Malmö University Publications
Change search
Refine search result
1 - 11 of 11
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1. Al-Dhaqm, Arafat
    et al.
    Abd Razak, Shukor
    Dampier, David A.
    Choo, Kim-Kwang Raymond
    Siddique, Kamran
    Ikuesan, Richard Adeyemi
    d.
    Alqarni, Abdulhadi
    Kebande, Victor R.
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Categorization and Organization of Database Forensic Investigation Processes2020In: IEEE Access, E-ISSN 2169-3536, Vol. 8, p. 112846-112858Article in journal (Refereed)
    Abstract [en]

    Database forensic investigation (DBFI) is an important area of research within digital forensics. It & x2019;s importance is growing as digital data becomes more extensive and commonplace. The challenges associated with DBFI are numerous, and one of the challenges is the lack of a harmonized DBFI process for investigators to follow. In this paper, therefore, we conduct a survey of existing literature with the hope of understanding the body of work already accomplished. Furthermore, we build on the existing literature to present a harmonized DBFI process using design science research methodology. This harmonized DBFI process has been developed based on three key categories (i.e. planning, preparation and pre-response, acquisition and preservation, and analysis and reconstruction). Furthermore, the DBFI has been designed to avoid confusion or ambiguity, as well as providing practitioners with a systematic method of performing DBFI with a higher degree of certainty.

    Download full text (pdf)
    fulltext
  • 2. Al-Dhaqm, Arafat
    et al.
    Razak, Shukor Abd
    Ikuesan, Richard Adeyemi
    Kebande, Victor R.
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Internet of Things and People (IOTAP).
    Siddique, Kamran
    A Review of Mobile Forensic Investigation Process Models2020In: IEEE Access, E-ISSN 2169-3536, Vol. 8, p. 173359-173375Article, review/survey (Refereed)
    Abstract [en]

    Mobile Forensics (MF) field uses prescribed scientific approaches with a focus on recovering Potential Digital Evidence (PDE) from mobile devices leveraging forensic techniques. Consequently, increased proliferation, mobile-based services, and the need for new requirements have led to the development of the MF field, which has in the recent past become an area of importance. In this article, the authors take a step to conduct a review on Mobile Forensics Investigation Process Models (MFIPMs) as a step towards uncovering the MF transitions as well as identifying open and future challenges. Based on the study conducted in this article, a review of the literature revealed that there are a few MFIPMs that are designed for solving certain mobile scenarios, with a variety of concepts, investigation processes, activities, and tasks. A total of 100 MFIPMs were reviewed, to present an inclusive and up-to-date background of MFIPMs. Also, this study proposes a Harmonized Mobile Forensic Investigation Process Model (HMFIPM) for the MF field to unify and structure whole redundant investigation processes of the MF field. The paper also goes the extra mile to discuss the state of the art of mobile forensic tools, open and future challenges from a generic standpoint. The results of this study find direct relevance to forensic practitioners and researchers who could leverage the comprehensiveness of the developed processes for investigation.

    Download full text (pdf)
    fulltext
  • 3. Al-Dhaqm, Arafat
    et al.
    Razak, Shukor Abd
    Siddique, Kamran
    Ikuesan, Richard Adeyemi
    Kebande, Victor R.
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Towards the Development of an Integrated Incident Response Model for Database Forensic Investigation Field2020In: IEEE Access, E-ISSN 2169-3536, Vol. 8, p. 145018-145032Article in journal (Refereed)
    Abstract [en]

    For every contact that is made in a database, a digital trace will potentially be left and most of the database breaches are mostly aimed at defeating the major security goals (Confidentiality, Integrity, and Authenticity) of data that reside in the database. In order to prove/refute a fact during litigation, it is important to identify suitable investigation techniques that can be used to link a potential incident/suspect to the digital crime. As a result, this paper has proposed suitable steps of constructing and Integrated Incident Response Model (IIRM) that can be relied upon in the database forensic investigation field. While developing the IIRM, design science methodology has been adapted and the outcome of this study has shown significant and promising approaches that could be leveraged by digital forensic experts, legal practitioners and law enforcement agencies. This is owing to the fact, that IIRM construction has followed incident investigation principles that are stipulated in ISO guidelines.

