Dear all,
We have submitted the paper „Technical Threat Intelligence Analytics: What and How to Visualize for Analytic Process“ to the 24th International Conference ELECTRONICS 2020
Abstract: Visual Analytics uses data visualization methods for enabling compelling analysis of data by engaging graphical and visual representation. In the domain of cybersecurity, convincing visual representation of data enables to ascertain valuable observations that allow the domain experts to construct efficient cyberattack mitigation strategies and provide useful decision support. In this paper, we present a survey of the visual analytics tools and methods in the domain of cybersecurity. We explore and discuss Technical Threat Intelligence visualization tools using the Five Question Method. We conclude the analysis of the works using Moody’s Physics of Notations, and VIS4ML ontology as a methodological background of visual analytics process.
This paper is still under evaluation.
If it gets accepted, we will acknowledge SPARTA.
Best,
Algimantas Venčkauskas
Kauno technologijos universitetas
Dear All,
We submitted Sparta paper (attached) to a journal in January 2020.
Title: Securing Organization’s Data: A Role-Based Authorized Keyword Search Scheme with Efficient Decryption
By: Nazatul Haque Sultan, Maryline Laurent, Vijay Varadharajan.
If accepted we plan to acknowledge SPARTA.
Kind Regards,
Prof. Maryline Laurent
Maryline Laurent
Professor, Télécom SudParis
Head of R3S team, CNRS UMR5157 SAMOVAR lab
Cofounder of the chair Values and Policies of Personal Information
9 rue Charles Fourier, 91011 EVRY
+33 (0)160764442
Dear all,
we plan to submit the survey paper “Security and Privacy Protection for
Intelligent Infrastructures in the Post-Quantum Era” to the journal IEEE
COMMUNICATIONS SURVEYS & TUTORIALS.
Please find the compressed manuscript version in the attachment. The paper is in
line with WP6 - Task 6.5 Privacy-by-Design and does not contain any
sensitive information.
If the paper will be accepted and no objections will be raised by diss.
committee, we would like to acknowledge to SPARTA.
Thank you.
Best regards,
Lukas Malina
--
doc. Ing. Lukáš Malina, Ph.D.
E-mail: malina(a)feec.vutbr.cz
Brno University of Technology
Faculty of Electrical Engineering and Communication
Department of Telecommunications
Technicka 12
616 00 Brno
Czech Republic
Dear all,
UNamur wrote a paper titled "GDPR and Automated individual
decision-making: Fair processing v. Fair result". In order to respect
the deadline set by the GA, please find enclosed the complete draft of
the publication.
If the dissemination committee raises no objections, we would like to
acknowledge SPARTA.
Best regards,
Manon
--
MANON KNOCKAERT
Chercheuse
Centre de Recherches Information, Droit et Société
T. +32 (0)81 724 798
F. +32 (0)81 725 202
manon.knockaert(a)unamur.be <mailto:manon.knockaert@unamur.be>
http://www.unamur.be
Université de Namur
Rue de Bruxelles 61 - 5000 Namur
Belgique
Let's respect the environment together.
Only print this message if necessary!
Dear Dissemination Committee,
we have about to publish a paper for which we would like to acknowledge
the SPARTA project.
Please, find the version that we plan to submit in attachment and a
brief description of the content, the venue and the relation with the
activities of WP6 below.
Please let us know if you have any objections or comments.
Best regards
Gabriele Costa
===
Title: WAF-A-MoLE: Evading Web Application Firewalls through Adversarial
Machine Learning
Venue: ACM Symposium on Applied Computing
Relationship with SPARTA: The paper presents a a technique to evade
machine learning-based web application firewalls (WAFs). This work shows
that ML WAFs are not reliable in discriminating between attack payloads
and harmless traffic. The activity is related to the identification and
evaluation of the state-of-the-art technologies adopted in the IIs.
Dear all,
If the dissemination committee raises no objections, we would like to acknowledge the SPARTA project on the attached paper (not yet the camera ready version).
This paper has been recently accepted at ESEC/FSE conference (https://2020.esec-fse.org/).
This paper is related to our research activities performed in WP5 Cape.
