Channels with both random errors and burst erasures: Capacities, LDPC code thresholds, and code performances

Li, Kan; Kavcic, A.; Venkataramani, R.; Erden, M.F.

doi:10.1109/isit.2010.5513593

Cited by 3 publications

(6 citation statements)

References 12 publications

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“…For example, when the trojan process is scheduled by the OS, it has no information on whether the spy process is running on another core or not. The temporal inactivity of the spy process leads to the loss of large amount of bits -this is known as burst erasure [34]. In a similar spirit, it is difficult for the spy to distinguish the absence of the signal (when the trojan is switched out) from a sequence of zeroes sent by the trojan.…”

Section: Detecting the Trojan And The Spymentioning

confidence: 99%

“…In a similar spirit, it is difficult for the spy to distinguish the absence of the signal (when the trojan is switched out) from a sequence of zeroes sent by the trojan. While it is possible to adopt error correcting codes [30] that can correct burst erasures [34], this significantly complicates the design and lowers the channel capacity. In any case, the ability to detect the presence of the other party needs to be added to both the trojan and the spy.…”

Section: Detecting the Trojan And The Spymentioning

confidence: 99%

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Covert Channels through Random Number Generator

Evtyushkin

Ponomarev

2016

Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security

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Covert channels present serious security threat because they allow secret communication between two malicious processes even if the system inhibits direct communication. We describe, implement and quantify a new covert channel through shared hardware random number generation (RNG) module that is available on modern processors. We demonstrate that a reliable, high-capacity and low-error covert channel can be created through the RNG module that works across CPU cores and across virtual machines. We quantify the capacity of the RNG channel under different settings and show that transmission rates in the range of 7-200 kbit/s can be achieved depending on a particular system used for transmission, assumptions, and the load level. Finally, we describe challenges in mitigating the RNG channel, and propose several mitigation approaches both in software and hardware. CCS Concepts •Security and privacy → Side-channel analysis and countermeasures; Security in hardware;

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Section: Detecting the Trojan And The Spymentioning

confidence: 99%

Section: Detecting the Trojan And The Spymentioning

confidence: 99%

Covert Channels through Random Number Generator

Evtyushkin

Ponomarev

2016

Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security

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“…In this paper, we focus on a special burst-erasure channel (BuEC) which incorporates both random noise (Gaussian noise) and erasures. Taking the magnetic (or optical) recording system as an example, we can regard its background noise as the white Gaussian noise, and designate the detected thermal asperities (or scratches) at the decoder as erasures [4], [5]. The noise in such channel is the combination of the background Gaussian noise and erasures, this is different from the classic erasure-burst channel (defined in [1]) that only considers erasures.…”

Section: Introductionmentioning

confidence: 99%

“…With respect to such channel model, outputs are randomly erased with a small erasure probability rather than dropped in a bursty fashion. K. Li et al presented a new type of BuECs-G in [5]. They regarded the channel as a concatenation of a memoryless channel (or an indecomposable finite-state channel) and a burst-erasure channel, and derived the non-feedback capacity of this channel.…”

Section: Introductionmentioning

confidence: 99%

“…However, the concatenated structure would increase decoding complexity and delay. The other way focuses on constructing and optimizing the parity-check matrices of LDPC codes with good error-correction capabilities and large maximum resolvable erasure burst length [4], [5], [11], [12], [22]. The algebraic construction is one of the important design methods for combating the burst erasures noise.…”

Section: Introductionmentioning

confidence: 99%

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Protograph-Based Globally-Coupled LDPC Codes Over the Gaussian Channel With Burst Erasures

Bai

Zhu

et al. 2019

IEEE Access

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This paper presents two types of protograph-based globally-coupled low-density parity-check (GC-LDPC) codes formed by a new edge spreading operation. This operation is called the global edge spreading. The Gaussian approximation (GA) and the protograph-based extrinsic information transfer (P-EXIT) analysis are then generalized over a special type of burst-erasure channels (BuECs). Such channel incorporates both Gaussian noise and burst erasures, and is denoted by the Gaussian channel with burst erasures (BuEC-G). Furthermore, the stability condition for BuECs-G is proved and an edge spreading optimization method is proposed to design the structured GC-LDPC codes by predicting the iterative decoding thresholds of corresponding protographs. Simulation results show that the optimized GC-LDPC codes can achieve better thresholds and error performances than existing well-designed GC-LDPC codes, and provide near-capacity performances over BuECs-G. INDEX TERMS Globally-coupled low-density parity-check codes, Gaussian approximation, protographbased extrinsic information transfer, burst-erasure, Gilbert-Elliott erasure.

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Capacity of Burst Noise-Erasure Channels With and Without Feedback and Input Cost

Song

Alajaji

Linder

2019

IEEE Trans. Inform. Theory

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A class of burst noise-erasure channels which incorporate both errors and erasures during transmission is studied. The channel, whose output is explicitly expressed in terms of its input and a stationary ergodic noise-erasure process, is shown to have a so-called "quasi-symmetry" property under certain invertibility conditions. As a result, it is proved that a uniformly distributed input process maximizes the channel's block mutual information, resulting in a closed-form formula for its non-feedback capacity in terms of the noise-erasure entropy rate and the entropy rate of an auxiliary erasure process. The feedback channel capacity is also characterized, showing that feedback does not increase capacity and generalizing prior related results. The capacity-cost function of the channel with and without feedback is also investigated. A sequence of finite-letter upper bounds for the capacity-cost function without feedback is derived. Finite-letter lower bonds for the capacity-cost function with feedback are obtained using a specific encoding rule. Based on these bounds, it is demonstrated both numerically and analytically that feedback can increase the capacity-cost function for a class of channels with Markov noise-erasure processes. Index TermsChannels with burst errors and erasures, channels with memory, channel symmetry, non-feedback and feedback capacities, non-feedback and feedback capacity-cost functions, input cost constraints, stationary ergodic and Markov processes.The authors are with the

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Channels with both random errors and burst erasures: Capacities, LDPC code thresholds, and code performances

Cited by 3 publications

References 12 publications

Covert Channels through Random Number Generator

Covert Channels through Random Number Generator

Protograph-Based Globally-Coupled LDPC Codes Over the Gaussian Channel With Burst Erasures

Capacity of Burst Noise-Erasure Channels With and Without Feedback and Input Cost

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