    Download full text (pdf)
    fulltext
  • 4.
    Banda, Laurence
    et al.
    Univ Witwatersrand, Wits Business Sch WBS, ZA-2000 Johannesburg, South Africa..
    Mzyece, Mjumo
    Univ Witwatersrand, Wits Business Sch WBS, ZA-2000 Johannesburg, South Africa..
    Mekuria, Fisseha
    Univ Witwatersrand, Wits Business Sch WBS, ZA-2000 Johannesburg, South Africa.;Council Sci & Ind Res CSIR, ZA-0001 Pretoria, South Africa..
    5G Business Models for Mobile Network Operators-A Survey2022In: IEEE Access, E-ISSN 2169-3536, Vol. 10, p. 94851-94886Article in journal (Refereed)
    Abstract [en]

    Emerging Fifth-generation (5G) mobile networks and associated technologies are expected to provide multi-service wireless applications with diverse specifications intended to address not only consumer-based smartphone applications, but also the needs of various vertical industry markets (e.g., healthcare, education, energy, mining, agriculture, manufacturing, and so forth). This paper extends 5G networks' technology orientation towards attaining economic value for all key 5G stakeholders, including customers, mobile network operators (MNOs), equipment vendors, public institutions, private enterprises, digital business start-ups and other third parties. Although several surveys and tutorials have discussed business models in connection with 5G networks, there is no comprehensive study on business models for emerging 5G networks from the MNO's perspective. In this survey article, we present and investigate key advances on business models for 5G networks and 5G MNOs in particular, from industry, use cases and research community perspectives. The paper focuses the theoretical business model concept from both strategic management and technological innovation perspectives. Thereafter, we discuss conventional business models for MNOs before presenting particular disruptive business models which can be considered for rolling out 5G networks with an aim to improve business efficiency. Additionally, the paper explores the emerging network deployment concept of private 5G networks and their related business models. Finally, we present some of the open research challenges and provide possible guidelines for implementing 5G business models based on various countries' socio-economic status and relevant 5G use cases applicable in a specific context of emerging economies.

  • 5. Chang, Jianghao
    et al.
    Yu, Jingcun
    Li, Juanjuan
    Xue, Guoqiang
    Malekian, Reza
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Su, Benyu
    Diffusion Law of Whole-Space Transient Electromagnetic Field Generated by the Underground Magnetic Source and Its Application2019In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 63415-63425Article in journal (Refereed)
    Abstract [en]

    Mine water inrush stays as one of the major disasters in coalmine production and construction. As one of the principal methods for detecting hidden water-rich areas in coal mines, underground transient electromagnetic method (TEM) adopts the small loop of a magnetic source which generates a kind of whole-space transient electromagnetic field. To study the diffusion of whole-space transient electromagnetic field, a 3-D finite-difference time-domain (FDTD) is employed in simulating the diffusion pattern of whole-space transient electromagnetic field created by the magnetic source in any direction and the whole-space transient electromagnetic response of the 3-D low-resistance body. The simulation results indicate that the diffusion of whole-space transient electromagnetic field is different from ground half-space and that it does not conform to the "smoke ring effect'' of half-space transient electromagnetic field, for the radius of the electric field's contour ring in whole space keeps expanding without moving upward or downward. The low-resistance body can significantly affect the diffusion of transient electromagnetic field. When the excitation direction is consistent with the bearing of the low-resistance body, the coupling between the transient electromagnetic field and the low-resistance body is optimal, and the abnormal response is most obvious. The bearing of the low-resistance body can be distinguished by comparing the response information of different excitation directions. Based on the results above, multi-directional sector detection technology is adapted to detect the water-rich areas, which can not only detect the target ahead of the roadway but also distinguish the bearing of the target. Both numerical simulation and practical application in underground indicate that the mining TEM can accurately reflect the location of water-rich areas.

