Swedish Institute of Computer Science Publications Database
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ASArP: Automated Security Assessment & Audit of Remote Platforms using TCG-SCAP synergies
No full textMany enterprise solutions today are built upon complex distributed systems which are accessible to the users globally. Due to this global access, the security of the host platforms becomes critical. The platform administrators use security automation techniques such as those provided by Security Content Automation Protocol (SCAP) standards to protect the systems from the vulnerabilities that are reported daily; furthermore, they are responsible for keeping their systems compliant to the relevant security recommendations (governmental or industrial). Additionally, third party audit and certification processes are used to increase user trust in enterprise solutions. However, traditional audit and certification mechanisms are not continuous , that is, not frequent enough to deal with the daily reported vulnerabilities, and for that matter even auditors expect platform administrators to keep the systems updated. As a result, the end user is also forced to trust the platform administrators about the latest state of the platform. In this paper we develop an automated security audit and certification system (ASArP)(ASArP) which can be used by platform users or by third party auditors. We use security automation techniques for continuous monitoring of the platform security posture and make the results trustworthy by using trusted computing (TCG) techniques. The prototype development of ASArPASArP validates the implementation feasibility; it also provides performance benchmarks which show that the ASArPASArP based audit and certification can be done much more frequently (e.g. daily or weekly). The feasibility of ASArPASArP based continuous audits is significantly better than traditional platform audits which are dependent on the physical presence of the auditors, thus making frequent audits much more expensive and operationally infeasible
Simulative Evaluation of Security Attacks in Networked Critical Infrastructures
No full textICT is becoming a fundamental and pervasive component of critical infrastructures (CIs). Despite the advantages that it brings about, ICT also exposes CIs to a number of security attacks that can severely compromise human safety, service availability and business interests. Although it is vital to ensure an adequate level of security, it is practically infeasible to counteract all possible attacks to the maximum extent. Thus, it is important to understand attacks' impact and rank attacks according to their severity. We propose SEA++, a tool for simulative evaluation of attack impact based on the INET framework and the OMNeT++ platform. Rather than actually executing attacks, SEA++ reproduces their effects and allows to quantitatively evaluate their impact. The user describes attacks through a high-level description language and simulates their effects without any modification to the simulation platform. We show SEA++ capabilities referring to different attacks carried out against a traffic light system
Believing is Seeing: Confirmation Bias Studies in Software Engineering
No full textConfirmation bias is the human tendency to search for, collect, interpret, analyse, or recall information in a way that confirms one’s prior beliefs or preferences. In this paper, we review previous research and demonstrate confirmation bias and its effect in two software engineering contexts. The first study documents that managers bias their interpretation of randomly generated project data towards confirmation of their preferred contract type. The second study reports from an analysis of the results of 35 published comparisons of regression and analogybased cost estimation models. Twenty of these comparisons evaluate the performance of a self-developed analogy-based estimation model relative to a regression-based model and may
be biased towards finding evidence confirming a better accuracy of their own model. A statistical meta-analysis of all 35 comparisons showed that the analogy-based models were more accurate than the regression-based models, whereas removing the 20 comparisons where the researchers evaluated their own models gave the opposite result. Our results support the idea that it is important to consider the presence and degree of confirmation bias when collecting information about topics where there are prior preferences, beliefs, or vested interests to avoid misleading conclusions
Offline Analysis of Independent Guarded Assertions in Automotive Integration Testing
No full textThe size and complexity of software in automotive systems have increased steadily over the last decades. Modern vehicles typically contain numerous electrical control units (ECUs), and more and more features require real-time interaction between several dedicated ECUs (e.g., gearbox, brake and engine control units) in order to perform their tasks. Since system safety and reliability must not be adversely affected by this increase in complexity, proper quality assurance is a must. Such quality assurance is often performed by testing the system in different levels of integration throughout the development process. However, the growth of complexity of the system under test aslo affects the testing, making it laborious, difficult and costly. This paper presents a novel method for efficient offline analysis of traces, which has been especially tailored for integration testing of automotive systems. The method exploits the recently defined concept of independent guarded assertion in order to formally describe the events that are relevant for the analysis as well as the expected behavior in those events. The offline analysis is implemented using a standard commercial model checker and has shown good performance in the conducted experiments
Improved Linear Cryptanalysis of reduced-round SIMON-32 and SIMON-48
No full textIn this paper we analyse two variants of SIMON family of light-weight block ciphers
against linear cryptanalysis and present the best linear cryptanalytic results on these variants of
reduced-round SIMON to date.
We propose a time-memory trade-off method that finds differential/linear trails for any permutation
allowing low Hamming weight differential/linear trails. Our method combines low Hamming
weight trails found by the correlation matrix representing the target permutation with heavy Hamming
weight trails found using a Mixed Integer Programming model representing the target differential/linear
trail. Our method enables us to find a 17-round linear approximation for SIMON-48
which is the best current linear approximation for SIMON-48. Using only the correlation matrix
method, we are able to find a 14-round linear approximation for SIMON-32 which is also the current
best linear approximation for SIMON-32.
