Counters: Interplay Between Safety and Security in Complex Cyber-Physical Systems
    IEEE Transactions on Device and Materials Reliability, 2019
    Co-Authors: Alberto Carelli, Alessandro Vallero, Stefano Di Carlo
    Abstract:

    Recent years have witnessed the growth of the adoption of cyber-physical systems (CPSs) in many sectors, such as automotive, aerospace, civil infrastructures, and healthcare. Several CPS applications include critical scenarios, where a failure of the system can lead to catastrophic consequences. Therefore, anomalies due to failures or malicious attacks must be detected timely. This paper focuses on two relevant aspects of the design of a CPS: 1) safety and 2) security. It analyzes in a specific scenario how the Performance Monitor counters (PMCs) available in several commercial microprocessors can be from the one hand a valuable tool to enhance the safety of a system and, on the other hand, a security backdoor. Starting from the example of a PMC-based safety mechanism, this paper shows the implementation of a possible attack and eventually proposes a strategy to mitigate the effectiveness of the attack while preserving the safety of the system.

  • Shielding Performance Monitor Counters: a double edged weapon for safety and security
    2018 IEEE 24th International Symposium on On-Line Testing And Robust System Design (IOLTS), 2018
    Co-Authors: Alberto Carelli, Alessandro Vallero, Stefano Di Carlo
    Abstract:

    Recent years have witnessed the growth of the adoption of Cyber-Physical Systems (CPSs) in many sectors such as automotive, aerospace, civil infrastructures and healthcare. Several CPS applications include critical scenarios, where a failure of the system can lead to catastrophic consequences. Therefore, anomalies due to failure or malicious attacks must be timely detected. This paper focuses on two relevant aspects of the design of a CPS: safety and security. In particular, it studies how Performance Monitor counters (PMCs) available in modern microprocessors can be from the one hand a valuable tool to enhance the safety of a system and, on the other hand, a security backdoor. Starting from the example of a PMC based safety mechanism, the paper shows the implementation of a possible attack and eventually proposes a strategy to mitigate the effectiveness of the attack while preserving the safeness of the system.

Armand Castillejo - One of the best experts on this subject based on the ideXlab platform.

  • An industrial case study of low cost adaptive voltage scaling using delay test patterns
    2018 Design Automation & Test in Europe Conference & Exhibition (DATE), 2018
    Co-Authors: Mahroo Zandrahimi, Philippe Debaud, Armand Castillejo
    Abstract:

    In deep sub-micron technologies, the increasing effect of process and environmental variations has lead chip manufacturers to use adaptive voltage scaling techniques in order to adapt operation parameters exclusively to each chip. The increasing effect of process variation is limiting the effectiveness of current chip Monitoring approaches, such as on-chip Performance Monitor boxes (PMBs), which results in yield loss and high design margins, thus high power consumption. This paper proposes an alternative solution for adaptive voltage scaling using delay test patterns, which is able to eliminate the need for PMBs, and thus the long expensive characterization phase of tuning PMBs to each design, while improving the yield as well as power optimization. Results show, using an industrial grade 28nm FD-SOI library developed for low power devices, that delay testing for Performance prediction reduces the inaccuracy down to 1.85%.

Jianping Wang - One of the best experts on this subject based on the ideXlab platform.

  • Enhancing the Credibility of the Optical Performance Monitor With Adversarial Training
    IEEE Access, 2020
    Co-Authors: Yuwei Su, Jingyu Zhang, Yiying Zhang, Tao Dong, Jianping Wang
    Abstract:

    The existing optical Performance Monitoring (OPM) scheme based on deep neural network has no selection capability of the input data. They always accept and process all, which may result in serious Monitoring errors and reduce the credibility of the Monitoring system. Because the transmitted data in the future heterogeneous fiber-optic networks are diverse, and it's likely to exceed the scope of the Monitoring system. We propose an unsupervised generative adversarial network (GAN) as the judgement module in the new OPM framework to select the legal data within the scope of the Monitoring system. The generator consists of encoder-decoder-encoder (EDE) sub-network, jointly learns the image and latent feature distribution of the legal data. And the training data for the network in the new added judgement module is the same as the OPM analyzer network's, therefore, no extra data are collected, which is low-cost. In the simulation, four modulation formats under two bit-rates are taken into account to verify the model Performance in the judgement module. When 60 Gbps 64QAM signal is selected as illegal data, the max value of the area under the curve (AUC) is 0.942. The judgement time for single image is about 12 ms. Moreover, the influence of the task weights and the latent feature shape on the judgement Performance are investigated. The new added judgement module largely increases the credibility and safety of the existing OPM scheme.