    Download full text (pdf)
    FULLTEXT01
  • 6. Cheng, Kang
    et al.
    Ye, Ning
    Malekian, Reza
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Internet of Things and People (IOTAP).
    Wang, Ruchuan
    In-Air Gesture Interaction: Real Time Hand Posture Recognition Using Passive RFID Tags2019In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 94460-94472Article in journal (Refereed)
    Abstract [en]

    In-air gesture interaction enables a natural communication between a man and a machine with its clear semantics and humane mode of operation. In this paper, we propose a real-time recognition system on multiple gestures in the air. It uses the commodity off-the-shelf (COTS) reader with three antennas to detect the radio frequency (RF) signals of the passive radio frequency identification (RFID) Tags attached to the fingers. The idea derives from the crucial insight that the sequential phase profile of the backscatter RF signals is a reliable and well-regulated indicator insinuating space-time situation of the tagged object, which presents a close interdependency with tag's movements and positions. The KL divergence is utilized to extract the dynamic gesture segment by confirming the endpoints of the data flow. To achieve the template matching and classification, we bring in the dynamic time warping (DTW) and k-nearest neighbors (KNN) for similarity scores calculation and appropriate gesture recognition. The experiment results show that the recognition rates for static and dynamic gestures can reach 85% and 90%, respectively. Moreover, it can maintain satisfying performance under different situations, such as diverse antenna-to-user distances and being hidden from view by nonconducting obstacles.

    Download full text (pdf)
    FULLTEXT01
  • 7.
    Danielsson, Patrik
    et al.
    Mpya Sci & Tech, Gothenburg, Sweden.
    Postema, Tom
    Axis Communications, Lund, Sweden.
    Munir, Hussan
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
    Heroku-Based Innovative Platform for Web-Based Deployment in Product Development at Axis2021In: IEEE Access, E-ISSN 2169-3536, Vol. 9, p. 10805-10819Article in journal (Other academic)
    Abstract [en]

    The introduction of cloud technology has reduced the feedback time in software development for many companies. However, companies require significant resources to run applications in an Infrastructure as a Service. The study aims at developing an innovation platform which enables faster deployment of web-based applications. The innovation platform is an add-on for a cloud service, its purpose is to allow developers to set up and use multiple cameras in a cloud environment. Furthermore, the study investigates the drivers and value created by the platform for Axis. We developed a proof of concept built on the innovation platform, using the design science methodology and evaluated it in a focus group. The prototype was a mock version of a grocery store’s internal website, used to show the potential of the innovation platform. Moreover, we conducted semi-structured interviews to investigate the drivers for implementing the platform and the value it created. Results showed that the implementation of the prototype may make the deployment of web-based applications easier. A majority of the interviewees and the focus group participants agreed that the development of the innovation platform should continue and be tested to adopt the platform as a complement to AWS. However, the degree to which the platform should be open source needs a more clear management strategy. The prototype is seen as an innovation platform which may be used to quickly experiment with new ideas. The key drivers for implementing a prototype entails reduced cost, faster time to market and reduced complexity of web-based deployments.

    Download full text (pdf)
    fulltext
  • 8.
    Engström, Jimmy
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Sony Europe B.V., Lund, Sweden.
    Improving Indoor Positioning With Adaptive Noise Modeling2020In: IEEE Access, E-ISSN 2169-3536, Vol. 8, p. 227213-227221Article in journal (Refereed)
    Abstract [en]

    Indoor positioning is important for applications within Internet of Things, such as equipment tracking and indoor maps. Inexpensive Bluetooth-beacons have become common for such applications, where the distance is estimated using the Received Signal Strength. Large installations require substantial efforts, either in determining the exact location of all beacons to facilitate lateration, or collecting signal strength data from a grid over all locations to facilitate fingerprinting. To reduce this initial setup cost, one may infer the positions using Simultaneous Location and Mapping. In this paper, we use a mobile phone equipped with an Inertial Measurement Unit, a Bluetooth receiver, and an Unscented Kalman Filter to infer beacon positions. Further, we apply adaptive noise modeling in the filter based on the estimated distance of the beacons, in contrast to using a fixed noise estimate which is the common approach. This gives us more granular control of how much impact each signal strength reading has on the position estimates. The adaptive model decreases the beacon positioning errors by 27% and the user positioning errors by 21%. The positioning accuracy is 0.3 m better compared to using known beacon positions with fixed noise, while the effort to setup and maintain the position of each beacon is also substantially reduced. Therefore, adaptive noise modeling of Received Signal Strength is a significant improvement over static noise modeling for indoor positioning.

