| 1. |
- Bruhner, Carl Magnus, 1988-, et al.
(författare)
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Changing of the Guards: Certificate and Public Key Management on the Internet
- 2022
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Ingår i: Passive and active measurement (PAM 2022). - Cham : Springer International Publishing. - 9783030987855 - 9783030987848 ; , s. 50-80
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Konferensbidrag (refereegranskat)abstract
- Certificates are the foundation of secure communication over the internet. However, not all certificates are created and managed in a consistent manner and the certificate authorities (CAs) issuing certificates achieve different levels of trust. Furthermore, user trust in public keys, certificates, and CAs can quickly change. Combined with the expectation of 24/7 encrypted access to websites, this quickly evolving landscape has made careful certificate management both an important and challenging problem. In this paper, we first present a novel server-side characterization of the certificate replacement (CR) relationships in the wild, including the reuse of public keys. Our data-driven CR analysis captures management biases, highlights a lack of industry standards for replacement policies, and features successful example cases and trends. Based on the characterization results we then propose an efficient solution to an important revocation problem that currently leaves web users vulnerable long after a certificate has been revoked.
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| 2. |
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| 3. |
- Dubrefjord, Dennis, et al.
(författare)
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Security of In-Vehicle Communication Systems
- 2021
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Ingår i: Decision Support Systems and Industrial IoT in Smart Grid, Factories, and Cities. - : IGI Global. ; , s. 162-179
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- The automotive industry has seen remarkable growth in the use of network and communication technology. These technologies can be vulnerable to attacks. Several examples of confirmed attacks have been documented in academic studies, and many vehicular communications systems have been designed without security aspects in mind. Furthermore, all the security implications mentioned here would affect the functionality of decision support systems (DSS) of IoT and vehicular networks. This chapter focuses on in-vehicle security and aims to categorize some attacks in this field according to the exploited vulnerability by showing common patterns. The conclusion suggests that an ethernet-based architecture could be a good architecture for future vehicular systems; it enables them to meet future security needs while still allowing network communication with outside systems.
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| 4. |
- Gerken, Jan, 1991, et al.
(författare)
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Equivariance versus augmentation for spherical images
- 2022
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Ingår i: Proceedings of Machine Learning Resaerch. ; , s. 7404-7421
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Konferensbidrag (refereegranskat)abstract
- We analyze the role of rotational equivariance in convolutional neural networks (CNNs) applied to spherical images. We compare the performance of the group equivariant networks known as S2CNNs and standard non-equivariant CNNs trained with an increasing amount of data augmentation. The chosen architectures can be considered baseline references for the respective design paradigms. Our models are trained and evaluated on single or multiple items from the MNIST- or FashionMNIST dataset projected onto the sphere. For the task of image classification, which is inherently rotationally invariant, we find that by considerably increasing the amount of data augmentation and the size of the networks, it is possible for the standard CNNs to reach at least the same performance as the equivariant network. In contrast, for the inherently equivariant task of semantic segmentation, the non-equivariant networks are consistently outperformed by the equivariant networks with significantly fewer parameters. We also analyze and compare the inference latency and training times of the different networks, enabling detailed tradeoff considerations between equivariant architectures and data augmentation for practical problems.
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| 5. |
- Gerken, Jan, 1991, et al.
(författare)
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Geometric deep learning and equivariant neural networks
- 2023
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Ingår i: Artificial Intelligence Review. - : Springer Nature. - 1573-7462 .- 0269-2821. ; 56:12, s. 14605-14662
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Tidskriftsartikel (refereegranskat)abstract
- We survey the mathematical foundations of geometric deep learning, focusing on group equivariant and gauge equivariant neural networks. We develop gauge equivariant convolutional neural networks on arbitrary manifolds M using principal bundles with structure group K and equivariant maps between sections of associated vector bundles. We also discuss group equivariant neural networks for homogeneous spaces M= G/ K , which are instead equivariant with respect to the global symmetry G on M . Group equivariant layers can be interpreted as intertwiners between induced representations of G, and we show their relation to gauge equivariant convolutional layers. We analyze several applications of this formalism, including semantic segmentation and object detection networks. We also discuss the case of spherical networks in great detail, corresponding to the case M= S2= SO (3) / SO (2) . Here we emphasize the use of Fourier analysis involving Wigner matrices, spherical harmonics and Clebsch–Gordan coefficients for G= SO (3) , illustrating the power of representation theory for deep learning.
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| 6. |
- Jarpehult, Oscar, et al.