The presented linear approximations allow us to mount a 23-round key recovery attack on
SIMON-32 and a 24-round Key recovery attack on SIMON-48/96 which are the current best results
on SIMON-32 and SIMON-48. In addition we have an attack on 24 rounds of SIMON-32 with
marginal complexity
A Multivariate Statistical Framework for the Analysis of Software Effort Phase Distribution
No full textContext
In software project management, the distribution of resources to various project activities is one of the most challenging problems since it affects team productivity, product quality and project constraints related to budget and scheduling.
Objective
The study aims to (a) reveal the high complexity of modelling the effort usage proportion in different phases as well as the divergence from various rules-of-thumb in related literature, and (b) present a systematic data analysis framework, able to offer better interpretations and visualisation of the effort distributed in specific phases.
Method
The basis for the proposed multivariate statistical framework is Compositional Data Analysis, a methodology appropriate for proportions, along with other methods like the deviation from rules-of-thumb, the cluster analysis and the analysis of variance. The effort allocations to phases, as reported in around 1,500 software projects of the ISBSG R11 repository, were transformed to vectors of proportions of the total effort and were analysed with respect to prime project attributes.
Results
The proposed statistical framework was able to detect high dispersion among data, distribution inequality and various interesting correlations and trends, groupings and outliers, especially with respect to other categorical and continuous project attributes. Only a very small number of projects were found close to the rules-of-thumb from the related literature. Significant differences in the proportion of effort spent in different phrases for different types of projects were found.
Conclusion
There is no simple model for the effort allocated to phases of software projects. The data from previous projects can provide valuable information regarding the distribution of the effort for various types of projects, through analysis with multivariate statistical methodologies. The proposed statistical framework is generic and can be easily applied in a similar sense to any dataset containing effort allocation to phases
Current State of the Art in Smart Metering Security
No full textPower supply infrastructures are facing radical changes. The introduction of Information and Communication
Technologies (ICT) into power grids will allow to automatically monitor and control the power
demand and supply. This concept is generally referred to as Smart Grid, and is expected to exponentially
grow during the coming years. However, ICT systems are increasingly subject to security cyber attacks,
which can have a disruptive impact on the whole power grid, and put people’s safety and business interests
at risk. This report covers background information on the smart grid with focus on smart metering in particular.
Important aspects such as security and life-cycle management are covered. In addition, the typical
smart grid components and communication protocols are surveyed
Decision support for choosing architectural assets in the development of software-intensive systems: The GRADE taxonomy
No full textAutomotive System Testing by Independent Guarded Assertions
No full textTesting is a key activity in industry to verify and validate products before they reach end customers. In hardwarein- the-loop system-level verification of automotive systems, testing is often performed using sequential execution of test scripts, each containing a mix of stimuli and assertions. In this paper, we propose and study an alternative approach for automated system-level testing automotive systems. In our approach, assertion-only test scripts and one (or several) stimulionly script(s), execute concurrently on the test driver. By separating the stimuli from the assertions, with each assertion independently determining when the system under test shall be verified, we seek to achieve three things: 1) tests that better represent real-world handling of the product, 2) reduced test execution time, and 3) increased defect detection. In addition to describing our proposed approach in detail, we provide experimental results from an industrial case study evaluating the approach in an automotive system test environment
Orchestra: Robust Mesh Networks Through Autonomously Scheduled TSCH
No full textTime slotted operation is a well-proven approach to achieve highly reliable low-power networking through scheduling and channel hopping. It is, however, difficult to apply time slotting to dynamic networks as envisioned in the Internet of Things. Commonly, these applications do not have pre-defined periodic traffic patterns and nodes can be added or removed dynamically.
This paper addresses the challenge of bringing TSCH (Time Slotted Channel Hopping MAC) to such dynamic networks. We focus on low-power IPv6 and RPL networks, and introduce Orchestra. In Orchestra, nodes autonomously compute their own, local schedules. They maintain multiple schedules, each allocated to a particular traffic plane (application, routing, MAC), and updated automatically as the topology evolves. Orchestra (re)computes local schedules without signaling overhead, and does not require any central or distributed scheduler. Instead, it relies on the existing network stack information to maintain the schedules. This scheme allows Orchestra to build non-deterministic networks while exploiting the robustness of TSCH.
We demonstrate the practicality of Orchestra and quantify its benefits through extensive evaluation in two testbeds, on two hardware platforms. Orchestra reduces, or even eliminates, network contention. In long running experiments of up to 72~h we show that Orchestra achieves end-to-end delivery ratios of over 99.99%. Compared to RPL in asynchronous low-power listening networks, Orchestra improves reliability by two orders of magnitude, while achieving a similar latency-energy balance