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Järpe, E. & Gouchet, Q. (2022). Perspective Chapter: Distinguishing Encrypted from Non-Encrypted Data. In: Srinivasan Ramakrishnan (Ed.), Lightweight Cryptographic Techniques and Cybersecurity Approaches: . Rijeka: InTech
Open this publication in new window or tab >>Perspective Chapter: Distinguishing Encrypted from Non-Encrypted Data
2022 (English)In: Lightweight Cryptographic Techniques and Cybersecurity Approaches / [ed] Srinivasan Ramakrishnan, Rijeka: InTech, 2022Chapter in book (Refereed)
Abstract [en]

Discriminating between encrypted and non-encrypted information is desired for many purposes. Much of the efforts in this direction in the literature is focused on deploying machine learning methods for the discrimination in streamed data which is transmitted in packets in communication networks. Here, however, the focus and the methods are different. The retrieval of data from computer hard drives that have been seized from police busts against suspected criminals is sometimes not straightforward. Typically the incriminating code, which may be important evidence in subsequent trials, is encrypted and quick deleted. The cryptanalysis of what can be recovered from such hard drives is then subject to time-consuming brute forcing and password guessing. To this end methods for accurate classification of what is encrypted code and what is not is of the essence. Here a procedure for discriminating encrypted code from non-encrypted is derived. Two methods to detect where encrypted data is located in a hard disk drive are detailed using passive change-point detection. Measures of performance of such methods are discussed and a new property for evaluation is suggested. The methods are then evaluated and discussed according to the performance measures. 

Place, publisher, year, edition, pages
Rijeka: InTech, 2022
Keywords
likelihood ratio, change-point detection, cryptology, compression, uniform distribution
National Category
Computer Sciences
Identifiers
urn:nbn:se:hh:diva-49909 (URN)10.5772/intechopen.102856 (DOI)978-1-80355-732-8 (ISBN)978-1-80355-734-2 (ISBN)
Available from: 2023-02-03 Created: 2023-02-03 Last updated: 2023-02-03Bibliographically approved
Ortiz-Barrios, M., Järpe, E., García-Constantino, M., Cleland, I., Nugent, C., Arias-Fonseca, S. & Jaramillo-Rueda, N. (2022). Predicting Activity Duration in Smart Sensing Environments Using Synthetic Data and Partial Least Squares Regression: The Case of Dementia Patients. Sensors, 22(14), Article ID 5410.
Open this publication in new window or tab >>Predicting Activity Duration in Smart Sensing Environments Using Synthetic Data and Partial Least Squares Regression: The Case of Dementia Patients
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2022 (English)In: Sensors, E-ISSN 1424-8220, Vol. 22, no 14, article id 5410Article in journal (Refereed) Published
Abstract [en]

The accurate recognition of activities is fundamental for following up on the health progress of people with dementia (PwD), thereby supporting subsequent diagnosis and treatments. When monitoring the activities of daily living (ADLs), it is feasible to detect behaviour patterns, parse out the disease evolution, and consequently provide effective and timely assistance. However, this task is affected by uncertainties derived from the differences in smart home configurations and the way in which each person undertakes the ADLs. One adjacent pathway is to train a supervised classification algorithm using large-sized datasets; nonetheless, obtaining real-world data is costly and characterized by a challenging recruiting research process. The resulting activity data is then small and may not capture each person's intrinsic properties. Simulation approaches have risen as an alternative efficient choice, but synthetic data can be significantly dissimilar compared to real data. Hence, this paper proposes the application of Partial Least Squares Regression (PLSR) to approximate the real activity duration of various ADLs based on synthetic observations. First, the real activity duration of each ADL is initially contrasted with the one derived from an intelligent environment simulator. Following this, different PLSR models were evaluated for estimating real activity duration based on synthetic variables. A case study including eight ADLs was considered to validate the proposed approach. The results revealed that simulated and real observations are significantly different in some ADLs (p-value < 0.05), nevertheless synthetic variables can be further modified to predict the real activity duration with high accuracy (R2(pred)>90%). © 2022 by the authors.

Place, publisher, year, edition, pages
Basel: MDPI, 2022
Keywords
activities of daily living (ADLs), activity duration, activity recognition, artificial intelligence, partial least square regression (PLSR), people with dementia (PwD), sensor systems, simulated data, smart homes
National Category
Computer Sciences
Identifiers
urn:nbn:se:hh:diva-49084 (URN)10.3390/s22145410 (DOI)000834421300001 ()35891090 (PubMedID)2-s2.0-85135137665 (Scopus ID)
Note

Funding text: This research has received funding under the REMIND project Marie Sklodowska-Curie EU Framework for Research and Innovation Horizon 2020, under Grant Agreement No. 734355.

Available from: 2023-01-09 Created: 2023-01-09 Last updated: 2023-01-09Bibliographically approved
Cooney, M., Järpe, E. & Vinel, A. (2022). “Robot Steganography”: Opportunities and Challenges. In: Ana Paula Rocha; Luc Steels; Jaap van den Herik (Ed.), Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART: . Paper presented at ICAART 2022: 14th International Conference on Agents and Artificial Intelligence, Online, Feb. 3-5, 2022 (pp. 200-207). Setúbal: SciTePress
Open this publication in new window or tab >>“Robot Steganography”: Opportunities and Challenges
2022 (English)In: Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART / [ed] Ana Paula Rocha; Luc Steels; Jaap van den Herik, Setúbal: SciTePress, 2022, p. 200-207Conference paper, Published paper (Refereed)
Abstract [en]

Robots are being designed to communicate with people in various public and domestic venues in a perceptive, helpful, and discreet way. Here, we use a speculative prototyping approach to shine light on a new concept of robot steganography (RS): that a robot could seek to help vulnerable populations by discreetly warning of potential threats: We first identify some potentially useful scenarios for RS related to safety and security– concerns that are estimated to cost the world trillions of dollars each year–with a focus on two kinds of robots, a socially assistive robot (SAR) and an autonomous vehicle (AV). Next, we propose that existing, powerful, computer-based steganography (CS) approaches can be adopted with little effort in new contexts (SARs), while also pointing out potential benefits of human-like steganography (HS): Although less efficient and robust than CS, HS represents a currently-unused form of RS that could also be used to avoid requiring a computer to receive messages, detection by more technically advanced adversaries, or a lack of alternative connectivity (e.g., if a wireless channel is being jammed). Some unique challenges of RS are also introduced, that arise from message generation, indirect perception, and effects of perspective. Finally, we confirm the feasibility of the basic concept for RS, that messages can be hidden in a robot’s behaviors, via a simplified, initial user study, also making available some code and a video. The immediate implication is that RS could potentially help to improve people’s lives and mitigate some costly problems, as robots become increasingly prevalent in our society–suggesting the usefulness of further discussion, ideation, and consideration by designers.

Place, publisher, year, edition, pages
Setúbal: SciTePress, 2022
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:hh:diva-46453 (URN)10.5220/0010820300003116 (DOI)000774749000020 ()978-989-758-547-0 (ISBN)
Conference
ICAART 2022: 14th International Conference on Agents and Artificial Intelligence, Online, Feb. 3-5, 2022
Projects
Safety of Connected Intelligent Vehicles in Smart Cities
Funder
Knowledge Foundation
Available from: 2022-03-12 Created: 2022-03-12 Last updated: 2023-10-05Bibliographically approved
Cooney, M., Järpe, E. & Vinel, A. (2021). “Vehicular Steganography”?: Opportunities and Challenges. Paper presented at International Conference on Networked Systems 2021 (NetSys 2021), Lübeck, Germany, September 13-16, 2021. Electronic Communications of the EASST, 80
Open this publication in new window or tab >>“Vehicular Steganography”?: Opportunities and Challenges
2021 (English)In: Electronic Communications of the EASST, E-ISSN 1863-2122, Vol. 80Article in journal (Refereed) Published
Abstract [en]

What if an autonomous vehicle (AV) could secretly warn of potential threats? “Steganography”, the hiding of messages, is a vital way for vulnerable populations to communicate securely and get help. Here, we shine light on the concept of vehicular steganography (VS) using a speculative approach: We identify some key scenarios, highlighting unique challenges that arise from indirect perception, message generation, and effects of perspective-as well as potential carrier signals and message generation considerations. One observation is that, despite challenges to transmission rates and robustness, physical signals such as locomotion or sound could offer a complementary, currently-unused alternative to traditional methods. The immediate implication is that VS could help to mitigate some costly safety problems-suggesting the benefit of further discussion and ideation. © 2021. All Rights Reserved.

