scholarly journals A Survey on Using Kolmogorov Complexity in Cybersecurity

Entropy ◽  
2019 ◽  
Vol 21 (12) ◽  
pp. 1196 ◽  
Author(s):  
João S. Resende ◽  
Rolando Martins ◽  
Luís Antunes
Keyword(s):  
Kolmogorov Complexity ◽  
Security And Privacy ◽  
Algorithmic Information Theory ◽  
Specific Knowledge ◽  
Privacy Concerns ◽  
Web Interfaces ◽  
Algorithmic Information ◽  
Software Implementations ◽  
New Research ◽  
And Control

Security and privacy concerns are challenging the way users interact with devices. The number of devices connected to a home or enterprise network increases every day. Nowadays, the security of information systems is relevant as user information is constantly being shared and moving in the cloud; however, there are still many problems such as, unsecured web interfaces, weak authentication, insecure networks, lack of encryption, among others, that make services insecure. The software implementations that are currently deployed in companies should have updates and control, as cybersecurity threats increasingly appearing over time. There is already some research towards solutions and methods to predict new attacks or classify variants of previous known attacks, such as (algorithmic) information theory. This survey combines all relevant applications of this topic (also known as Kolmogorov Complexity) in the security and privacy domains. The use of Kolmogorov-based approaches is resource-focused without the need for specific knowledge of the topic under analysis. We have defined a taxonomy with already existing work to classify their different application areas and open up new research questions.

SETS OF K-INDEPENDENT STRINGS

2010 ◽  
Vol 21 (03) ◽  
pp. 321-327 ◽  
Author(s):  
YEN-WU TI ◽  
CHING-LUEH CHANG ◽  
YUH-DAUH LYUU ◽  
ALEXANDER SHEN
Keyword(s):  
Information Theory ◽  
Kolmogorov Complexity ◽  
Upper Bounds ◽  
The Other ◽  
Lower And Upper Bounds ◽  
Algorithmic Information Theory ◽  
Algorithmic Information ◽  
Conditional Complexity

A bit string is random (in the sense of algorithmic information theory) if it is incompressible, i.e., its Kolmogorov complexity is close to its length. Two random strings are independent if knowing one of them does not simplify the description of the other, i.e., the conditional complexity of each string (using the other as a condition) is close to its length. We may define independence of a k-tuple of strings in the same way. In this paper we address the following question: what is that maximal cardinality of a set of n-bit strings if any k elements of this set are independent (up to a certain constant)? Lower and upper bounds that match each other (with logarithmic precision) are provided.

scholarly journals Generic algorithms for halting problem and optimal machines revisited

2017 ◽  
Author(s):  
Laurent Bienvenu ◽  
Damien Desfontaines ◽  
Alexander Shen
Keyword(s):  
Kolmogorov Complexity ◽  
Asymptotic Properties ◽  
Probabilistic Algorithms ◽  
Algorithmic Information Theory ◽  
Halting Problem ◽  
Negative Results ◽  
Long Time ◽  
Algorithmic Information ◽  
Random Reals ◽  
Generic Algorithms

The halting problem is undecidable — but can it be solved for “most” inputs? This natural question was considered in a number of papers, in different settings. We revisit their results and show that most of them can be easily proven in a natural framework of optimal machines (considered in algorithmic information theory) using the notion of Kolmogorov complexity. We also consider some related questions about this framework and about asymptotic properties of the halting problem. In particular, we show that the fraction of terminating programs cannot have a limit, and all limit points are Martin-L¨of random reals. We then consider mass problems of finding an approximate solution of halting problem and probabilistic algorithms for them, proving both positive and negative results. We consider the fraction of terminating programs that require a long time for termination, and describe this fraction using the busy beaver function. We also consider approximate versions of separation problems, and revisit Schnorr’s results about optimal numberings showing how they can be generalized.

DESCRIPTIONAL COMPLEXITY IN ENCODED BLUM STATIC COMPLEXITY SPACES

2014 ◽  
Vol 25 (07) ◽  
pp. 917-932
Author(s):  
CEZAR CÂMPEANU
Keyword(s):  
Kolmogorov Complexity ◽  
Regular Language ◽  
Formal Language ◽  
Function Spaces ◽  
Language Theory ◽  
Algorithmic Information Theory ◽  
Descriptional Complexity ◽  
Algorithmic Information ◽  
Minimal Description ◽  
Minimal Description Length

Algorithmic Information Theory is based on the notion of descriptional complexity known as Chaitin-Kolmogorov complexity, defined in the '60s in terms of minimal description length. Blum Static Complexity spaces defined using Blum axioms, and Encoded Function spaces defined using properties of the complexity function, were introduced in 2012 to generalize the concept of descriptional complexity. In formal language theory we also use the concept of descriptional complexity for the number of states, or the number of transitions in a minimal finite automaton accepting a regular language, and apparently, this number has no connection to the general case of descriptional complexity. In this paper we prove that all the definitions of descriptional complexity, including complexity of operations, can be defined within the framework of Encoded Blum Static Complexity spaces, which extend both Blum Static Complexity spaces and Encoded Function spaces.

scholarly journals Computational Creativity and Aesthetics with Algorithmic Information Theory

Entropy ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. 1654
Author(s):  
Tiasa Mondol ◽  
Daniel G. Brown
Keyword(s):  
Information Theory ◽  
Kolmogorov Complexity ◽  
Creative Work ◽  
Computational Creativity ◽  
Algorithmic Information Theory ◽  
Information Theoretic ◽  
Related Research ◽  
Computational Aesthetics ◽  
Algorithmic Information ◽  
Randomness Deficiency

We build an analysis based on the Algorithmic Information Theory of computational creativity and extend it to revisit computational aesthetics, thereby, improving on the existing efforts of its formulation. We discuss Kolmogorov complexity, models and randomness deficiency (which is a measure of how much a model falls short of capturing the regularities in an artifact) and show that the notions of typicality and novelty of a creative artifact follow naturally from such definitions. Other exciting formalizations of aesthetic measures include logical depth and sophistication with which we can define, respectively, the value and creator’s artistry present in a creative work. We then look at some related research that combines information theory and creativity and analyze them with the algorithmic tools that we develop throughout the paper. Finally, we assemble the ideas and their algorithmic counterparts to complete an algorithmic information theoretic recipe for computational creativity and aesthetics.

Assessment and Prediction of Privacy Concerns on Health Apps (Preprint)

2020 ◽  
Author(s):  
Reham AlTamime ◽  
Vincent Marmion ◽  
Wendy Hall
Keyword(s):  
Data Sharing ◽  
Mobile Applications ◽  
Retention Rate ◽  
Mobile Apps ◽  
Third Party ◽  
Privacy Concerns ◽  
Health Apps ◽  
Mobile Health Apps ◽  
Specific Factors ◽  
And Control

BACKGROUND Mobile apps and IoT-enabled smartphones technologies facilitate collecting, sharing, and inferring from a vast amount of data about individuals’ location, health conditions, mobility status, and other factors. The use of such technology highlights the importance of understanding individuals’ privacy concerns to design applications that integrate their privacy expectations and requirements. OBJECTIVE This paper explores, assesses, and predicts individuals’ privacy concerns in relation to collecting and disclosing data on mobile health apps. METHODS We designed a questionnaire to identify participants’ privacy concerns pertaining to a set of 432 mobile apps’ data collection and sharing scenarios. Participants were presented with 27 scenarios that varied across three categorical factors: (1) type of data collected (e.g. health, demographic, behavioral, and location); (2) data sharing (e.g., whether it is shared, and for what purpose); and, (3) retention rate (e.g., forever, until the purpose is satisfied, unspecified, week, or year). RESULTS Our findings show that type of data, data sharing, and retention rate are all factors that affect individuals’ privacy concerns. However, specific factors such as collecting and disclosing health data to a third-party tracker play a larger role than other factors in triggering privacy concerns. CONCLUSIONS Our findings suggest that it is possible to predict privacy concerns based on these three factors. We propose design approaches that can improve users’ awareness and control of their data on mobile applications

scholarly journals Assessing Users’ Privacy and Security Concerns of Smart Home Technologies

i-com ◽  
2019 ◽  
Vol 18 (3) ◽  
pp. 197-216 ◽  
Author(s):  
Verena Zimmermann ◽  
Paul Gerber ◽  
Karola Marky ◽  
Leon Böck ◽  
Florian Kirchbuchner
Keyword(s):  
Smart Home ◽  
Elderly Care ◽  
Security And Privacy ◽  
Structured Interviews ◽  
Privacy And Security ◽  
Privacy Concerns ◽  
Private Lives ◽  
Societal Level ◽  
Home Users

AbstractSmart Home technologies have the potential to increase the quality of life, home security and facilitate elderly care. Therefore, they require access to a plethora of data about the users’ homes and private lives. Resulting security and privacy concerns form a relevant barrier to adopting this promising technology. Aiming to support end users’ informed decision-making through addressing the concerns we first conducted semi-structured interviews with 42 potential and little-experienced Smart Home users. Their diverse concerns were clustered into four themes that center around attacks on Smart Home data and devices, the perceived loss of control, the trade-off between functionality and security, and user-centric concerns as compared to concerns on a societal level. Second, we discuss measures to address the four themes from an interdisciplinary perspective. The paper concludes with recommendations for addressing user concerns and for supporting developers in designing user-centered Smart Home technologies.

scholarly journals Privacy Care

2021 ◽  
Vol 21 (1) ◽  
pp. 1-32
Author(s):  
Vikram Mehta ◽  
Daniel Gooch ◽  
Arosha Bandara ◽  
Blaine Price ◽  
Bashar Nuseibeh
Keyword(s):  
Ad Hoc ◽  
Physical Space ◽  
User Interaction ◽  
Privacy Management ◽  
Management Tools ◽  
Privacy Concerns ◽  
Tangible Computing ◽  
Need Support ◽  
And Control ◽  
Sample Set

The emergence of ubiquitous computing (UbiComp) environments has increased the risk of undesired access to individuals’ physical space or their information, anytime and anywhere, raising potentially serious privacy concerns. Individuals lack awareness and control of the vulnerabilities in everyday contexts and need support and care in regulating disclosures to their physical and digital selves. Existing GUI-based solutions, however, often feel physically interruptive, socially disruptive, time-consuming and cumbersome. To address such challenges, we investigate the user interaction experience and discuss the need for more tangible and embodied interactions for effective and seamless natural privacy management in everyday UbiComp settings. We propose the Privacy Care interaction framework, which is rooted in the literature of privacy management and tangible computing. Keeping users at the center, Awareness and Control are established as the core parts of our framework. This is supported with three interrelated interaction tenets: Direct, Ready-to-Hand, and Contextual . Direct refers to intuitiveness through metaphor usage. Ready-to-Hand supports granularity, non-intrusiveness, and ad hoc management, through periphery-to-center style attention transitions. Contextual supports customization through modularity and configurability. Together, they aim to provide experience of an embodied privacy care with varied interactions that are calming and yet actively empowering. The framework provides designers of such care with a basis to refer to, to generate effective tangible tools for privacy management in everyday settings. Through five semi-structured focus groups, we explore the privacy challenges faced by a sample set of 15 older adults (aged 60+) across their cyber-physical-social spaces. The results show conformity to our framework, demonstrating the relevance of the facets of the framework to the design of privacy management tools in everyday UbiComp contexts.

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