Filters: Keyword is accountability  [Clear All Filters]
Severin Kacianka, Alexander Pretschner.  2021.  Designing Accountable Systems. Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. :424–437.
Accountability is an often called for property of technical systems. It is a requirement for algorithmic decision systems, autonomous cyber-physical systems, and for software systems in general. As a concept, accountability goes back to the early history of Liberalism and is suggested as a tool to limit the use of power. This long history has also given us many, often slightly differing, definitions of accountability. The problem that software developers now face is to understand what accountability means for their systems and how to reflect it in a system's design. To enable the rigorous study of accountability in a system, we need models that are suitable for capturing such a varied concept. In this paper, we present a method to express and compare different definitions of accountability using Structural Causal Models. We show how these models can be used to evaluate a system's design and present a small use case based on an autonomous car.
Severin Kacianka, Alexander Pretschner.  2021.  Designing Accountable Systems. Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. :424–437.
Accountability is an often called for property of technical systems. It is a requirement for algorithmic decision systems, autonomous cyber-physical systems, and for software systems in general. As a concept, accountability goes back to the early history of Liberalism and is suggested as a tool to limit the use of power. This long history has also given us many, often slightly differing, definitions of accountability. The problem that software developers now face is to understand what accountability means for their systems and how to reflect it in a system's design. To enable the rigorous study of accountability in a system, we need models that are suitable for capturing such a varied concept. In this paper, we present a method to express and compare different definitions of accountability using Structural Causal Models. We show how these models can be used to evaluate a system's design and present a small use case based on an autonomous car.
Ahmed, Farooq, Li, Xudong, Niu, Yukun, Zhang, Chi, Wei, Lingbo, Gu, Chengjie.  2020.  UniRoam: An Anonymous and Accountable Authentication Scheme for Cross-Domain Access. 2020 International Conference on Networking and Network Applications (NaNA). :198—205.
In recent years, cross-domain roaming through Wi-Fi is ubiquitous, and the number of roaming users has increased dramatically. It is essential to authenticate users belonging to different institutes to ensure network privacy and security. Existing systems, such as eduroam, have centralized and hierarchical structure on indorse accounts that create privacy and security issues. We have proposed UniRoam, a blockchain-based cross-domain authentication scheme that provides accountability and anonymity without any trusted authority. Unlike traditional centralized approaches, UniRoam provides access authentication for its servers and users to provide anonymity and accountability without any privacy leakage issues efficiently. By using the sovrin identifier as an anonymous identity, we integrate our system with Hyperledger and Intel SGX to authenticate users that preserves both anonymity and trust when the user connects to the network. Therefore, UniRoam is highly “faulted-tolerant” to deal with different attacks and provides an effective solution that can be deployed easily in different environments.
Künnemann, Robert, Esiyok, Ilkan, Backes, Michael.  2019.  Automated Verification of Accountability in Security Protocols. 2019 IEEE 32nd Computer Security Foundations Symposium (CSF). :397—39716.

Accountability is a recent paradigm in security protocol design which aims to eliminate traditional trust assumptions on parties and hold them accountable for their misbehavior. It is meant to establish trust in the first place and to recognize and react if this trust is violated. In this work, we discuss a protocol-agnostic definition of accountability: a protocol provides accountability (w.r.t. some security property) if it can identify all misbehaving parties, where misbehavior is defined as a deviation from the protocol that causes a security violation. We provide a mechanized method for the verification of accountability and demonstrate its use for verification and attack finding on various examples from the accountability and causality literature, including Certificate Transparency and Krollˆ\textbackslashtextbackslashprimes Accountable Algorithms protocol. We reach a high degree of automation by expressing accountability in terms of a set of trace properties and show their soundness and completeness.

He, Lin, Ren, Gang, Liu, Ying.  2019.  Bootstrapping Accountability and Privacy to IPv6 Internet without Starting from Scratch. IEEE INFOCOM 2019 - IEEE Conference on Computer Communications. :1486–1494.

