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We are entering a new era in which software systems are becoming more and more complex and larger. So, the composition of such systems is becoming infeasible by manual means. To address this challenge, self-organising software models…

Formal Languages and Automata Theory · Computer Science 2025-08-27 Damian Arellanes

Higher-order logic programming is an interesting extension of traditional logic programming that allows predicates to appear as arguments and variables to be used where predicates typically occur. Higher-order characteristics are indeed…

Programming Languages · Computer Science 2018-12-04 Antonis Troumpoukis , Angelos Charalambidis

This paper introduces a new framework for data hiding security. Contrary to the existing ones, the approach introduced here is not based on probability theory. In this paper, a scheme is considered as secure if its behavior is proven…

Cryptography and Security · Computer Science 2010-05-06 Jacques M. Bahi , Christophe Guyeux

When implementing secure software, developers must ensure certain requirements, such as the erasure of secret data after its use and execution in real time. Such requirements are not explicitly captured by the C language and could…

Cryptography and Security · Computer Science 2019-07-08 A. P. Shivarpatna Venkatesh , A. Bhat Handadi , M. Mory

We give a principled method for decomposing the predictive uncertainty of a model into aleatoric and epistemic components with explicit semantics relating them to the real-world data distribution. While many works in the literature have…

Machine Learning · Computer Science 2024-12-30 Gustaf Ahdritz , Aravind Gollakota , Parikshit Gopalan , Charlotte Peale , Udi Wieder

In this paper, we study a security problem of protecting secrets in distributed systems. Specifically, we employ discrete-event systems to describe the structure and behaviour of distributed systems, in which global secret information is…

Systems and Control · Electrical Eng. & Systems 2024-02-15 Shoma Matsui , Kai Cai , Karen Rudie

Information-flow security typing statically preserves confidentiality by enforcing noninterference. To address the practical need of selective and flexible declassification of confidential information, several approaches have developed a…

Programming Languages · Computer Science 2019-10-15 Raimil Cruz , Éric Tanter

We consider the problem of computing tight privacy guarantees for the composition of subsampled differentially private mechanisms. Recent algorithms can numerically compute the privacy parameters to arbitrary precision but must be carefully…

Cryptography and Security · Computer Science 2025-04-09 Christian Janos Lebeda , Matthew Regehr , Gautam Kamath , Thomas Steinke

Cloud computing is an evolving paradigm that is frequently changing the way humans share, store, and access their information in digital format. While cloud computing offers tremendous benefits (e.g., efficiency, flexibility, and reduced…

Cryptography and Security · Computer Science 2023-01-20 Tian Wang , Masooda Bashir

Composition is an important feature of a specification language, as it enables the design of a complex system in terms of a product of its parts. Decomposition is equally important in order to reason about structural properties of a system.…

Logic in Computer Science · Computer Science 2022-07-05 Benjamin Lion , Farhad Arbab , Carolyn Talcott

Secure applications implement software protections against side-channel and physical attacks. Such protections are meaningful at machine code or micro-architectural level, but they typically do not carry observable semantics at source…

Cryptography and Security · Computer Science 2021-01-18 Son Tuan Vu , Albert Cohen , Karine Heydemann , Arnaud de Grandmaison , Christophe Guillon

This paper delves into the intricate landscape of privacy notions, specifically honed in on the local setting. Central to our discussion is the juxtaposition of point-wise protection and average-case protection, offering a comparative…

Cryptography and Security · Computer Science 2023-08-29 Nan Wang , Likun Qin , Tianshuo Qiu

When creating public data products out of confidential datasets, inferential/posterior-based privacy definitions, such as Pufferfish, provide compelling privacy semantics for data with correlations. However, such privacy definitions are…

Cryptography and Security · Computer Science 2026-02-04 Jiamu Bai , Guanlin He , Xin Gu , Daniel Kifer , Kiwan Maeng

An `obfuscation' for encrypted computing is quantified exactly here, leading to an argument that security against polynomial-time attacks has been achieved for user data via the deliberately `chaotic' compilation required for security…

Cryptography and Security · Computer Science 2019-04-30 Peter T. Breuer

Privacy has been frequently identified as a main concern for system developers while dealing with/managing personal information. Despite this, most existing work on privacy requirements deals with them as a special case of security…

Software Engineering · Computer Science 2016-12-01 Mohamad Gharib , Paolo Giorgini , John Mylopoulos

Many programming frameworks have been introduced to support the development of differentially private software applications. In this chapter, we survey some of the conceptual ideas underlying these frameworks in a way that we hope will be…

Cryptography and Security · Computer Science 2024-03-19 Marco Gaboardi , Michael Hay , Salil Vadhan

We develop formal privacy mechanisms for releasing statistics from data with many outlying values, such as income data. These mechanisms ensure that a per-record differential privacy guarantee degrades slowly in the protected records'…

Cryptography and Security · Computer Science 2025-05-05 Brian Finley , Anthony M Caruso , Justin C Doty , Ashwin Machanavajjhala , Mikaela R Meyer , David Pujol , William Sexton , Zachary Terner

Developing secure distributed systems is difficult, and even harder when advanced cryptography must be used to achieve security goals. Following prior work, we advocate using secure program partitioning to synthesize cryptographic…

Cryptography and Security · Computer Science 2024-01-10 Coşku Acay , Joshua Gancher , Rolph Recto , Andrew C. Myers

Differential Privacy (DP) provides strong guarantees on the risk of compromising a user's data in statistical learning applications, though these strong protections make learning challenging and may be too stringent for some use cases. To…

Machine Learning · Computer Science 2019-12-10 Hilal Asi , John Duchi , Omid Javidbakht

Non-uniquely decodable codes can be defined as the codes that cannot be uniquely decoded without additional disambiguation information. These are mainly the class of non-prefix-free codes, where a codeword can be a prefix of other(s), and…

Data Structures and Algorithms · Computer Science 2019-11-14 M. Oğuzhan Külekci , Yasin Öztürk , Elif Altunok , Can Altıniğne
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