Secure Source Coding with Side-information at Decoder and Shared Key at Encoder and Decoder

Ghourchian, Hamid; Stavrou, Photios A.; Oechtering, Tobias J.; Skoglund, Mikael

doi:10.1109/itw48936.2021.9611508

Cited by 6 publications

(9 citation statements)

References 22 publications

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“…In ( 2 ) and ( 3 ), we consider conditional mutual information terms to take account of unavoidable secrecy and privacy leakages due to Eve’s side information, i.e.,

and

, respectively; see also [ 21 , 32 ]. Furthermore, we consider conditional mutual information terms rather than corresponding conditional entropy terms, the latter of which is used in [ 6 , 14 , 33 , 34 , 35 ], to characterize the secrecy and privacy leakages simplifies our analysis.…”

Section: System Modelmentioning

confidence: 99%

“…Allowing for the eavesdropper to access only a strict subset of all messages is also a method to enable secure distributed source coding, which was considered in [ 9 , 10 , 11 ]; see also [ 12 ], in which a similar method was applied to enable secure remote source reconstruction. Similarly, a private key that is shared by legitimate terminals and hidden from the eavesdropper can also provide such an advantage, as in [ 13 , 14 ].…”

Section: Introductionmentioning

confidence: 99%

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Private Key and Decoder Side Information for Secure and Private Source Coding

Günlü

Schaefer

Boche

et al. 2022

Entropy

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We extend the problem of secure source coding by considering a remote source whose noisy measurements are correlated random variables used for secure source reconstruction. The main additions to the problem are as follows: (1) all terminals noncausally observe a noisy measurement of the remote source; (2) a private key is available to all legitimate terminals; (3) the public communication link between the encoder and decoder is rate-limited; and (4) the secrecy leakage to the eavesdropper is measured with respect to the encoder input, whereas the privacy leakage is measured with respect to the remote source. Exact rate regions are characterized for a lossy source coding problem with a private key, remote source, and decoder side information under security, privacy, communication, and distortion constraints. By replacing the distortion constraint with a reliability constraint, we obtain the exact rate region for the lossless case as well. Furthermore, the lossy rate region for scalar discrete-time Gaussian sources and measurement channels is established. An achievable lossy rate region that can be numerically computed is also provided for binary-input multiple additive discrete-time Gaussian noise measurement channels.

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“…In ( 2 ) and ( 3 ), we consider conditional mutual information terms to take account of unavoidable secrecy and privacy leakages due to Eve’s side information, i.e.,

and

Section: System Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Private Key and Decoder Side Information for Secure and Private Source Coding

Günlü

Schaefer

Boche

et al. 2022

Entropy

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show abstract

“…♦ Note that in (2) and ( 3) we consider conditional mutual information terms to take account of unavoidable privacy and secrecy leakages due to Eve's side information; see also [21], [31]. Furthermore, considering conditional mutual information terms rather than corresponding conditional entropy terms, the latter of which is used in [6], [14], [32]- [34], to characterize the secrecy and privacy leakages simplifies our analysis.…”

Section: System Modelmentioning

confidence: 99%

“…for some P QV U XXY Z = P Q|V P V |U P U| X P X|X P X P Y Z|X (14) such that E d X, X(U, Y ) ≤ D for some reconstruction function X(U, Y ). The region R D is convexified by using the time-sharing random variable Q, required due to the We remark that ( 12) and (13) show that one can simultaneously achieve strong secrecy and strong privacy, i.e., unnormalized versions of (2) and (3), respectively, by using a large private key K, which is a result missing in some recent works on secure source coding with private key.…”

Section: A Lossy Source Codingmentioning

confidence: 99%

“…Allowing the eavesdropper to access only a strict subset of all messages is also a method to enable secure distributed source coding, considered in [9]- [11]; see also [12] in which a similar method is applied to enable secure remote source reconstruction. Similarly, also a private key that is shared by legitimate terminals and hidden from the eavesdropper can provide such an advantage, as in [13], [14].…”

Section: Introductionmentioning

confidence: 99%

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Secure and Private Source Coding with Private Key and Decoder Side Information

Günlü¹,

Schaefer²,

Boche³

et al. 2022

Preprint

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The problem of secure source coding with multiple terminals is extended by considering a remote source whose noisy measurements are the correlated random variables used for secure source reconstruction. The main additions to the problem include 1) all terminals noncausally observe a noisy measurement of the remote source; 2) a private key is available to all legitimate terminals; 3) the public communication link between the encoder and decoder is rate-limited; 4) the secrecy leakage to the eavesdropper is measured with respect to the encoder input, whereas the privacy leakage is measured with respect to the remote source. Exact rate regions are characterized for a lossy source coding problem with a private key, remote source, and decoder side information under security, privacy, communication, and distortion constraints. By replacing the distortion constraint with a reliability constraint, we obtain the exact rate region also for the lossless case. Furthermore, the lossy rate region for scalar discrete-time Gaussian sources and measurement channels is established.

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