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Automated State Machines Applied in Client Honeypots
2010
2010 5th International Conference on Future Information Technology
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If known malicious similarities are found, then it predicts the possible future malicious behaviour of the current web page and reports this back to the system. ...
By using this label, we can identify similarity between groups and then use the label to match with new data. ...
doi:10.1109/futuretech.2010.5482695
fatcat:n6xgujmyeng6lmqgqwoou52cfy
Internet of Things Applications, Security Challenges, Attacks, Intrusion Detection, and Future Visions: A Systematic Review
2021
IEEE Access
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learning techniques for data pre-processing and malware detection has been discussed. ...
It makes up for an urgent need to assess present security risks and discuss the upcoming challenges to be ready to face the same. ...
In the future, we plan to implement these solutions and develop a robust and generalized intrusion detection model. ...
doi:10.1109/access.2021.3073408
fatcat:ebzvtidh2relplv3kn3t6plygu
Leveraging CybOX™ to standardize representation and exchange of digital forensic information
2015
Digital Investigation. The International Journal of Digital Forensics and Incident Response
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The capability to represent provenance by leveraging CybOX is also demonstrated, including specifics of the tool used to process digital evidence and the resulting output. ...
With the growing number of digital forensic tools and the increasing use of digital forensics in various contexts, including incident response and cyber threat intelligence, there is a pressing need for ...
Conclusions and future work To be effective, digital forensic information needs to be represented and shared in a form that is consistent across all applicable contexts and tools. ...
doi:10.1016/j.diin.2015.01.014
fatcat:4tljk4lhdngvrdheqwwacxtana
Online Advertising Security: Issues, Taxonomy, and Future Directions
[article]
2021
arXiv
pre-print
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to discover new security vulnerabilities in the model, to propose countermeasures and to forecast future trends in research. ...
To complete our work, we identify some open issues and outline some possible directions for future research towards improving security methods for online advertising systems. ...
The authors in [137] used the UI-based methodology to detect malware on the mobile operating system. They claimed that it is essential to find the source of the attack in order to detect it. ...
arXiv:2006.03986v4
fatcat:vyxorsmo4rgdllv7lmntc5bv7i
NLP Methods in Host-based Intrusion Detection Systems: A Systematic Review and Future Directions
[article]
2022
arXiv
pre-print
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We highlight the prevalent practices and the future research areas. ...
We conduct a systematic review of the literature on NLP-based HIDS in order to build a systematized body of knowledge. ...
ACKNOWLEDGMENTS The work has been supported by the Cyber Security Research Centre Limited whose activities are partially funded by the Australian Government's Cooperative Research Centres Programme. ...
arXiv:2201.08066v1
fatcat:t6nsqoj5hnhnhcv4hsugsnau6m
Learning-Based Methods for Cyber Attacks Detection in IoT Systems: Methods, Analysis, and Future Prospects
2022
Electronics
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Finally, future research directions are also provided in the paper. ...
For learning-based methods, both machine and deep learning methods are presented and analyzed in relation to the detection of cyber attacks in IoT systems. ...
In [54] , the hierarchical stacking-temporal convolutional network (HS-TCN) was developed to detect anomalies in the communication of smart homes. ...
doi:10.3390/electronics11091502
fatcat:stweql4ru5behg2scpumznzy6i
A Review of Intrusion Detection Systems Using Machine and Deep Learning in Internet of Things: Challenges, Solutions and Future Directions
2020
Electronics
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This work also covers the analysis of various machine learning and deep learning-based techniques suitable to detect IoT systems related to cyber-attacks. ...
The Internet of Things (IoT) is poised to impact several aspects of our lives with its fast proliferation in many areas such as wearable devices, smart sensors and home appliances. ...
This leads to exposing all information stored on the phone with the possibility of malware compromise. ...
doi:10.3390/electronics9071177
fatcat:isocsvn75ja6bfqsk2wekuufyy
Current and Future Challenges in Mining Large Networks
2016
SIGKDD Explorations
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This half-day workshop consisted of a keynote talk, four technical paper presentations, one demonstration, and a panel on future challenges in mining large networks. ...
