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An Intellect Learning on E-Mail Security and Fraud, Spam and Phishing
2015
International journal of network security and its applications
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Nonetheless hefty figure of security and privacy available with modern expertise; phishing, spam and email fraud are more equally exasperating. ...
In this intellect learning, the authors' primary interest is to make a healthy charge on phishing, spam and email fraud towards the wealthy personal information and realm.Official and business related ...
Hossain et al [13] intended the associative classification data mining ebanking phishing website archetypal. ...
doi:10.5121/ijnsa.2015.7503
fatcat:eibm2q4svnaexh2xzbkgrzuf4i
SoK: Applying Machine Learning in Security - A Survey
[article]
2016
arXiv
pre-print
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As information and communications grow more ubiquitous and more data become available, many security risks arise as well as appetite to manage and mitigate such risks. ...
We examine the generalized system designs, underlying assumptions, measurements, and use cases in active research. ...
We emphasize a position which treats security as a game theory problem. ...
arXiv:1611.03186v1
fatcat:hfvc5hhu7ze77lrnjufslcg6gm
Cyberspace Security Using Adversarial Learning and Conformal Prediction
2015
Intelligent Information Management
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This paper advances new directions for cyber security using adversarial learning and conformal prediction in order to enhance network and computing services defenses against adaptive, malicious, persistent ...
Conformal prediction is the principled and unified adaptive and learning framework used to design, develop, and deploy a multi-faceted self-managing defensive shield to detect, disrupt, and deny intrusive ...
One early example for data mining use is audit data analysis and mining (ADAM) system [55] to discover attacks in a TCP dump audit trail using KDD 1999 for test bed and seeking DOS and PROBE attacks. ...
doi:10.4236/iim.2015.74016
fatcat:wqiu3pkl6zeurlr3mizdahhgd4
The Threat of Offensive AI to Organizations
[article]
2021
arXiv
pre-print
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AI has provided us with the ability to automate tasks, extract information from vast amounts of data, and synthesize media that is nearly indistinguishable from the real thing. ...
However, positive tools can also be used for negative purposes. In particular, cyber adversaries can use AI (such as machine learning) to enhance their attacks and expand their campaigns. ...
Pin-Yu Chen, Evan Downing, and Didier Contis for taking the time to participate in our survey. ...
arXiv:2106.15764v1
fatcat:zkfukg4krjcczpie2gbdznwqqi
Artificial Intelligence in the Cyber Domain: Offense and Defense
2020
Symmetry
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In the cybersecurity domain, AI-based techniques can provide better cyber defense tools and help adversaries improve methods of attack. ...
However, malicious actors are aware of the new prospects too and will probably attempt to use them for nefarious purposes. ...
Meanwhile, the scholars in [10] presented a framework for classifying and detecting malicious software using data mining and ML classification. ...
doi:10.3390/sym12030410
fatcat:7gyse3gaxjguhgkvfnbi7knkf4
Online social networks security and privacy: comprehensive review and analysis
2021
Complex & Intelligent Systems
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Finally, this survey discusses open issues, challenges, and relevant security guidelines to achieve trustworthiness in online social networks. ...
The attacker can maliciously use shared information for illegitimate purposes. The risks are even higher if children are targeted. ...
It uses data mining procedures on visibly available data like the user's friend list and network topology [62] . ...
doi:10.1007/s40747-021-00409-7
fatcat:s4mc4ydaa5hdhpgghwqsjmyruq
Table of Contents
2020
2020 International Conference on Data Mining Workshops (ICDMW)
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Hefei , China), and Shengli Zhang (Anhui Zhiqu Cherub Information Technology Co., Ltd Suzhou, China) 1st International Workshop on Multi-Source Data Mining (MSDM) Ensemble Node Embeddings using Tensor ...
di Torino) and Luca Cagliero (Politecnico di Torino) Stock Price Prediction by Using Hybrid Sequential Generative Adversarial Networks 341 Bate He (Nagoya University) and Eisuke Kita (Graduate School ...
International Workshop on Mining and Learning in the Legal Domain (MLLD-2020) ...
doi:10.1109/icdmw51313.2020.00004
fatcat:ykrkkp5hx5asrpvw6r3oo4rwcq
Detecting adversarial advertisements in the wild
2011
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '11
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In this paper, we present a large scale data mining effort that detects and blocks such adversarial advertisements for the benefit and safety of our users. ...
Because both false positives and false negatives have high cost, our deployed system uses a tiered strategy combining automated and semi-automated methods to ensure reliable classification. ...
