Quantitative theories of information flow give us an approach to relax the absolute confidentiality properties that are difficult to satisfy for many practical programs. The classical information-theoretic approaches for sequential programs, where the program is modeled as a communication channel with only input and output, and the measure of leakage is based on the notions of initial uncertainty and remaining uncertainty after observing the final outcomes, are not suitable to multi-threaded programs. Besides, the information-theoretic approaches have been also shown to conflict with each other when comparing programs. Reasoning about the exposed information flow of multi-threaded programs is more complicated, since the outcomes of such programs depend on the scheduler policy, and the leakages in intermediate states also contribute to the overall leakage of the program.
This paper proposes a novel model of quantitative analysis for multi-threaded programs that also takes into account the effect of observables in intermediate states along the trace. We define a notion of the leakage of a program trace. Given the fact that the execution of a multi-threaded program is typically described by a set of traces, the leakage of a program under a specific scheduler is computed as the expected value of the leakages of all possible traces. Examples are given to compare our approach with the existing approaches.
Enhancing Security Testing Software for Systems that Cannot be Subjected to the Risks of Penetration Testing Through the Incorporation of Multi-threading and and Other Capabilities
We delineate a methodology for the specification and verification of flow security properties expressible in the opacity framework. We propose a logic, OpacTL , for straightforwardly expressing such properties in systems that can be modelled as partially observable labelled transition systems.We develop verification techniques for analysing property opacity with respect to observation notions. Adding a probabilistic operator to the specification language enables quantitative analysis and verification. This analysis is implemented as an extension to the PRISM model checker and illustrated via a…
We analyze the utilization of publish-subscribe protocols in IoT and Fog Computing and challenges around security configuration, performance, and qualitative characteristics. Such problems with security configuration lead to significant disruptions and high operation costs. Yet, These issues can be prevented by selecting the appropriate transmission technology for each configuration, considering the variations in sizing, installation, sensor profile, distribution, security, networking, and locality. This work aims to present a comparative qualitative and quantitative analysis around diverse co…
The Internet of Vehicles (IoV) equips vehicles with connectivity to the Internet and the Internet of Things (IoT) to support modern applications such as autonomous driving. However, the consolidation of complex computing domains of vehicles, the Internet, and the IoT limits the applicability of tailored security solutions. In this paper, we propose a new methodology to quantitatively verify the security of single or system-level assets of the IoV infrastructure. In detail, our methodology decomposes assets of the IoV infrastructure with the help of reference sub-architectures and the 4+1 view …
Domain-specific quantitative modeling and analysis approaches are fundamental in scenarios in which qualitative approaches are inappropriate or unfeasible. In this paper, we present a tool-supported approach to quantitative graph-based security risk modeling and analysis based on attack-defense trees. Our approach is based on QFLan, a successful domain-specific approach to support quantitative modeling and analysis of highly configurable systems, whose domain-specific components have been decoupled to facilitate the instantiation of the QFLan approach in the domain of graph-based security risk…
New York University（纽约大学）；Universität Klagenfurt（克拉根福大学）；Joanneum Research（乔安诺姆研究公司）；Alias Robotics（Alias Robotics公司）
Robotics is becoming more and more ubiquitous, but the pressure to bring systems to market occasionally goes at the cost of neglecting security mechanisms during the development, deployment or while in production. As a result, contemporary robotic systems are vulnerable to diverse attack patterns, and an a posteriori hardening is at least challenging, if not impossible at all. This book aims to stipulate the inclusion of security in robotics from the earliest design phases onward and with a special focus on the cost-benefit tradeoff that can otherwise be an inhibitor for the fast development o…
The SCADA system is the foundation of the large-scale industrial control system. It is widely used in industries of petrochemistry, electric power, pipeline, etc. The natural gas SCADA system is among the critical infrastructure systems that have security issues related to trusted communications in transactions at the control system layer, and lack quantitative risk assessment and mitigation models. However, to guarantee the security of the Oil and Gas Transmission SCADA systems (OGTSS), there should be a holistic security system that considers the nature of these SCADA systems. In this paper,…
Numerous analysis methods for quantitative attack tree analysis have been proposed. These algorithms compute relevant security metrics, i.e. performance indicators that quantify how good the security of a system is, such as the most likely attack, the cheapest, or the most damaging one. This paper classifies attack trees in two dimensions: proper trees vs. directed acyclic graphs (i.e. with shared subtrees); and static vs. dynamic gates. For each class, we propose novel algorithms that work over a generic attribute domain, encompassing a large number of concrete security metrics defined on the…
National University of Singapore（新加坡国立大学）；University of California, Berkeley（加州大学伯克利分校）
Neural networks are increasingly employed in safety-critical domains. This has prompted interest in verifying or certifying logically encoded properties of neural networks. Prior work has largely focused on checking existential properties, wherein the goal is to check whether there exists any input that violates a given property of interest. However, neural network training is a stochastic process, and many questions arising in their analysis require probabilistic and quantitative reasoning, i.e., estimating how many inputs satisfy a given property. To this end, our paper proposes a novel and …
EPFL（洛桑联邦理工学院）；QuantPi（QuantPi公司）；Eindhoven University of Technology（埃因霍温理工大学）；CISPA Helmholtz Center of Information Security（CISPA亥姆霍兹信息安全中心）；University of Cagliari（卡利亚里大学）