Accountability and privacy are considered valuable but conflicting properties in the Internet, which at present does not provide native support for either. Past efforts to balance accountability and privacy in the Internet have unsatisfactory deployability due to the introduction of new communication identifiers, and because of large-scale modifications to fully deployed infrastructures and protocols. The IPv6 is being deployed around the world and this trend will accelerate. In this paper, we propose a private and accountable proposal based on IPv6 called PAVI that seeks to bootstrap accountability and privacy to the IPv6 Internet without introducing new communication identifiers and large-scale modifications to the deployed base. A dedicated quantitative analysis shows that the proposed PAVI achieves satisfactory levels of accountability and privacy. The results of evaluation of a PAVI prototype show that it incurs little performance overhead, and is widely deployable.

Jemal, Jay, Kornegay, Kevin T..  2019.  Security Assessment of Blockchains in Heterogenous IoT Networks : Invited Presentation. 2019 53rd Annual Conference on Information Sciences and Systems (CISS). :1—4.

As Blockchain technology become more understood in recent years and its capability to solve enterprise business use cases become evident, technologist have been exploring Blockchain technology to solve use cases that have been daunting industries for years. Unlike existing technologies, one of the key features of blockchain technology is its unparalleled capability to provide, traceability, accountability and immutable records that can be accessed at any point in time. One application area of interest for blockchain is securing heterogenous networks. This paper explores the security challenges in a heterogonous network of IoT devices and whether blockchain can be a viable solution. Using an experimental approach, we explore the possibility of using blockchain technology to secure IoT devices, validate IoT device transactions, and establish a chain of trust to secure an IoT device mesh network, as well as investigate the plausibility of using immutable transactions for forensic analysis.

Takahashi, Daisuke, Xiao, Yang, Li, Tieshan.  2018.  Database Structures for Accountable Flow-Net Logging. 2018 10th International Conference on Communication Software and Networks (ICCSN). :254–258.
Computer and network accountability is to make every action in computers and networks accountable. In order to achieve accountability, we need to answer the following questions: what did it happen? When did it happen? Who did it? In order to achieve accountability, the first step is to record what exactly happened. Therefore, an accountable logging is needed and implemented in computers and networks. Our previous work proposed a novel accountable logging methodology called Flow-Net. However, how to storage the huge amount of Flow-net logs into databases is not clear. In this paper, we try to answer this question.
Cui, Zhicheng, Zhang, Muhan, Chen, Yixin.  2018.  Deep Embedding Logistic Regression. 2018 IEEE International Conference on Big Knowledge (ICBK). :176–183.
Logistic regression (LR) is used in many areas due to its simplicity and interpretability. While at the same time, those two properties limit its classification accuracy. Deep neural networks (DNNs), instead, achieve state-of-the-art performance in many domains. However, the nonlinearity and complexity of DNNs make it less interpretable. To balance interpretability and classification performance, we propose a novel nonlinear model, Deep Embedding Logistic Regression (DELR), which augments LR with a nonlinear dimension-wise feature embedding. In DELR, each feature embedding is learned through a deep and narrow neural network and LR is attached to decide feature importance. A compact and yet powerful model, DELR offers great interpretability: it can tell the importance of each input feature, yield meaningful embedding of categorical features, and extract actionable changes, making it attractive for tasks such as market analysis and clinical prediction.
Ma, Yuxiang, Wu, Yulei, Ge, Jingguo, Li, Jun.  2018.  A Flow-Level Architecture for Balancing Accountability and Privacy. 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). :984–989.
With the rapid development of the Internet, flow-based approach has attracted more and more attention. To this end, this paper presents a new and efficient architecture to balance accountability and privacy based on network flows. A self-certifying identifier is proposed to efficiently identify a flow. In addition, a delegate-registry cooperation scheme and a multi-delegate mechanism are developed to ensure users' privacy. The effectiveness and overhead of the proposed architecture are evaluated by virtue of the real trace collected from an Internet service provider. The experimental results show that our architecture can achieve a better network performance in terms of lower resource consumption, lower response time, and higher stability.
Memon, Raheel Ahmed, Li, Jianping, Ahmed, Junaid, Khan, Asif, Nazir, M. Irshad, Mangrio, M. Ismail.  2018.  Modeling of Blockchain Based Systems Using Queuing Theory Simulation. 2018 15th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP). :107–111.
Blockchain is the one of leading technology of this time; it has started to revolutionize several fields like, finance, business, industry, smart home, healthcare, social networks, Internet and the Internet of Things. It has many benefits like, decentralized network, robustness, availability, stability, anonymity, auditability and accountability. The applications of Blockchain are emerging, and it is found that most of the work is focused on its engineering implementation. While the theoretical part is very less considered and explored. In this paper we implemented the simulation of mining process in Blockchain based systems using queuing theory. We took the parameters of one of the mature Cryptocurrency, Bitcoin's real data and simulated using M/M/n/L queuing system in JSIMgraph. We have achieved realistic results; and expect that it will open up new research direction in theoretical research of Blockchain based systems.
Ioini, N. E., Pahl, C..  2018.  Trustworthy Orchestration of Container Based Edge Computing Using Permissioned Blockchain. 2018 Fifth International Conference on Internet of Things: Systems, Management and Security. :147-154.