    Download full text (pdf)
    fulltext
  • 9.
    Kebande, Victor R.
    et al.
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Internet of Things and People (IOTAP).
    Alawadi, Sadi
    Uppsala Universitet.
    Awaysheh, Feras
    University of Tartu.
    Persson, Jan A.
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Internet of Things and People (IOTAP).
    Active Machine Learning Adversarial Attack Detection in the User Feedback Process2021In: IEEE Access, E-ISSN 2169-3536, E-ISSN 2169-3536, Vol. 9Article in journal (Refereed)
    Abstract [en]

    Modern Information and Communication Technology (ICT)-based applications utilize currenttechnological advancements for purposes of streaming data, as a way of adapting to the ever-changingtechnological landscape. Such efforts require providing accurate, meaningful, and trustworthy output fromthe streaming sensors particularly during dynamic virtual sensing. However, to ensure that the sensingecosystem is devoid of any sensor threats or active attacks, it is paramount to implement secure real-timestrategies. Fundamentally, real-time detection of adversarial attacks/instances during the User FeedbackProcess (UFP) is the key to forecasting potential attacks in active learning. Also, according to existingliterature, there lacks a comprehensive study that has a focus on adversarial detection from an activemachine learning perspective at the time of writing this paper. Therefore, the authors posit the importance ofdetecting adversarial attacks in active learning strategy. Attack in the context of this paper through a UFPThreat driven model has been presented as any action that exerts an alteration to the learning system ordata. To achieve this, the study employed ambient data collected from a smart environment human activityrecognition from (Continuous Ambient Sensors Dataset, CASA) with fully labeled connections, where weintentionally subject the Dataset to wrong labels as a targeted/manipulative attack (by a malevolent labeler)in the UFP, with an assumption that the user-labels were connected to unique identities. While the dataset’sfocus is to classify tasks and predict activities, our study gives a focus on active adversarial strategies froman information security point of view. Furthermore, the strategies for modeling threats have been presentedusing the Meta Attack Language (MAL) compiler for purposes adversarial detection. The findings fromthe experiments conducted have shown that real-time adversarial identification and profiling during the UFPcould significantly increase the accuracy during the learning process with a high degree of certainty and pavesthe way towards an automated adversarial detection and profiling approaches on the Internet of CognitiveThings (ICoT).

    Download full text (pdf)
    fulltext
  • 10.
    Ozkan-Okay, Merve
    et al.
    Ankara Univ, Dept Comp Engn, TR-06100 Golbasi, Ankara, Turkiye..
    Akin, Erdal
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Internet of Things and People (IOTAP). Bitlis Eren Univ, Dept Comp Engn, TR-13100 Merkez, Bitlis, Turkiye..
    Aslan, Omer
    Bandirma Onyedi Eylul Univ, Dept Software Engn, TR-10250 Bandirma, Balikesir, Turkiye..
    Kosunalp, Selahattin
    Bandirma Onyedi Eylul Univ, Gonen Vocat Sch, Dept Comp Technol, TR-10250 Bandirma, Balikesir, Turkiye..
    Iliev, Teodor
    Univ Ruse, Dept Telecommun, Ruse 7017, Bulgaria..
    Stoyanov, Ivaylo
    Univ Ruse, Dept Elect Power Engn, Ruse 7017, Bulgaria..
    Beloev, Ivan
    Univ Ruse, Dept Transport, Ruse 7017, Bulgaria..
    A Comprehensive Survey: Evaluating the Efficiency of Artificial Intelligence and Machine Learning Techniques on Cyber Security Solutions2024In: IEEE Access, E-ISSN 2169-3536, Vol. 12, p. 12229-12256Article in journal (Refereed)
    Abstract [en]