Despite the large body of academic work on machine learning security, little is known about the occurrence of attacks on machine learning systems in the wild. In this paper, we report on a quantitative study with 139 industrial practitioners. We analyze attack occurrence and concern and evaluate statistical hypotheses on factors influencing threat perception and exposure. Our results shed light on real-world attacks on deployed machine learning. On the organizational level, while we find no predictors for threat exposure in our sample, the amount of implement defenses depends on exposure to th…
With the developing of the attack and defense technology, the cyber environment has been more and more sophisticated. We failed to give an accurate evaluation of network security situation, as we lack a more accurate quantitative evaluation of attack-defense behaviors. In response to this situation, we proposed an attack-defense stochastic game model (ADSGM), analyzed the different security property of distinct defense mechanism, and put forward a corresponding utility calculation coping with the distinct defense mechanism. Through a case study, we showed the impact of active defense and the r…
Security still remains an afterthought in modern Electronic Design Automation (EDA) tools, which solely focus on enhancing performance and reducing the chip size. Typically, the security analysis is conducted by hand, leading to vulnerabilities in the design remaining unnoticed. Security-aware EDA tools assist the designer in the identification and removal of security threats while keeping performance and area in mind. State-of-the-art approaches utilize information flow analysis to spot unintended information leakages in design structures. However, the classification of such threats is binary…
The enormous amount of code required to design modern hardware implementations often leads to critical vulnerabilities being overlooked. Especially vulnerabilities that compromise the confidentiality of sensitive data, such as cryptographic keys, have a major impact on the trustworthiness of an entire system. Information flow analysis can elaborate whether information from sensitive signals flows towards outputs or untrusted components of the system. But most of these analytical strategies rely on the non-interference property, stating that the untrusted targets must not be influenced by the s…
Numerous analysis methods for quantitative attack tree analysis have been proposed. These algorithms compute relevant security metrics, i.e. performance indicators that quantify how good the security of a system is; typical metrics being the most likely attack, the cheapest, or the most damaging one. However, existing methods are only geared towards specific metrics or do not work on general attack trees. This paper classifies attack trees in two dimensions: proper trees vs. directed acyclic graphs (i.e. with shared subtrees); and static vs. dynamic gates. For three out of these four classes, …
Network traffic generators are invaluable tools that allow for applied experimentation to evaluate the performance of networks, infrastructure, and security controls, by modelling and simulating the communication packets and payloads that would be produced by machines and devices on the network. Specifically for security applications, these tools can be used to consistently simulate malicious activity on the network and test the components designed to detect and mitigate malicious activities, in a highly reliable and customisable way. However, despite the promising features, most of these tool…
Industrial components are of high importance because they control critical infrastructures that form the lifeline of modern societies. However, the rapid evolution of industrial components, together with the new paradigm of Industry 4.0, and the new connectivity features that will be introduced by the 5G technology, all increase the likelihood of security incidents. These incidents are caused by the vulnerabilities present in these devices. In addition, although international standards define tasks to assess vulnerabilities, they do not specify any particular method. Having a secure design is …
Most recent theoretical literature on program obfuscation is based on notions like Virtual Black Box (VBB) obfuscation and indistinguishability Obfuscation (iO). These notions are very strong and are hard to satisfy. Further, they offer far more protection than is typically required in practical applications. On the other hand, the security notions introduced by software security researchers are suitable for practical designs but are not formal or precise enough to enable researchers to provide a quantitative security assurance. Hence, in this paper, we introduce a new formalism for practical …
Many important cryptographic primitives offer probabilistic guarantees of security that can be specified as quantitative hyperproperties; these are specifications that stipulate the existence of a certain number of traces in the system satisfying certain constraints. Verification of such hyperproperties is extremely challenging because they involve simultaneous reasoning about an unbounded number of different traces. In this paper, we introduce a technique for verification of quantitative hyperproperties based on the notion of trace enumeration relations. These relations allow us to reduce the…
Power side-channel attacks, which can deduce secret data via statistical analysis, have become a serious threat. Masking is an effective countermeasure for reducing the statistical dependence between secret data and side-channel information. However, designing masking algorithms is an error-prone process. In this paper, we propose a hybrid approach combing type inference and model-counting to verify masked arithmetic programs against side-channel attacks. The type inference allows an efficient, lightweight procedure to determine most observable variables whereas model-counting accounts for com…
Many software analysis techniques attempt to determine whether bugs are reachable, but for security purpose this is only part of the story as it does not indicate whether the bugs found could be easily triggered by an attacker. The recently introduced notion of robust reachability aims at filling this gap by distinguishing the input controlled by the attacker from those that are not. Yet, this qualitative notion may be too strong in practice, leaving apart bugs which are mostly but not fully replicable. We aim here at proposing a quantitative version of robust reachability, more flexible and s…
Attack-Defence Trees (ADTs) are well-suited to assess possible attacks to systems and the efficiency of counter-measures. In this paper, we first enrich the available constructs with reactive patterns that cover further security scenarios, and equip all constructs with attributes such as time and cost to allow quantitative analyses. Then, ADTs are modelled as (an extension of) Asynchronous Multi-Agents Systems--EAMAS. The ADT-EAMAS transformation is performed in a systematic manner that ensures correctness. The transformation allows us to quantify the impact of different agents configurations …