The need to process the verity, volume and velocity of data generated by today's Internet of Things (IoT) devices has pushed both academia and the industry to investigate new architectural alternatives to support the new challenges. As a result, Edge Computing (EC) has emerged to address these issues, by placing part of the cloud resources (e.g., computation, storage, logic) closer to the edge of the network, which allows faster and context dependent data analysis and storage. However, as EC infrastructures grow, different providers who do not necessarily trust each other need to collaborate in order serve different IoT devices. In this context, EC infrastructures, IoT devices and the data transiting the network all need to be subject to identity and provenance checks, in order to increase trust and accountability. Each device/data in the network needs to be identified and the provenance of its actions needs to be tracked. In this paper, we propose a blockchain container based architecture that implements the W3C-PROV Data Model, to track identities and provenance of all orchestration decisions of a business network. This architecture provides new forms of interaction between the different stakeholders, which supports trustworthy transactions and leads to a new decentralized interaction model for IoT based applications.

Severin Kacianka, Alexander Pretschner.  2018.  Understanding and Formalizing Accountability for Cyber-Physical Systems. IEE International Conference on Systems, Man, and Cybernetics. :3165–3170.

Accountability is the property of a system that enables the uncovering of causes for events and helps understand who or what is responsible for these events. Definitions and interpretations of accountability differ; however, they are typically expressed in natural language that obscures design decisions and the impact on the overall system. This paper presents a formal model to express the accountability properties of cyber-physical systems. To illustrate the usefulness of our approach, we demonstrate how three different interpretations of accountability can be expressed using the proposed model and describe the implementation implications through a case study. This formal model can be used to highlight context specific-elements of accountability mechanisms, define their capabilities, and express different notions of accountability. In addition, it makes design decisions explicit and facilitates discussion, analysis and comparison of different approaches.

Üzüm, İbrahim, Can, Özgü.  2018.  An anomaly detection approach for enterprise file integration. 2018 6th International Symposium on Digital Forensic and Security (ISDFS). :1–4.
An information system based on real-time file integrations has an important role in today's organizations' work process management. By connecting to the network, file flow and integration between corporate systems have gained a great significance. In addition, network and security issues have emerged depending on the file structure and transfer processes. Thus, there has become a need for an effective and self-learning anomaly detection module for file transfer processes in order to provide the persistence of integration channels, accountability of transfer logs and data integrity. This paper proposes a novel anomaly detection approach that focuses on file size and integration duration of file transfers between enterprise systems. For this purpose, size and time anomalies on transferring files will be detected by a machine learning-based structure. Later, an alarm system is going to be developed in order to inform the authenticated individuals about the anomalies.
Crabtree, A., Lodge, T., Colley, J., Greenghalgh, C., Mortier, R..  2017.  Accountable Internet of Things? Outline of the IoT databox model 2017 IEEE 18th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM). :1–6.