    Given the continually rising frequency of cyberattacks, the adoption of artificial intelligence methods, particularly Machine Learning (ML), Deep Learning (DL), and Reinforcement Learning (RL), has become essential in the realm of cybersecurity. These techniques have proven to be effective in detecting and mitigating cyberattacks, which can cause significant harm to individuals, organizations, and even countries. Machine learning algorithms use statistical methods to identify patterns and anomalies in large datasets, enabling security analysts to detect previously unknown threats. Deep learning, a subfield of ML, has shown great potential in improving the accuracy and efficiency of cybersecurity systems, particularly in image and speech recognition. On the other hand, RL is again a subfield of machine learning that trains algorithms to learn through trial and error, making it particularly effective in dynamic environments. We also evaluated the usage of ChatGPT-like AI tools in cyber-related problem domains on both sides, positive and negative. This article provides an overview of how ML, DL, and RL are applied in cybersecurity, including their usage in malware detection, intrusion detection, vulnerability assessment, and other areas. The paper also specifies several research questions to provide a more comprehensive framework to investigate the efficiency of AI and ML models in the cybersecurity domain. The state-of-the-art studies using ML, DL, and RL models are evaluated in each Section based on the main idea, techniques, and important findings. It also discusses these techniques' challenges and limitations, including data quality, interpretability, and adversarial attacks. Overall, the use of ML, DL, and RL in cybersecurity holds great promise for improving the effectiveness of security systems and enhancing our ability to protect against cyberattacks. Therefore, it is essential to continue developing and refining these techniques to address the ever-evolving nature of cyber threats. Besides, some promising solutions that rely on machine learning, deep learning, and reinforcement learning are susceptible to adversarial attacks, underscoring the importance of factoring in this vulnerability when devising countermeasures against sophisticated cyber threats. We also concluded that ChatGPT can be a valuable tool for cybersecurity, but it should be noted that ChatGPT-like tools can also be manipulated to threaten the integrity, confidentiality, and availability of data.

  • 11.
    Zhang, Xuan-Yu
    et al.
    Jishou Univ, Sch Commun & Elect Engn, Jishou 416000, Hunan, Peoples R China.;Jishou Univ, Lab Ethn Cultural Heritage Digitizat Wuling Mt Ar, Jishou 416000, Hunan, Peoples R China..
    Zhou, Kai-Qing
    Jishou Univ, Sch Commun & Elect Engn, Jishou 416000, Hunan, Peoples R China.;Jishou Univ, Lab Ethn Cultural Heritage Digitizat Wuling Mt Ar, Jishou 416000, Hunan, Peoples R China..
    Li, Peng-Cheng
    Jishou Univ, Sch Commun & Elect Engn, Jishou 416000, Hunan, Peoples R China.;Jishou Univ, Lab Ethn Cultural Heritage Digitizat Wuling Mt Ar, Jishou 416000, Hunan, Peoples R China..
    Xiang, Yin-Hong
    Jishou Univ, Sch Commun & Elect Engn, Jishou 416000, Hunan, Peoples R China.;Jishou Univ, Lab Ethn Cultural Heritage Digitizat Wuling Mt Ar, Jishou 416000, Hunan, Peoples R China..
    Zain, Azlan Mohd
    Univ Teknol Malaysia, UTM Big Data Ctr, Skudai 81310, Johor, Malaysia..
    Sarkheyli-Hägele, Arezoo
    Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Internet of Things and People (IOTAP).
    An Improved Chaos Sparrow Search Optimization Algorithm Using Adaptive Weight Modification and Hybrid Strategies2022In: IEEE Access, E-ISSN 2169-3536, Vol. 10, p. 96159-96179Article in journal (Refereed)
    Abstract [en]

    Sparrow Search Algorithm (SSA) is a kind of novel swarm intelligence algorithm, which has been applied in-to various domains because of its unique characteristics, such as strong global search capability, few adjustable parameters, and a clear structure. However, the SSA still has some inherent weaknesses that hinder its further development, such as poor population diversity, weak local searchability, and falling into local optima easily. This manuscript proposes an improved chaos sparrow search optimization algorithm (ICSSOA) to overcome the mentioned shortcomings of the standard SSA. Firstly, the Cubic chaos mapping is introduced to increase the population diversity in the initialization stage. Then, an adaptive weight is employed to automatically adjust the search step for balancing the global search performance and the local search capability in different phases. Finally, a hybrid strategy of Levy flight and reverse learning is presented to perturb the position of individuals in the population according to the random strategy, and a greedy strategy is utilized to select individuals with higher fitness values to decrease the possibility of falling into the local optimum. The experiments are divided into two modules. The former investigates the performance of the proposed approach through 20 benchmark functions optimization using the ICSSOA, standard SSA, and other four SSA variants. In the latter experiment, the selected 20 functions are also optimized by the ICSSOA and other classic swarm intelligence algorithms, namely ACO, PSO, GWO, and WOA. Experimental results and corresponding statistical analysis revealed that only one function optimization test using the ICSSOA was slightly lower than the CSSOA and the WOA among the 20-function optimization. In most cases, the values for both accuracy and convergence speed are higher than other algorithms. The results also indicate that the ICSSOA has an outstanding ability to jump out of the local optimum.

1 - 11 of 11
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf