Combating Enhanced Thermal Covert Channel in Multi-/Many-Core Systems With Channel-Aware Jamming

Wang, Jiachen; Wang, Xiaohang; Jiang, Yingtao; Singh, Amit Kumar; Huang, Letian; Yang, Mei

doi:10.1109/tcad.2020.3012642

Cited by 17 publications

(47 citation statements)

References 18 publications

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“…For example, before a user application is loaded into its own SGX enclave, the transmitter codes can be injected into the user application as a Trojan [9], resulting in that the transmitter is able to run in the secure zone and has access to private data. After implanted into the secure zone, a TCC program can leak private data by deliberately manipulating chip temperatures [2], [3], [5], [6]. The thermal signals can be obtained either by directly reading the thermal sensors through MSR (i.e., Model Specific Register) software interface [10] or by reading the temperature files exposed by some commonly installed temperature-monitoring utility tool (e.g., CoreTemp [11] in Linux system).…”

Section: Baseline Thermal Covert Channelsmentioning

confidence: 99%

“…Step 2 -Backpropagation: From the output layer to the first layer, the gradient of the cost function to the parameters of each layer is calculated layer by layer by the chain rule following Eqn. (6) to Eqn. (9),…”

Section: Data Preprocessing and Trainingmentioning

confidence: 99%

“…1(a)) to 0.9t b (the case shown in Fig. 1(b)), the signal amplitude is so low that the threshold-based detection schemes proposed in [5], [6] will fail to detect any TCC, pushing down the detection accuracy to almost 0 as indicated in Fig. 1(c).…”

Section: Introductionmentioning

confidence: 98%

“…To fight against TCC attacks, the dynamic voltage and frequency scaling (DVFS) or noise jamming based countermeasures that are supposedly to block any meaningful thermal signal transmission can be applied [5], [6]. Both countermeasures rely on the threshold-based detection methods to detect the existence of a TCC.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Detection of Thermal Covert Channel Attacks Based on Classification of Components of the Thermal Signal Features

Wang

Huang

Chen

et al. 2023

IEEE Trans. Comput.

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In response to growing security challenges facing many-core systems imposed by thermal covert channel (TCC) attacks, a number of threshold-based detection methods have been proposed. In this paper, we show that these threshold-based detection methods are inadequate to detect TCCs that harness advanced signaling and specific modulation techniques. Since the frequency representation of a TCC signal is found to have multiple side lobes, this important feature shall be explored to enhance the TCC detection capability. To this end, we present a pattern-classification-based TCC detection method using an artificial neural network that is trained with a large volume of spectrum traces of TCC signals. After proper training, this classifier is applied at runtime to infer TCCs, should they exist. The proposed detection method is able to achieve a detection accuracy of 99%, even in the presence of the stealthiest TCCs ever discovered. Because of its low runtime overhead (< 0.187%) and low energy overhead (< 0.072%), this proposed detection method can be indispensable in fighting against TCC attacks in many-core systems. With such a high accuracy in detecting TCCs, powerful countermeasures, like the ones based on dynamic voltage and frequency scaling (DVFS), can be rightfully applied to neutralize any malicious core participating in a TCC attack.

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Section: Baseline Thermal Covert Channelsmentioning

confidence: 99%

Section: Data Preprocessing and Trainingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Detection of Thermal Covert Channel Attacks Based on Classification of Components of the Thermal Signal Features

Wang

Huang

Chen

et al. 2023

IEEE Trans. Comput.

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“…To counter thermal covert channel attacks, recently, a couple of countermeasures [6], [7] have been proposed. In [6], strong noise whose spectrum matches that of the detected thermal covert channel is emitted to jam the data transmission.…”

Section: Introductionmentioning

confidence: 99%

Combating Stealthy Thermal Covert Channel Attack With Its Thermal Signal Transmitted in Direct Sequence Spread Spectrum

Wang

Jiang

et al. 2022

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

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Many-core systems are susceptible to attacks launched by thermal covert channel (TCC) attacks. Detection of TCC attacks often relies on the use of threshold-based approaches or variants, and a countermeasure to thwart the channel can be applied only after an attack is deemed to be present. In this paper, we describe a direct sequence spread spectrum (DSSS) based TCC, where its thermal data are modulated by a pseudorandom bit sequence. Unfortunately, such DSSS-based TCC has an extremely low signal strength that the signal is nearly indistinguishable from the noise and thus cannot be detected by any existing threshold-based detection methods. To combat this stealthy TCC, we propose a novel detection scheme that lets the received signal pass through a differential filter where irrelevant frequency components occupied mainly by the noise gets eliminated and the filtered signal is next compared against a threshold for successful detection. Experimental results show that the DSSS-based TCC can effectively survive detection by the existing detection methods with its BER as low as 4%. In contrast, with the proposed detection and countermeasure applied, the detection accuracy jumps to 89%, and the BER of the DSSS-based TCC soars to 50%, which indicates that the TCC is practically shut down.

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Inaudible sound covert channel with anti-jamming capability: Attacks vs. countermeasure

Wang¹,

Li²,

Jiang³

et al. 2022

Journal of Electronic Science and Technology

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Combating Enhanced Thermal Covert Channel in Multi-/Many-Core Systems With Channel-Aware Jamming

Cited by 17 publications

References 18 publications

Detection of Thermal Covert Channel Attacks Based on Classification of Components of the Thermal Signal Features

Detection of Thermal Covert Channel Attacks Based on Classification of Components of the Thermal Signal Features

Combating Stealthy Thermal Covert Channel Attack With Its Thermal Signal Transmitted in Direct Sequence Spread Spectrum

Inaudible sound covert channel with anti-jamming capability: Attacks vs. countermeasure

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