This paper outlines the IoT Databox model as a means of making the Internet of Things (IoT) accountable to individuals. Accountability is a key to building consumer trust and mandated in data protection legislation. We briefly outline the `external' data subject accountability requirement specified in actual legislation in Europe and proposed legislation in the US, and how meeting requirement this turns on surfacing the invisible actions and interactions of connected devices and the social arrangements in which they are embedded. The IoT Databox model is proposed as an in principle means of enabling accountability and providing individuals with the mechanisms needed to build trust in the IoT.

van der Heijden, Rens W., Engelmann, Felix, Mödinger, David, Schönig, Franziska, Kargl, Frank.  2017.  Blackchain: Scalability for Resource-Constrained Accountable Vehicle-to-x Communication. Proceedings of the 1st Workshop on Scalable and Resilient Infrastructures for Distributed Ledgers. :4:1–4:5.

In this paper, we propose a new Blockchain-based message and revocation accountability system called Blackchain. Combining a distributed ledger with existing mechanisms for security in V2X communication systems, we design a distributed event data recorder (EDR) that satisfies traditional accountability requirements by providing a compressed global state. Unlike previous approaches, our distributed ledger solution provides an accountable revocation mechanism without requiring trust in a single misbehavior authority, instead allowing a collaborative and transparent decision making process through Blackchain. This makes Blackchain an attractive alternative to existing solutions for revocation in a Security Credential Management System (SCMS), which suffer from the traditional disadvantages of PKIs, notably including centralized trust. Our proposal becomes scalable through the use of hierarchical consensus: individual vehicles dynamically create clusters, which then provide their consensus decisions as input for road-side units (RSUs), which in turn publish their results to misbehavior authorities. This authority, which is traditionally a single entity in the SCMS, responsible for the integrity of the entire V2X network, is now a set of authorities that transparently perform a revocation, whose result is then published in a global Blackchain state. This state can be used to prevent the issuance of certificates to previously malicious users, and also prevents the authority from misbehaving through the transparency implied by a global system state.

Goldwasser, Shafi, Park, Sunoo.  2017.  Public Accountability vs. Secret Laws: Can They Coexist?: A Cryptographic Proposal Proceedings of the 2017 on Workshop on Privacy in the Electronic Society. :99–110.

"Our Laws are not generally known; they are kept secret by the small group of nobles who rule us. We are convinced that these ancient laws are scrupulously administered; nevertheless it is an extremely painful thing to be ruled by laws that one does not know."–Franz Kafka, Parables and Paradoxes. Post 9/11, journalists, scholars and activists have pointed out that it secret laws - a body of law whose details and sometime mere existence is classified as top secret - were on the rise in all three branches of the US government due to growing national security concerns. Amid heated current debates on governmental wishes for exceptional access to encrypted digital data, one of the key issues is: which mechanisms can be put in place to ensure that government agencies follow agreed-upon rules in a manner which does not compromise national security objectives? This promises to be especially challenging when the rules, according to which access to encrypted data is granted, may themselves be secret. In this work we show how the use of cryptographic protocols, and in particular, the idea of zero knowledge proofs can ensure accountability and transperancy of the government in this extraordinary, seemingly deadlocked, setting. We propose an efficient record-keeping infrastructure with versatile publicly verifiable audits that preserve (information-theoretic) privacy of record contents as well as of the rules by which the records are attested to abide. Our protocol is based on existing blockchain and cryptographic tools including commitments and zero-knowledge SNARKs, and satisfies the properties of indelibility (i.e., no back-dating), perfect data privacy, public auditability of secret data with secret laws, accountable deletion, and succinctness. We also propose a variant scheme where entities can be required to pay fees based on record contents (e.g., for violating regulations) while still preserving privacy. Our scheme can be directly instantiated on the Ethereum blockchain (and a simplified version with weaker guarantees can be instantiated with Bitcoin).

Antignac, Thibaud, Mukelabai, Mukelabai, Schneider, Gerardo.  2017.  Specification, Design, and Verification of an Accountability-aware Surveillance Protocol. Proceedings of the Symposium on Applied Computing. :1372–1378.

