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A Survey on Ransomware: Evolution, Taxonomy, and Defense Solutions
[article]
2021
arXiv
pre-print
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domain very soon, understanding ransomware and analyzing defense mechanisms with respect to target platforms is becoming more imperative. ...
It has become a very profitable business for cybercriminals with revenues of millions of dollars, and a very serious threat to organizations with financial loss of billions of dollars. ...
ACKNOWLEDGEMENTS This work is partially supported by the US National Science Foundation Awards: NSF-CAREER-CNS-1453647 and NSF-1718116. ...
arXiv:2102.06249v1
fatcat:3n62zwlo2be47m3sinht5ts6bu
A Survey of Stealth Malware: Attacks, Mitigation Measures, and Steps Toward Autonomous Open World Solutions
[article]
2016
arXiv
pre-print
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and more lucrative targets for malware. ...
In this paper, we survey malicious stealth technologies as well as existing solutions for detecting and categorizing these countermeasures autonomously. ...
O N , z 1 , .., z N )) N , 2 HMMs are used for many sequential learning problems and have several different notations. ...
arXiv:1603.06028v2
fatcat:dyyemahzjze6bltxlwnnqgeyzy
EC2: Ensemble Clustering and Classification for Predicting Android Malware Families
2017
IEEE Transactions on Dependable and Secure Computing
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As the most widely used mobile platform, Android is also the biggest target for mobile malware. ...
We use the output of both supervised classifiers and unsupervised clustering to design EC2. ...
Part of this work was funded by ONR Grants N000141612739, N000141512007, N000141612896, and N000141512742, ARO grant W911NF1410358 and Maryland Procurement Office grant H9823014C0137. ...
doi:10.1109/tdsc.2017.2739145
fatcat:gfjfyb2mevcqnjvrrkffdp4dgq
Machine Learning Based Cyber Attacks Targeting on Controlled Information: A Survey
[article]
2021
arXiv
pre-print
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2021 accepted arXiv:2102.07969v2 fatcat:wfcs6efw5jgyxdk2jl4swoza7i
Detecting and defending against such attacks is challenging and urgent so that governments, organizations, and individuals should attach great importance to the ML-based stealing attacks. ...
Recent publications are summarized to generalize an overarching attack methodology and to derive the limitations and future directions of ML-based stealing attacks. ...
With N-gram probabilities representing the frequency of use, the tagged POS was used to select the most suitable segmentation for passwords. ...
arXiv:2102.07969v1
fatcat:h4br22tpjre2lisc4zbzpy2iee
International Research Conference on Smart Computing and Systems Engineering SCSE 2020 Proceedings [Full Conference Proceedings]
2020
2020 International Research Conference on Smart Computing and Systems Engineering (SCSE)
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ACKNOWLEDGMENT The authors would like to thank the Department of Census and Department of Irrigation, Sri Lanka for providing the paddy yield and climate data for this study. ...
in the University of Kelaniya for their immense support and encouragement they gave throughout the development phase of the data sets. ...
The mobile application was implemented using Android Studio for native Android development. The application was built for API level 26, and above and Gradle version 3.5.1 was used. ...
doi:10.1109/scse49731.2020.9313027
fatcat:gjk5az2mprgvrpallwh6uhvlfi
Applications in Security and Evasions in Machine Learning: A Survey
2020
Electronics
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By analyzing ML algorithms in security application it provides a blueprint for an interdisciplinary research area. ...
ML is used to address serious issues such as real-time attack detection, data leakage vulnerability assessments and many more. ...
All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/electronics9010097
fatcat:ttmpehdctjhbdk7arxgczl6224
Machine Learning for Security and the Internet of Things: the Good, the Bad, and the Ugly
2019
IEEE Access
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In this paper, we consider the good, the bad, and the ugly use of machine learning for cybersecurity and CPS/IoT. ...
Moreover, such technologies can be used by malicious actors, and the potential for cyber threats, attacks, intrusions, and obfuscation that are only just being considered, applied, and countered. ...
For instance, Zhang et al. [185] used n-gram and LSTM models to predict the end of bidding in online penny auctions, such as DealDash, with high accuracy, and clustered bidders into groups. ...
doi:10.1109/access.2019.2948912
fatcat:wxd6imn62fgufdmfh3gtaijeru
Mobile Behaviometrics: Behavior Modeling from Heterogeneous Sensor Time-Series
2018
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Over the decades, we have seen tremendous success in biometrics technologies being used in all types of applications based on the physical attributes of the individual such as face, fingerprints, voice ...