Features Feature engineering is a key component of effective data mining; the following is a listing of the features extracted from advertisements during training and classification. • Natural language ...
doi:10.1145/2020408.2020455
dblp:conf/kdd/SculleyOPSHZ11
fatcat:fsfthv6nlvcehohmq36j3fjuty
Harnessing Artificial Intelligence Capabilities to Improve Cybersecurity
2020
IEEE Access
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posed by adversaries. ...
Advances in cryptographic and Artificial Intelligence (AI) techniques (in particular, machine learning and deep learning) show promise in enabling cybersecurity experts to counter the ever-evolving threat ...
ACKNOWLEDGMENT The authors would like to thank the anonymous reviewers for their valuable comments and suggestions which helped us improve the content, quality, and presentation of this paper. ...
doi:10.1109/access.2020.2968045
fatcat:tb6xkdqqhfcahb5soip66x5qce
Online Social Deception and Its Countermeasures for Trustworthy Cyberspace: A Survey
[article]
2020
arXiv
pre-print
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used for validation and verification; and (v) legal and ethical concerns related to OSD research. ...
We are living in an era when online communication over social network services (SNSs) have become an indispensable part of people's everyday lives. ...
The current countermeasures against OSD related cybercrimes have mainly focused on detecting them using data mining [79] , text mining using machine learning (e.g., text mining for posts, tweets/retweets ...
arXiv:2004.07678v1
fatcat:k4a6siywefb6lhkmyn67lmoqwe
A Survey on Threat Situation Awareness Systems: Framework, Techniques, and Insights
[article]
2021
arXiv
pre-print
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This paper provides a comprehensive study on the current state-of-the-art in the cyber SA to discuss the following aspects of SA: key design principles, framework, classifications, data collection, and ...
and devising a plan to avoid further attacks. ...
ACKNOWLEDGEMENT This work was supported by the Cyber Security Research Programme-"Artificial Intelligence for Automating Response to Threats" from the Ministry of Business, Innovation, and Employment ( ...
arXiv:2110.15747v1
fatcat:zboddcg4a5gdxmq5hqmo5cpj34
Harvesting the Low-hanging Fruits: Defending Against Automated Large-Scale Cyber-Intrusions by Focusing on the Vulnerable Populations
2016
Zenodo
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This paper considers the implications of the proposed paradigm on existing defenses in three areas (phishing of user credentials, malware distribution and socialbot infiltration) and discusses how using ...
., phishing emails, social-bot infiltrations, malware offered for download). ...
for various adversarial objectives [10] , including social spamming [80] , political astroturfing [65] , and private data collection [12] . ...
doi:10.5281/zenodo.3264717
fatcat:pqzoajvmefblbdz6yqrfrdnl7m
Deep Reinforcement Learning for Cyber Security
[article]
2020
arXiv
pre-print
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We touch on different vital aspects, including DRL-based security methods for cyber-physical systems, autonomous intrusion detection techniques, and multi-agent DRL-based game theory simulations for defense ...
The complexity and dynamics of cyber attacks require protecting mechanisms to be responsive, adaptive, and scalable. ...
model, and other machine learning or data mining methods. ...
arXiv:1906.05799v3
fatcat:h4lujrwb5bgwngbi4xf6w347b4
Security Threats and Artificial Intelligence based Countermeasures for Internet of Things Networks: A Comprehensive Survey
2021
IEEE Access
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LATENCY Real-time IoT applications (such as driverless vehicles, healthcare, banking and supply-chain, online banking, etc.) use limitless training data to create a deterministic ML model. ...
[171] invented a unique lightweight AI enable security mechanism using SVM and online ML to ensure faster authentication by detecting the malicious data injection attacks in the IoT networks. ...
doi:10.1109/access.2021.3089681
fatcat:fatpywnjzzfilidakyduz6qz44
Online Social Deception and Its Countermeasures: A Survey
2020
IEEE Access
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and cybercrimes; 3) comprehensive defense mechanisms embracing prevention, detection, and response (or mitigation) against OSD attacks along with their pros and cons; 4) datasets/metrics used for validation ...
We are living in an era when online communication over social network services (SNSs) have become an indispensable part of people's everyday lives. ...
TABLE 8 . 8 Classification used for the defense mechanisms to deal with online social deception attacks in this survey. ...
doi:10.1109/access.2020.3047337
fatcat:xw2rr2sjnrdf3nk4vfuowrkizy
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