Though controversial, surveillance activities are more and more performed for security reasons. However, such activities are extremely privacy-intrusive. This is seen as a necessary side-effect to ensure the success of such operations. In this paper, we propose an accountability-aware protocol designed for surveillance purposes. It relies on a strong incentive for a surveillance organisation to register its activity to a data protection authority. We first elicit a list of account-ability requirements, we provide an architecture showing the interaction of the different involved parties, and we propose an accountability-aware protocol which is formally specified in the applied pi calculus. We use the ProVerif tool to automatically verify that the protocol respects confidentiality, integrity and authentication properties.

Boudguiga, A., Bouzerna, N., Granboulan, L., Olivereau, A., Quesnel, F., Roger, A., Sirdey, R..  2017.  Towards Better Availability and Accountability for IoT Updates by Means of a Blockchain. 2017 IEEE European Symposium on Security and Privacy Workshops (EuroS PW). :50–58.

Building the Internet of Things requires deploying a huge number of objects with full or limited connectivity to the Internet. Given that these objects are exposed to attackers and generally not secured-by-design, it is essential to be able to update them, to patch their vulnerabilities and to prevent hackers from enrolling them into botnets. Ideally, the update infrastructure should implement the CIA triad properties, i.e., confidentiality, integrity and availability. In this work, we investigate how the use of a blockchain infrastructure can meet these requirements, with a focus on availability. In addition, we propose a peer-to-peer mechanism, to spread updates between objects that have limited access to the Internet. Finally, we give an overview of our ongoing prototype implementation.

King, Jason, Williams, Laurie.  2014.  Log Your CRUD: Design Principles for Software Logging Mechanisms. Proceedings of the 2014 Symposium and Bootcamp on the Science of Security. :5:1–5:10.

According to a 2011 survey in healthcare, the most commonly reported breaches of protected health information involved employees snooping into medical records of friends and relatives. Logging mechanisms can provide a means for forensic analysis of user activity in software systems by proving that a user performed certain actions in the system. However, logging mechanisms often inconsistently capture user interactions with sensitive data, creating gaps in traces of user activity. Explicit design principles and systematic testing of logging mechanisms within the software development lifecycle may help strengthen the overall security of software. The objective of this research is to observe the current state of logging mechanisms by performing an exploratory case study in which we systematically evaluate logging mechanisms by supplementing the expected results of existing functional black-box test cases to include log output. We perform an exploratory case study of four open-source electronic health record (EHR) logging mechanisms: OpenEMR, OSCAR, Tolven eCHR, and WorldVistA. We supplement the expected results of 30 United States government-sanctioned test cases to include log output to track access of sensitive data. We then execute the test cases on each EHR system. Six of the 30 (20%) test cases failed on all four EHR systems because user interactions with sensitive data are not logged. We find that viewing protected data is often not logged by default, allowing unauthorized views of data to go undetected. Based on our results, we propose a set of principles that developers should consider when developing logging mechanisms to ensure the ability to capture adequate traces of user activity.

Feigenbaum, Joan, Jaggard, Aaron D., Wright, Rebecca N..  2014.  Open vs. Closed Systems for Accountability. Proceedings of the 2014 Symposium and Bootcamp on the Science of Security. :4:1–4:11.

The relationship between accountability and identity in online life presents many interesting questions. Here, we first systematically survey the various (directed) relationships among principals, system identities (nyms) used by principals, and actions carried out by principals using those nyms. We also map these relationships to corresponding accountability-related properties from the literature. Because punishment is fundamental to accountability, we then focus on the relationship between punishment and the strength of the connection between principals and nyms. To study this particular relationship, we formulate a utility-theoretic framework that distinguishes between principals and the identities they may use to commit violations. In doing so, we argue that the analogue applicable to our setting of the well known concept of quasilinear utility is insufficiently rich to capture important properties such as reputation. We propose more general utilities with linear transfer that do seem suitable for this model. In our use of this framework, we define notions of "open" and "closed" systems. This distinction captures the degree to which system participants are required to be bound to their system identities as a condition of participating in the system. This allows us to study the relationship between the strength of identity binding and the accountability properties of a system.