(författare)
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A Longitudinal Characterization of the Third-Party Authentication Landscape
- 2022
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Ingår i: <em></em>2022 IFIP Networking Conference (IFIP Networking). - : IEEE. - 9783903176485
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Konferensbidrag (refereegranskat)abstract
- Many websites offer users to authenticate using third-party identity providers (IDPs) such as Facebook or Google. As part of the signup process, these websites often ask the user to give them additional permissions with the IDP (e.g., some data sharing or authorize some actions) that can have significant privacy implications. Motivated by the increased scrutiny of Facebook and other popular IDPs (e.g., due to the 2018 Cambridge Analytica scandal), we present a longitudinal analysis of the IDP usage and permissions changes over the past nine years (2012–2021) as well as a large-scale characterization of the current state. Our longitudinal analysis identifies trends and characterizes changes in both the IDP usage and permission agreements of different subsets of websites. For our large-scale analysis, we develop and share a Selenium-based measurement framework that we use to collect datasets. Using this data, we study the IDP usage across popularity ranges, the permissions used in the wild, and highlight differences between websites using different IDPs and those that do not. Our analysis shows increased IDP usage, especially among the most popular websites, and that the permission requests on average are becoming more modest but also brings forward significant exceptions that may need further scrutiny.
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| 7. |
- Lindblom, Martin, et al.
(författare)
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Third-party Link Shortener Usage on Twitter
- 2021
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Ingår i: Proc. IFIP Network Traffic Measurement and Analysis Conference (TMA) 2021. - 9783903176409
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Konferensbidrag (refereegranskat)abstract
- Twitter has proven a powerful tool to shape peoples’ opinions and thoughts. One efficient way to spread information is with the use of links. In this paper, we characterize the link sharing usage on Twitter, placing particular focus on third-party link shortener services that hide the full URL from the user. First, we present a measurement framework that combines two Twitter APIs and the Bitly API, and allows us to collect detailed statistics about tweets, their posters, their link usage, and the retweets and clicks 24 hours after the original tweet. Second, using two one-week-long datasets, collected one year apart (April 2019 and2020), we then characterize and analyze important difference in link usage among users, the domains that different users and shorteners (re)direct users too, and compare the click rates of such links with the corresponding retweet rates. The analysis provides insights into link sharing biases on Twitter, skews, and behavioral differences in usage, as well as reveal interesting observations capturing differences in how a tweet containing a link may be retweeted versus how the embedded link is clicked. Finally, we use click-based results for covid-19 tweets to discuss the importance of controlling the spread of (mis)information.
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| 8. |
- Samuelsson, Oscar, et al.
(författare)
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Bias detectability during sensor validation with grab samples
- 2022
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Konferensbidrag (refereegranskat)abstract
- High sensor accuracy is reliant on timely calibrations where any drift is corrected for. Common validation practice involves cross-checking the sensor with a grab sample. In this paper we simulated and evaluated the effectiveness of this common approach. The results showed that more than one grab sample was needed to detect a bias of about ten percent. The random uncertainties in the grab sample could be reduced be replicate samples, which thereby improved the bias detection. The findings indicate that careful, at the cost of less frequent validations, is recommended, as compared to the opposite and current practice.
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| 9. |
- Samuelsson, Oscar, et al.
(författare)
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Model-based monitoring of diffuser fouling using standard sensors
- 2021
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Ingår i: WATER RESEARCH X. - : Elsevier. - 2589-9147. ; 13
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Tidskriftsartikel (refereegranskat)abstract
- Fouling of fine-pore diffusers can cause substantial aeration energy wastage. It remains challenging to monitor their condition and decide the optimal time for labour-intensive and costly cleaning actions. In this study, we show that data from standard sensors (airflow rate, dissolved oxygen concentration, pressure and airflow valve position), which are fed to simple models, can track the diffuser's condition. Additionally, the parameter estimation of diffuser dynamic wet pressure, oxygen transfer rate, respiration rate and the joint alpha fouling factor (alpha F) was facilitated by an active fault detection inspired method. The method executes a sequence with piecewise constant valve positions via the control system. As a result, airflow rates in a sequence similar to a staircase are obtained, which simplifies the estimation of dissolved oxygen dynamics and airflow rate dynamics. The proposed method was evaluated on a full scale over 18 months and successfully detected a reduced cleaning in the diffusers and several sensor-related disturbances. Ultimately, the findings motivate further research on how modelling combined with repetitive process disturbances can leverage data-driven insights from standard instrumentation.
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| 10. |
- Samuelsson, Oscar, et al.
(författare)
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Sensor bias impact on efficient aeration control during diurnal load variations
- 2021
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Ingår i: Water Science and Technology. - : IWA Publishing. - 0273-1223 .- 1996-9732. ; 83:6, s. 1335-1346
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Tidskriftsartikel (refereegranskat)abstract
- This study highlights the need to increase our understand of the interplay between sensor drift and the performance of the automatic control system. The impact from biased sensors on the automatic control systems is rarely considered when different control strategies are assessed in water resource recovery facilities. Still, the harsh measurement environment with negative effects on sensor data quality is widely acknowledged. Simulations were used to show how sensor bias in an ammonium cascade feedback controller impact aeration energy efficiency and total nitrogen removal in an activated sludge process. Response surface methodology was used to reduce the required number of simulations, and to consider the combined effect of two simultaneously biased sensors. The effects from flow variations, negatively biased ammonium (-1 mg/L) and suspended solids sensors (-500 mg/L) reduced the nitrification aeration energy efficiency between 7 and 25 percent. Less impact was seen on total nitrogen removal. There were no added non-linear effects from two simultaneously biased sensors, apart from an interaction between a biased ammonium sensor and dissolved oxygen sensor located in the last aerated zone. Negative effects from sensor bias can partly be limited if the expected bias direction is considered when the controller setpoint-limits are defined.
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| 11. |
- Samuelsson, Oscar
(författare)
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Sensor Fault Detection and Process Monitoring in Water Resource Recovery Facilities
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Water resource recovery facilities (WRRFs) operate 24/7 to reduce the environmental impact from wastewater on receiving waters. Inaccurate measurements hinder the improvement of operations, limits the performance of automatic control, and deteriorate data quality for decision support and other purposes. This thesis studied how faults can be detected in sensors and impact the treatment process, including aeration diffusers. Simulation studies as well as three 6-18 months long pilot and full-scale experiments were conducted. Evidence was given for the commonplace problem with biofilm formation, and the consequence of biased measurements in two types of dissolved oxygen (DO) sensors. The condition of the energy critical aeration diffusers was monitored by combining process models and a tailored process disturbance, which subsequently improved the information content in existing measurements. The deliberate disturbance approach was also successful in predicting fouling and other faults in DO sensors, and further enabled separation of sensor faults from process variations. The practicability of several machine learning methods was studied for both sensor and process monitoring applications. Probabilistic one-class classification methods showed promising for automatically tuning the alarm threshold, although simple methods produced similarly good results in many situations. Lack of annotated data limited the applicability of the classification methods. For sensor fault detection, this was mitigated by using data from sensor maintenance routines. The need for overall good data quality to identify deviating measurements was underscored when data reconciliation was applied for process monitoring. Reaching a balance between theoretical and practical limitations was further pinpointed as a success factor for data reconciliation. Many previously unknown disturbances in the sensors and the treatment process were revealed during the experiments and resulted in improvement opportunities. A major negative impact from biased sensor signals on treatment efficiency was quantified and analysed in simulations, where the drift direction appeared to be vital. Knowledge gaps related to current sensor data quality were identified and studies were proposed to mitigate the identified shortcomings. Ultimately, the findings in this thesis underline the significance of analysing data using fault detection methods, which can enable a better overall system understanding and decision support.
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| 12. |
- Samuelsson, Oscar, et al.
(författare)
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To calibrate or not to calibrate, that is the question
- 2023
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Ingår i: Water Research. - : Elsevier. - 0043-1354 .- 1879-2448. ; 229
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Tidskriftsartikel (refereegranskat)abstract
- Sensors used for control have become widespread in water resources recovery facilities during the strive for resource efficient operations. However, their accuracy is reliant on uncertain laboratory measurements, which are used for calibration and, in turn, to correct for sensor drift. At the same time, current sensor calibration practices are lacking clear theoretical understanding of how measurement uncertainties impact the final control action. The effects of a customarily, and ad hoc, applied calibration threshold are unknown, leading to the current situation where many wastewater treatment processes are controlled by measurements with unknown accuracy. To study how sensor accuracy is affected by calibration, including varying calibration thresholds, we developed a simple theoretical model with closed-form expressions based on the variance and bias in sensor and laboratory measurements. The model was then simulated to yield the results, which showed no practical gain of using a calibration threshold, apart from the situation when calibration is more time-consuming than validation. By contrast, the best accuracy was obtained when consistently executing calibration, which opposes common practice. Further, the sensor calibration error was shown to be transferred to the process, causing a similar deviation from the setpoint when the same sensor was used for control. This emphasizes the importance of minimizing laboratory measurement uncertainties during calibration, which otherwise directly impact operations. Due to these findings we strongly advice shifting mindset from considering calibration as a sequential detection and correction approach, towards an estimation approach, aiming to estimate bias magnitude and drift speed.
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