Jun Gao, Li Li, Pingfan Kong, Tegawendé F. Bissyandé and Jacques Klein,
Borrowing Your Enemy’s Arrows: the Case of Code Reuse in Android via Direct Inter-app Code Invocation,
28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2020), Nov. 2020, To appear, Sacramento, CA, United States
--
Prof. Jacques Klein
Chief Scientist
University of Luxembourg - SnT
00352 46 66 44 56 00 / Gsm: 0033 6 06 47 62 54
https://jacquesklein2302.github.io/
Dear all,
I would like to announce the submission and acceptance to ECAI2020 of our paper. It falls in the topics of SAFAIR: the idea is that one of the main obstacles to the usage of formal methods in verification and validation of NN is the absence of formal specification against which to verify. Our paper proposes a framework for NN that are trained on simulated data (a prevalent process in certain areas where not enough "real" data is available -- automotive for example), whereby the simulation process itself could be considered as a spec.
I will send you a link to the proceedings when they will be available online.
@inproceedings{girardsatabin2020,
TITLE = {{CAMUS: A Framework to Build Formal Specifications for Deep Perception Systems Using Simulators}},
AUTHOR = {Girard-Satabin, Julien and Charpiat, Guillaume and Chihani, Zakaria and Schoenauer, Marc},
URL = {https://hal.inria.fr/hal-02440520},
BOOKTITLE = {{ECAI 2020 - 24th European Conference on Artificial Intelligence}},
ADDRESS = {Santiago de Compostela, Spain},
YEAR = {2020},
MONTH = Jun,
HAL_ID = {hal-02440520},
HAL_VERSION = {v1},
}
Best wishes, stay safe.
Zak
_____________________________
Dear Dissemination Committee,
The previously announced accepted paper is now published in Future
Generation Computer Systems (IF=5,768).
I am sending attached the 'authors version' that can be posted online (if
necessary) with the proper citation/reference:
Pawlicki M., Choras M., Kozik R., Defending network intrusion detection
systems against adversarial evasion attacks , Future Generation Computer
Systems, Volume 110, September 2020, Pages 148-154, 2020.
The link:
https://www.sciencedirect.com/science/article/abs/pii/S0167739X20303368
Stay safe,
Kind Regards,
prof. Michal Choras
-------------------------- Wiadomość oryginalna --------------------------
Temat: [Fwd: Request for SPARTA acknowledgment in paper]
Od: mchoras(a)itti.com.pl
Data: 7 Kwietnia 2020, 9:59 pm, Wt
Do: bodies.dissemination-committee(a)internal.sparta.eu
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Dear All,
Just to let you know, the announced journal paper has been accepted :-).
We will share the final version in due time.
Regards,
prof. Michal Choras
-------------------------- Wiadomość oryginalna --------------------------
Temat: Request for SPARTA acknowledgment in paper
Od: mchoras(a)itti.com.pl
Data: 26 Stycznia 2020, 7:57 pm, N
Do: bodies.dissemination-committee(a)internal.sparta.eu
--------------------------------------------------------------------------
Dear All,
We submitted Sparta/Safair relevant paper (attached) to FGCS (Elsevier).
Title: Defending Network Intrusion Detection Systems against Adversarial
Evasion Attacks
By: Pawlicki, Choras, Kozik.
If accepted we plan to acknowledge SPARTA.
Kind Regards,
Prof. Michal Choras
Dear All,
we submitted a workshop paper "ModelSpeX: Model Specification Using
Explainable Artificial Intelligence Methods" to the**MLVis 2020
Workshop. We request to acknowledge SPARTA if the paper is accepted.
Abstract:
* /Explainable artificial intelligence (XAI) methods aim to reveal the
non-transparent decision-making mechanisms of black-box models
(e.g., deep learning models). The evaluation of insight generated by
such XAI methods remains challenging as the applied techniques
depend on many factors (e.g., parameters, human interpretation). We
propose ModelSpeX, a visual analytics workflow to interactively
extract human-centered rule-sets to generate model specifications
from black-box models. The workflow enables to reason about the
underlying problem, to extract rule sets, and to evaluate the
suitability of the models for a particular task. An exemplary usage
scenario walks an analyst trough the steps of the workflow to show
the applicability.//
//
/
Best Regards,
Eren Cakmak