The current and future challenges discussed at the workshop and elaborated here provide valuable guidance for future research in the field. ...
Graphs are a popular representation for such data because of their ability to represent different entity and relationship types, including the temporal relationships necessary to represent the dynamics ...
doi:10.1145/2980765.2980770
fatcat:e7g5ju6icnclpmc6z56rprwqu4
Machine Learning for Authentication and Authorization in IoT: Taxonomy, Challenges and Future Research Direction
2021
Sensors
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With the ongoing efforts for widespread Internet of Things (IoT) adoption, one of the key factors hindering the wide acceptance of IoT is security. ...
To address the security issue of IoT, several studies are being carried out that involve the use of, but are not limited to, blockchain, artificial intelligence, and edge/fog computing. ...
the dynamic malware detection game. ...
doi:10.3390/s21155122
fatcat:auzbla5c4rhzfdtnhmxeedyymq
Deep Learning-Based Network Security Data Sampling and Anomaly Prediction in Future Network
2020
Discrete Dynamics in Nature and Society
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With the comparison of various algorithms and the adjustment of hyperparameters, the data characteristics and classification algorithms corresponding to different network security attacks are found. ...
Deep learning methods are used on the selected nodes to collect data and analyze the characteristics of the network data. ...
In order to ensure the security of the network, it is necessary to detect packets in the future network. ...
doi:10.1155/2020/4163825
fatcat:ob7ggsp2cfbs3nnedq72o2ik4y
D2.1 5G Security: Current Status and Future Trends
2020
Zenodo
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domain of 5G security, the relevant 5G projects, and open source initiatives; and a description of future trends and technologies in 5G networks, their limitations, and gaps related to the security of ...
This deliverable aims to provide a basis for the identification of use cases and the development of 5G security enablers in INSPIRE-5Gplus. ...
In the context of future networks, where there will be a huge amount of data, it is impractical to manually label a dataset. ...
doi:10.5281/zenodo.3947893
fatcat:bg7jnn5ph5fv3gjp7pqacy3us4
AIs 10 to Watch: The Future of AI
2018
IEEE Intelligent Systems
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These initial successes point the way to important future research and applications in a wide range of security arenas. ...
The 2018 group consists of 10 young stars who have demonstrated outstanding AI achievements. ...
doi:10.1109/mis.2018.012001549
fatcat:mfx4dnb5lrgjbizilzh2anbcz4
D2.1 5G Security: Current Status and Future Trends
2020
Zenodo
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domain of 5G security, the relevant 5G projects, and open source initiatives; and a description of future trends and technologies in 5G networks, their limitations, and gaps related to the security of ...
This deliverable aims to provide a basis for the identification of use cases and the development of 5G security enablers in INSPIRE-5Gplus. ...
In the context of future networks, where there will be a huge amount of data, it is impractical to manually label a dataset. ...
doi:10.5281/zenodo.4569519
fatcat:7aersbhzyrccrn563shazvj4dq
Network Forensics Method Based on Evidence Graph and Vulnerability Reasoning
2016
Future Internet
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volume and to back track the attacks. ...
Zhang et al. applied machine learning methods to detecting malware activities through network traffic analysis [20] and developed an approach to analyze programs as black boxes from the network perspective ...
Acknowledgments: The work presented in this paper has been supported by funding from National High-Tech R&D Program (863 Program) (2015AA017204), National Natural Science Foundation of China (61272500) ...
doi:10.3390/fi8040054
fatcat:efksu26pofhtxekc3geldfxdsa
Federated Learning for Intrusion Detection System: Concepts, Challenges and Future Directions
[article]
2021
arXiv
pre-print
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Machine Learning and Deep Learning with Intrusion Detection Systems have gained great momentum due to their achievement of high classification accuracy. ...
The present paper aims to present an extensive and exhaustive review on the use of FL in intrusion detection system. ...
i th client, back to the server. ...
arXiv:2106.09527v1
fatcat:vsy4l2ew4nbh5j3gzdlao4ngxe
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