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Steganography is the task of concealing a message within a medium such that the presence of the hidden message cannot be detected. Though the prospect of steganography is conceivably interesting in many contexts, and though work has been…

Cryptography and Security · Computer Science 2017-07-04 Aubrey Alston

Underestimating the leakage can compromise secrecy, while overestimating it may lead to inefficient system design. Therefore, a reliable leakage estimator is essential. Neural network-based estimators provide a data-driven way to estimate…

Information Theory · Computer Science 2025-08-08 Darius S. Heerklotz , Ingo Schroeder , Pin-Hsun Lin , Christian Deppe , Eduard A. Jorswieck

In this paper, we investigate function computation problems under different secure conditions over a network with multiple source nodes and a single sink node which desires a function of all source messages without error. A wiretapper has…

Information Theory · Computer Science 2022-06-14 Min Xu , Gennian Ge , Minqian Liu

A new cryptographic approach -- Iterated Random Encryption (IRE) -- is presented here. Although it is very simple, and easy to implement, it provides a very high level of security. According to this approach, a sequence of operations…

Cryptography and Security · Computer Science 2018-10-30 Osvaldo Skliar , Sherry Gapper , Ricardo E. Monge

We consider the problem of reliable communication over non-binary insertion/deletion channels where symbols are randomly deleted from or inserted in the transmitted sequence and all symbols are corrupted by additive white Gaussian noise. To…

Information Theory · Computer Science 2012-04-17 Raman Yazdani , Masoud Ardakani

Discrete structures are currently second-class in differentiable programming. Since functions over discrete structures lack overt derivatives, differentiable programs do not differentiate through them and limit where they can be used. For…

Programming Languages · Computer Science 2025-11-20 Joey Velez-Ginorio , Nada Amin , Konrad Kording , Steve Zdancewic

Embeddings are functions that map raw input data to low-dimensional vector representations, while preserving important semantic information about the inputs. Pre-training embeddings on a large amount of unlabeled data and fine-tuning them…

Machine Learning · Computer Science 2020-08-21 Congzheng Song , Ananth Raghunathan

Submodular functions are discrete functions that model laws of diminishing returns and enjoy numerous algorithmic applications. They have been used in many areas, including combinatorial optimization, machine learning, and economics. In…

Data Structures and Algorithms · Computer Science 2012-08-24 Maria-Florina Balcan , Nicholas J. A. Harvey

We consider lattice coding for the Gaussian wiretap channel, where the challenge is to ensure reliable communication between two authorized parties while preventing an eavesdropper from learning the transmitted messages. Recently, a measure…

Information Theory · Computer Science 2021-11-03 Maiara F. Bollauf , Hsuan-Yin Lin , Øyvind Ytrehus

We introduce a new class of exact Minimum-Bandwidth Regenerating (MBR) codes for distributed storage systems, characterized by a low-complexity uncoded repair process that can tolerate multiple node failures. These codes consist of the…

Information Theory · Computer Science 2010-10-14 Salim El Rouayheb , Kannan Ramchandran

Bilevel optimization refers to scenarios whereby the optimal solution of a lower-level energy function serves as input features to an upper-level objective of interest. These optimal features typically depend on tunable parameters of the…

Machine Learning · Computer Science 2024-03-08 Amber Yijia Zheng , Tong He , Yixuan Qiu , Minjie Wang , David Wipf

This letter explores the positive side of the adversarial attack for the security-aware semantic communication system. Specifically, a pair of matching pluggable modules is installed: one after the semantic transmitter and the other before…

Information Theory · Computer Science 2024-07-03 Boxiang He , Fanggang Wang , Tony Q. S. Quek

In this paper, we present a new semi-decidable procedure to analyze cryptographic protocols for secrecy based on a new class of functions that we call: the Witness-Functions. A Witness-Function is a reliable function that guarantees the…

Cryptography and Security · Computer Science 2015-07-30 Jaouhar Fattahi , Mohamed Mejri , Hanane Houmani

A recent work of Harn and Fuyou presents the first multilevel (disjunctive) threshold secret sharing scheme based on the Chinese Remainder Theorem. In this work, we first show that the proposed method is not secure and also fails to work…

Cryptography and Security · Computer Science 2016-05-26 Oguzhan Ersoy , Kamer Kaya , Kerem Kaskaloglu

In this letter, we provide the construction of repairable fountain codes (RFCs) for distributed storage systems that are information-theoretically secure against an eavesdropper that has access to the data stored in a subset of the storage…

Information Theory · Computer Science 2016-05-27 Siddhartha Kumar , Eirik Rosnes , Alexandre Graell i Amat

We consider the problem of information-theoretic secrecy in identification schemes rather than transmission schemes. In identification, large identities are encoded into small challenges sent with the sole goal of allowing at the receiver…

Information Theory · Computer Science 2023-10-26 Mattia Spandri , Roberto Ferrara , Christian Deppe , Moritz Wiese , Holger Boche

Semantic communication (SemCom) improves transmission efficiency by focusing on task-relevant information. However, transmitting semantic-rich data over insecure channels introduces privacy risks. This paper proposes a novel SemCom…

Cryptography and Security · Computer Science 2025-05-07 Weixuan Chen , Shunpu Tang , Qianqian Yang , Zhiguo Shi , Dusit Niyato

Various notions of non-malleable secret sharing schemes have been considered. In this paper, we review the existing work on non-malleable secret sharing and suggest a novel game-based definition. We provide a new construction of an…

Cryptography and Security · Computer Science 2023-05-17 Shannon Veitch , Douglas R. Stinson

We consider active, semi-supervised learning in an offline transductive setting. We show that a previously proposed error bound for active learning on undirected weighted graphs can be generalized by replacing graph cut with an arbitrary…

Machine Learning · Computer Science 2012-02-20 Andrew Guillory , Jeff A. Bilmes

Binary Code Similarity Detection (BCSD) is not only essential for security tasks such as vulnerability identification but also for code copying detection, yet it remains challenging due to binary stripping and diverse compilation…

Cryptography and Security · Computer Science 2025-04-24 Li Zhou , Marc Dacier , Charalambos Konstantinou