Inspired by this, we introduce a new concept Mobile Behaviometrics, which uses algorithms and models to measure and quantify unique human behavioral patterns in place of human bio-attributes. ...
Behavioral n-gram Model An n-gram model is an n-order Markov model for predicting the next item in a sequence. ...
doi:10.1184/r1/6720647
fatcat:lnk44fetsrcjbkaqibbh5jvzda
Analysis of Currently Open and Closed-source Software for the Creation of an AI Personal Assistant
2021
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Analysis of currently open and closed-source software for the creation of an AI personal assistant. ...
For example, for all HMM-based systems, an ngram language model is required, and a typical n-gram language model often takes several gigabytes of memory to make it impractical to deploy on mobile devices ...
I could not get all the expected Alexa results because I was not using Alexa Echo, the device Alexa works efficiently, but I was only using its android application. ...
doi:10.7939/r3-f0jh-se38
fatcat:cw7fta23p5ffxn243r3gd6bmdm
IDENTIFYING SMARTPHONE USERS BASED ON SMARTWATCH DATA IDENTIFYING SMARTPHONE USERS BASED ON SMARTWATCH DATA
2017
unpublished
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For identification of a user, walking activity and call receiving activity are analyzed when the phone is on the table and in pocket or bag. ...
In recent years, smartphones have become part and parcel of peoples life. Smartphones are used for all day-today critical tasks like money transfer, storing important documents and other information. ...
For example, the way in which the user receives the phone, how often they move their hand while talking and doing other gestures. ...
fatcat:2gh55qpjrzajdka77gsl67kbmy
IMMM 2014 COMMITTEE IMMM Advisory Committee
unpublished
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to the development of special mining techniques, mechanisms support, applications and enabling tools. ...
a series of academic and industrial events focusing on advances in all aspects related to information mining, management, and use. ...
We developed an application available to Android smartphones, and used it for field testing in the city of Nagasaki, Japan. ...
fatcat:o5d5shizvratfpaaiibw7o2dhm
Robust behavioral malware detection
[article]
2018
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We evaluate Shape-GD by emulating a large community of Windows systems using the system call traces from a few thousand malicious and benign applications; we simulate both a phishing attack in a corporate ...
In both scenarios, Shape-GD identifies malware early on (∼100 infected nodes in a ∼100K-node system for watering hole attacks, and ∼10 of ∼1,000 for phishing attacks) and robustly (with ∼100% vi global ...
However, we have experimentally determined that FPs and TPs are separable for other LD types as well -an n-gram-based LD [95] and an LD that uses VirusTotal [46] reports for malware detection [117 ...
doi:10.15781/t2bn9xn0t
fatcat:mw4vzzmed5cujgyxiuhcxrwbna
Ubiquitäre Systeme (Seminar) und Mobile Computing (Proseminar) SS 2016. Mobile und Verteilte Systeme. Ubiquitous Computing. Teil XIV
2016
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As well as utilization rate, ratio between samples used for estimation and total samples. The HMM selection chose 4-state for 14 subjects and 2-state for the other 6. ...
Furthermore, soft sensor data such as application usage and web browser history are also recorded. ...
doi:10.5445/ir/1000062232
fatcat:rrcknw54vveibidmngtnqvw4iq
Real-time autonomic decision making under uncertain environments for UAV-based search-and-rescue missions
2020
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For this, I propose an actor-critic based Multi-Agent Deep Reinforcement Learning (MADRL) framework where the critic is trained in a centralized manner and the actor is decentralized and is used during ...
transformation of sensor data into actionable knowledge by giving semantic meaning to the raw data) and planning (making real-time decisions using this knowledge). ...
Mannini et al. [76] use HMMs for human user activity using HMM based on sensor measurements [76-79]. ...
doi:10.7282/t3-ms6y-wr38
fatcat:lnh6thuktvartnxdz6wnmtpkea
and On-line Learning eLmL 2017 COMMITTEE eLmL Steering Committee
2017
The Ninth International Conference on Mobile, Hybrid, The ninth edition of the International Conference on Mobile, Hybrid, and On-line Learning
unpublished
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The constraints of e-learning are diminishing and options are increasing as the Web becomes increasingly easy to use and the technology becomes better and less expensive. eLmL 2017 provided a forum where ...
We hope that eLmL 2017 was a successful international forum for the exchange of ideas and results between academia and industry and for the promotion of progress in eLearning research. ...
Special thanks to the research team in educational technology seminar, and school of computer science and information technology at Northeast Normal University. ...
fatcat:qex5su5c3fd2vlncczyh4mtav4
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