Place, publisher, year, edition, pages
Berlin: European Association of Software Science and Technology (E A S S T), 2021
Keywords
autonomous vehicles, steganography
National Category
Computer Sciences
Identifiers
urn:nbn:se:hh:diva-46121 (URN)10.14279/tuj.eceasst.80.1166 (DOI)2-s2.0-85120323523 (Scopus ID)
Conference
International Conference on Networked Systems 2021 (NetSys 2021), Lübeck, Germany, September 13-16, 2021
Projects
Safety of Connected Intelligent Vehicles in Smart Cities
Funder
Knowledge Foundation
Available from: 2021-12-15 Created: 2021-12-15 Last updated: 2023-10-23Bibliographically approved
Järpe, E. & Weckstén, M. (2021). Velody 2–Resilient High-Capacity MIDI Steganography for Organ and Harpsichord Music. Applied Sciences, 11(1)
Open this publication in new window or tab >>Velody 2–Resilient High-Capacity MIDI Steganography for Organ and Harpsichord Music
2021 (English)In: Applied Sciences, E-ISSN 2076-3417, Vol. 11, no 1Article in journal (Refereed) Published
Abstract [en]

A new method for musical steganography for the MIDI format is presented. The MIDI standard is a user-friendly music technology protocol that is frequently deployed by composers of different levels of ambition. There is to the author’s knowledge no fully implemented and rigorously specified, publicly available method for MIDI steganography. The goal of this study, however, is to investigate how a novel MIDI steganography algorithm can be implemented by manipulation of the velocity attribute subject to restrictions of capacity and security. Many of today’s MIDI steganography methods—less rigorously described in the literature—fail to be resilient to steganalysis. Traces (such as artefacts in the MIDI code which would not occur by the mere generation of MIDI music: MIDI file size inflation, radical changes in mean absolute error or peak signal-to-noise ratio of certain kinds of MIDI events or even audible effects in the stego MIDI file) that could catch the eye of a scrutinizing steganalyst are side-effects of many current methods described in the literature. This steganalysis resilience is an imperative property of the steganography method. However, by restricting the carrier MIDI files to classical organ and harpsichord pieces, the problem of velocities following the mood of the music can be avoided. The proposed method, called Velody 2, is found to be on par with or better than the cutting edge alternative methods regarding capacity and inflation while still possessing a better resilience against steganalysis. An audibility test was conducted to check that there are no signs of audible traces in the stego MIDI files. © 2020 by the author. Licensee MDPI, Basel, Switzerland.

Place, publisher, year, edition, pages
MDPI, 2021
Keywords
MIDI, velocity values, carrier file, stego file, capacity, steganalysis resilience, audibility, file-size change-rate, mean absolute error, peak signal-to-noise ratio
National Category
Computer Sciences
Identifiers
urn:nbn:se:hh:diva-44269 (URN)10.3390/app11010039 (DOI)000605894400001 ()2-s2.0-85098619917 (Scopus ID)
Funder
Knowledge Foundation, F2019/151
Available from: 2021-05-10 Created: 2021-05-10 Last updated: 2021-05-11Bibliographically approved
Järpe, E. (2020). An alternative Diffie-Hellman protocol. Cryptography, 4(1), Article ID 5.
Open this publication in new window or tab >>An alternative Diffie-Hellman protocol
2020 (English)In: Cryptography, E-ISSN 2410-387X, Vol. 4, no 1, article id 5Article in journal (Refereed) Published
Abstract [en]

The Diffie–Hellman protocol, ingenious in its simplicity, is still the major solution in protocols for generating a shared secret in cryptography for e-trading and many other applications after an impressive number of decades. However, lately, the threat from a future quantum computer has prompted successors resilient to quantum computer-based attacks. Here, an algorithm similar to Diffie–Hellman is presented. In contrast to the classic Diffie–Hellman, it involves floating point numbers of arbitrary size in the generation of a shared secret. This can, in turn, be used for encrypted communication based on symmetric cyphers. The validity of the algorithm is verified by proving that a vital part of the algorithm satisfies a one-way property. The decimal part is deployed for the one-way function in a way that makes the protocol a post-quantum key generation procedure. This is concluded from the fact that there is, as of yet, no quantum computer algorithm reverse engineering the one-way function. An example illustrating the use of the protocol in combination with XOR encryption is given. © 2020 MDPI (Basel, Switzerland)

Place, publisher, year, edition, pages
Basel: MDPI, 2020
Keywords
encryption key generation protocol, key exchange, shared secret, decimal part, one-way function, real numbers
National Category
Computer Systems
Identifiers
urn:nbn:se:hh:diva-41725 (URN)10.3390/cryptography4010005 (DOI)000561544900004 ()2-s2.0-85101963508 (Scopus ID)
Projects
SmartSafe
Funder
Knowledge Foundation
Note

Other funding: Halmstad University, grant number F2019/151. The APC was funded by Halmstad University.

Available from: 2020-02-28 Created: 2020-02-28 Last updated: 2021-10-20Bibliographically approved
Ortiz-Barrios, M. A., Lundström, J., Synnott, J., Järpe, E. & Pinheiro Sant'Anna, A. (2020). Complementing real datasets with simulated data: a regression-based approach. Multimedia tools and applications (79), 34301-34324
Open this publication in new window or tab >>Complementing real datasets with simulated data: a regression-based approach
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2020 (English)In: Multimedia tools and applications, ISSN 1380-7501, E-ISSN 1573-7721, no 79, p. 34301-34324Article in journal (Refereed) Published
Abstract [en]

Activity recognition in smart environments is essential for ensuring the wellbeing of older residents. By tracking activities of daily living (ADLs), a person’s health status can be monitored over time. Nonetheless, accurate activity classification must overcome the fact that each person performs ADLs in different ways and in homes with different layouts. One possible solution is to obtain large amounts of data to train a supervised classifier. Data collection in real environments, however, is very expensive and cannot contain every possible variation of how different ADLs are performed. A more cost-effective solution is to generate a variety of simulated scenarios and synthesize large amounts of data. Nonetheless, simulated data can be considerably different from real data. Therefore, this paper proposes the use of regression models to better approximate real observations based on simulated data. To achieve this, ADL data from a smart home were first compared with equivalent ADLs performed in a simulator. Such comparison was undertaken considering the number of events per activity, number of events per type of sensor per activity, and activity duration. Then, different regression models were assessed for calculating real data based on simulated data. The results evidenced that simulated data can be transformed with a prediction accuracy of R2 = 97.03%.

© Springer Science+Business Media, LLC, part of Springer Nature 2020

Place, publisher, year, edition, pages
New York, NY: Springer, 2020
Keywords
Activity recognition, Activity duration, Regression analysis, Non-linear models, Determination coefficient, Quantile-quantile plots
National Category
Other Computer and Information Science
Identifiers
urn:nbn:se:hh:diva-41728 (URN)10.1007/s11042-019-08368-5 (DOI)000507701400004 ()2-s2.0-85078616730 (Scopus ID)
Projects
REMIND
Funder
EU, Horizon 2020, 734355
Available from: 2020-02-28 Created: 2020-02-28 Last updated: 2021-11-01Bibliographically approved
Ortíz-Barrios, M. A., Cleland, I., Nugent, C., Pancardo, P., Järpe, E. & Synnott, J. (2020). Simulated Data to Estimate Real Sensor Events—A Poisson-Regression-Based Modelling. Remote Sensing, 12(5), Article ID 771.
Open this publication in new window or tab >>Simulated Data to Estimate Real Sensor Events—A Poisson-Regression-Based Modelling
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2020 (English)In: Remote Sensing, E-ISSN 2072-4292, Vol. 12, no 5, article id 771Article in journal (Refereed) Published
Abstract [en]

Automatic detection and recognition of Activities of Daily Living (ADL) are crucial for providing effective care to frail older adults living alone. A step forward in addressing this challenge is the deployment of smart home sensors capturing the intrinsic nature of ADLs performed by these people. As the real-life scenario is characterized by a comprehensive range of ADLs and smart home layouts, deviations are expected in the number of sensor events per activity (SEPA), a variable often used for training activity recognition models. Such models, however, rely on the availability of suitable and representative data collection and is habitually expensive and resource-intensive. Simulation tools are an alternative for tackling these barriers; nonetheless, an ongoing challenge is their ability to generate synthetic data representing the real SEPA. Hence, this paper proposes the use of Poisson regression modelling for transforming simulated data in a better approximation of real SEPA. First, synthetic and real data were compared to verify the equivalence hypothesis. Then, several Poisson regression models were formulated for estimating real SEPA using simulated data. The outcomes revealed that real SEPA can be better approximated ( R2pred = 92.72 % ) if synthetic data is post-processed through Poisson regression incorporating dummy variables. © 2020 MDPI (Basel, Switzerland)

Place, publisher, year, edition, pages
Basel: MDPI, 2020
Keywords
activity recognition, Activities of Daily Living (ADL), digital simulation, poisson regression, large-scale datasets, sensor systems, smart homes
National Category
Other Computer and Information Science
Identifiers
urn:nbn:se:hh:diva-41726 (URN)10.3390/rs12050771 (DOI)000531559300026 ()2-s2.0-85081935349 (Scopus ID)
Projects
REMIND
Funder
EU, Horizon 2020, 734355
Available from: 2020-02-28 Created: 2020-02-28 Last updated: 2023-08-28Bibliographically approved
Khan, T., Lundgren, L., Järpe, E., Olsson, M. C. & Wiberg, P. (2019). A Novel Method for Classification of Running Fatigue Using Change-Point Segmentation. Sensors, 19(21), Article ID 4729.
Open this publication in new window or tab >>A Novel Method for Classification of Running Fatigue Using Change-Point Segmentation
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2019 (English)In: Sensors, E-ISSN 1424-8220, Vol. 19, no 21, article id 4729Article in journal (Refereed) Published
Abstract [en]

Blood lactate accumulation is a crucial fatigue indicator during sports training. Previous studies have predicted cycling fatigue using surface-electromyography (sEMG) to non-invasively estimate lactate concentration in blood. This study used sEMG to predict muscle fatigue while running and proposes a novel method for the automatic classification of running fatigue based on sEMG. Data were acquired from 12 runners during an incremental treadmill running-test using sEMG sensors placed on the vastus-lateralis, vastus-medialis, biceps-femoris, semitendinosus, and gastrocnemius muscles of the right and left legs. Blood lactate samples of each runner were collected every two minutes during the test. A change-point segmentation algorithm labeled each sample with a class of fatigue level as (1) aerobic, (2) anaerobic, or (3) recovery. Three separate random forest models were trained to classify fatigue using 36 frequency, 51 time-domain, and 36 time-event sEMG features. The models were optimized using a forward sequential feature elimination algorithm. Results showed that the random forest trained using distributive power frequency of the sEMG signal of the vastus-lateralis muscle alone could classify fatigue with high accuracy. Importantly for this feature, group-mean ranks were significantly different (p < 0.01) between fatigue classes. Findings support using this model for monitoring fatigue levels during running. © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Place, publisher, year, edition, pages
Basel: MDPI, 2019
Keywords
surface-electromyography, blood lactate concentration, random forest, running, fatigue
National Category
Sport and Fitness Sciences
Identifiers
urn:nbn:se:hh:diva-40834 (URN)10.3390/s19214729 (DOI)000498834000126 ()2-s2.0-85074441602 (Scopus ID)
Funder
Knowledge Foundation
Note

Other funder: Swedish Adrenaline.

Available from: 2019-11-04 Created: 2019-11-04 Last updated: 2022-02-10Bibliographically approved
Cooney, M., Pashami, S., Järpe, E., Ashfaq, A. & Ong, L. (2019). Avoiding Improper Treatment of Persons with Dementia by Care Robots. In: : . Paper presented at ACM/IEEE International Conference on Human-Robot Interaction (HRI) Workshop on The Dark Side of Human-Robot Interaction: Ethical Considerations and Community Guidelines for the Field of HRI, Daegu, South Korea, March 11, 2019.
Open this publication in new window or tab >>Avoiding Improper Treatment of Persons with Dementia by Care Robots
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2019 (English)Conference paper, Published paper (Refereed)
Abstract [en]

The phrase “most cruel and revolting crimes” has been used to describe some poor historical treatment of vulnerable impaired persons by precisely those who should have had the responsibility of protecting and helping them. We believe we might be poised to see history repeat itself, as increasingly humanlike aware robots become capable of engaging in behavior which we would consider immoral in a human–either unknowingly or deliberately. In the current paper we focus in particular on exploring some potential dangers affecting persons with dementia (PWD), which could arise from insufficient software or external factors, and describe a proposed solution involving rich causal models and accountability measures: Specifically, the Consequences of Needs-driven Dementia-compromised Behaviour model (C-NDB) could be adapted to be used with conversation topic detection, causal networks and multi-criteria decision making, alongside reports, audits, and deterrents. Our aim is that the considerations raised could help inform the design of care robots intended to support well-being in PWD.

Keywords
care robot, therapy robot, dementia, ethics
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:hh:diva-39448 (URN)
Conference
ACM/IEEE International Conference on Human-Robot Interaction (HRI) Workshop on The Dark Side of Human-Robot Interaction: Ethical Considerations and Community Guidelines for the Field of HRI, Daegu, South Korea, March 11, 2019
Funder
Knowledge Foundation, 20140220
Note

Funding: EU REMIND project (H2020-MSCA-RISE No 734355)

Available from: 2019-05-22 Created: 2019-05-22 Last updated: 2021-05-11Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-9307-9421

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