  • Reliable Optical Performance Monitor: The combination of parallel framework and skip connected generative adversarial network
    IEEE Access, 1
    Co-Authors: Jingyu Zhang, Yiying Zhang, Jianping Wang
    Abstract:

    Future optical network is developing towards highly heterogeneity and flexibility, which means that the various signals will be transmitted in the network and the optical Performance Monitor is more likely to encounter the signal beyond its Monitoring range. When the signal beyond Monitoring range (abnormal data) is input, the conventional optical Performance Monitoring (OPM) framework without the ability of data filtering will produce completely wrong results. Although the serial OPM framework has the ability of data filtering, it increases the processing time cost. We propose a novel parallel OPM framework, in which the judgement and analysis modules process the input data simultaneously to reduce the time cost. Moreover, the light-weight and high-Performance skip connected generative adversarial network (GAN) trained only on the normal data (within the Monitoring range) is proposed in the judgement module to filter the abnormal data in a fast-speed way (~9 ms). In the simulation, eight common signals are used to test the Performance of the skip connected GAN in the judgement module. The optimal area under the curve (AUC) value of 0.952 is obtained when the abnormal data is defined as 60 Gbps 64QAM signal. Besides, the impact of the latent vector length, the task weights, the weight of abnormal score, shifted K values and training data size on the model Performance are studied.

Yongmin Kim - One of the best experts on this subject based on the ideXlab platform.

  • Performance analysis and tuning for a single-chip multiprocessor DSP
    IEEE Concurrency, 1997
    Co-Authors: Jihong Kim, Yongmin Kim
    Abstract:

    A new generation of high Performance programmable digital signal processors has a highly integrated parallel architecture, incorporating special purpose hardware features, on-chip memory, and multiple processors into a single chip. Such single chip multiprocessor DSPs, however, require a sophisticated Performance Monitoring tool to achieve maximum Performance. The authors discuss the requirements and functionality of Performance Monitoring tools suitable for single chip multiprocessor DSPs. Specifically, they describe a Performance Monitoring tool that satisfies these requirements and functionality: the MVP Performance Monitor, developed for the Texas Instruments' TMS320C80 Multimedia Video Processor. They present an overview of the MPM and a general Performance tuning approach using the MPM. An 8/spl times/8 block based 2D discrete cosine transform (DCT) implementation demonstrates the MPM's effectiveness. The authors achieved an overall speedup of 4.67 by tuning the Performance based on the Monitoring results from the MPM.

  • Performance Monitoring and tuning for a single-chip multiprocessor digital signal processor
    Proceedings of 1996 IEEE Second International Conference on Algorithms and Architectures for Parallel Processing ICA sup 3 PP '96, 1996
    Co-Authors: Jihong Kim, Yongmin Kim
    Abstract:

    A new generation of high Performance programmable digital signal processors (DSPs) has a highly-integrated parallel architecture, incorporating special-purpose hardware features, on-chip memory and multiple processors into a single chip. For such single-chip multiprocessor DSPs, however, a sophisticated Performance Monitoring tool is essential to achieve the maximum Performance. The authors discuss the requirements and functionality of Performance Monitoring tools suitable for single-chip multiprocessor DSPs. As a specific example, they describe a Performance Monitoring tool developed for Texas Instruments' TMS320C80 (MVP), MVP Performance Monitor (MPM), which satisfies these requirements and functionality. The effectiveness of the MPM is demonstrated using an 8/spl times/8 block-based discrete cosine transform (DCT) implementation. An overall speed-up of 4.67 was achieved by using the MPM.

Weiguo Yang - One of the best experts on this subject based on the ideXlab platform.

  • Sensitivity issues of optical Performance Monitoring
    IEEE Photonics Technology Letters, 2002
    Co-Authors: Weiguo Yang
    Abstract:

    Optical Performance Monitoring is becoming an important network building block as the system becomes increasingly sophisticated and the network span becomes larger and larger. The general requirement for the optical Performance Monitor from the noise perspective is derived from the fundamental considerations of detector noises. Based upon this understanding, the Monitor sensitivity, defined as the minimum input optical power that is required for a specified dynamic range of the signal-to-noise ratio (SNR) Monitoring, for example, 30 dB of detectable SNR range, is shown related to the data rate and the Monitor characteristics. It is also shown that within the optical layer, the bit-error rate as can be measured by a full receiver may not be a good measure for signal quality Monitoring.