Treat agents
5. CO N CLU SIO N
As can be seen from the above, the process o f introducing Artificial Intelligence methods at the different levels o f Cyber Threat Intelligence is at very different stages: while in Tactical Intelligence, it has long gone out o f the phase o f research and experiments and is used for building real effective systems, In the field o f Operational Intelligence, these studies are in a very initial phase and require the commitment o f substantial resources. Furthermore, the question arises as to the application o f possible outcomes o f Operational Iintelligence in the activity of Tactical Intelligence systems, which are intended to neutralize the immediate threats to computer systems and networks.
R EFER EN C ES
[1] ENISA Threats Landscape Report 2 0 1 6 : 15 T o p C y b e r - T h r e a ts a n d T re n d s , J a n u a r y 2 0 1 7
[2] R e p u b lic o f B u lg a ria : National Cyber Security Strategy “Cyber Resilient Bulgaria 2020” 2 0 1 6 -0 3 N C S S B u lg a r ia fin a l d r a f t v 5 3
[3] Cyber Intelligence: Setting the Landscape fo r an emerging Discipline, Intelligence and National Security Alliance ( I N S A ), 2 0 1 1
[4] Operational Level o f Cyber Intelligence, IN S A , 2 0 1 3 [5] Operational Cyber Intelligence, IN S A , 2 0 1 4
[6] B r ia n P . K im e Threat Intelligence: Planning and Direction, S A N S In s titu te , 2 0 1 5
[7] L iu Y ., S o u r in a O . a n d N g u y e n M . K . R e a l- tim e E E G - b a s e d h u m a n e m o tio n r e c o g n itio n a n d v is u a liz a tio n , Proceedings o f the Int. Conf. on Cyberworlds ( C W ’ 10), S in g a p o r e , 2 0 1 0
[8] [R F C 1 7 5 7 R e m o te N e tw o r k M o n ito r in g M a n a g e m e n t I n f o r m a tio n B a s e , C a rn e g ie M e llo n U n iv e r s ity , F e b r u a r y 1995
[9] L . B o z h k o v , P . G e o r g ie v a C la s s if ic a tio n m o d e ls o f e m o tio n a l b io s ig n a ls e v o k e d w h ile v ie w in g
a f f e c tiv e p ic tu r e s , International Conference on Simulation and Modeling Methodologies,
Technologies and Applications ( S I M U L T E C H ) , V ie n n a , 2 0 1 4
[1 0 ] H a m m o n P .S . a n d S a V .R . d e P r e p r o c e s s in g a n d m e ta - c la s s if ic a tio n f o r b r a in - c o m p u te r in te rfa c e s ,
IEEE Transactions on Biomedical Engineering, 5 4 (3 ) , 2 0 0 7 .
[1 1 ] E r ik H je lm v ik P a s s iv e N e tw o r k S e c u r ity A n a ly s is w ith N e tw o r k M in e r F o r e n s ic F o c u s , 2 0 0 8
[1 2 ] L u k o s e v ic iu s M . a n d J a e g e r H . R e s e r v o ir c o m p u tin g a p p r o a c h e s to r e c u r r e n t n e u r a l n e tw o r k tr a in in g ,
Computer Science Review, v o l. 3, 2 0 0 9
[1 3 ] K o p r in k o v a - H r is to v a P ., B o z h k o v L . a n d G e o r g ie v a P. E c h o S ta te N e tw o r k s f o r f e a tu r e s e le c tio n in a f f e c tiv e c o m p u tin g 13th Int. Conf. on Practical Applications o f Agents and Multi-Agent Systems (PAAMS), S p a in , 3 -5 J u n e 2 0 1 5
20-21 September 2018, BULGARIA 65
[1 4 ] G u y o n I. a n d E l i s s e e f f A . A n I n tr o d u c tio n to V a r ia b le a n d F e a tu r e S e le c tio n , Journal o f Machine Learning Research, v o l. 3, 2 0 0 3
Proceedings o f the International Conference on Information Technologies (InfoTech-2018) 20-21 September 2018, Bulgaria
M O D E L L I N G A N D I M P L E M E N T A T I O N O F M A C H I N E L E A R N I N G T E C H N I Q U E S F O R H A T E S P E E C H
D E T E C T I O N I N M O B I L E A P P L I C A T I O N S
B u ja r Raufi, Ildi X h aferri
South East European University, Canadian Institute o f Technology e-mails: b.raufi@seeu.edu.mk, ildi.xhaferri@cit.edu.al
Republic o f Macedonia, Republic o f Albania
Abstract:
The proliferation o f data through various platforms and applications is in constant increase. The versatility o f data and its omnipresence makes it very hard to detect the trustworthiness and intention o f the source. This is very evident in dynamic environments such as mobile applications. As a result, designing mobile applications that will monitor, control and block any type o f malintents is important. This paper makes an attempt in this direction by implementing a lightweight machine learning classification scheme for hate speech detection in Albanian Language for mobile applications. Initial testing and evaluations indicate good classifier accuracy in mobile environments where frequent and realtime training o f the algorithm is required.Key words:
automatic hate speech detection, machine learning, artificial neural networks (ANNs)This p ap e r is published in IE E E X plore D igital L ib ra ry and the inform ation can be accessed by URL:
https://ieeexplore.ieee.org/xpl/mostRecentIssue.isp?punumber=8500053
20-21 September 2018, BULGARIA 75 Proceedings o f the International Conference on Information Technologies (InfoTech-2018) 20-21 September 2018, Bulgaria
A R T I F I C I A L I N T E L L I G E N C E I N I N T E R N E T O F M E D I C A L I M A G I N G T H I N G S : T H E P O W E R O F
T H Y R O I D C A N C E R D E T E C T I O N
Desislava Ivanova
Technical University o f Sofia, Faculty o f Applied Mathematics and Informatics e-mail: d_ivanova@tu-sofia.bg
Bulgaria
Abstract:
The paper proposed an approach for thyroid cancer detection based on artificial intelligence in Internet o f Medical Imaging Things (IoMIT) ecosystem.Ultrasonic imaging collected in IoMIT ecosystem is the best way for thyroid cancer diagnosis. Image segmentation and detection o f benign and malignant thyroid nodules is an important part o f the proposed approach. It is implemented in Apache Spark using MLlib based on Convolutional Neural Networks (CNNs). Finally, the results o f medical imaging analytics are discussed.
Key words:
Internet o f Things (IoT), Internet o f Medical Imaging Things (IoMIT), Artificial Intelligence (AI), Big Data (BD), Thyroid Cancer Detection.This p ap e r is published in IE E E X plore D igital L ib ra ry and the inform ation can be accessed by URL:
https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8500053
Proceedings o f the International Conference on Information Technologies (InfoTech-2018) 20-21 September 2018, Bulgaria
D U A L M L P P A I R S W I T H H I D D E N L A Y E R S H A R I N G
Ivan Blagoev, Ja n e ta Sevova, Kolyu Kolev
Institute o f Information and Communication Technologies Bulgarian Academy o f Sciences
e-mails: i.blagoev@iit.bas.bg Bulgaria
Abstract:
Artificial neural networks (ANN) are well known and widely used from decades. One o f the most popular is the multilayer perceptron (MLP). M PL’s general characteristic is that it has more than one layer. The most used topology o f MLP has three layers (input, hidden and output). Layers are fully-connected, between each other (the input with the hidden layer and the hidden layer with the output). The general disadvantage o f this topology is the lack o f recurrent connections. The common usage of MLP is to solve only a single task. This research addresses these two common features o f the MLP.Key words:
artificial neural networks, multilayer perceptron, topologies.This article has not been presented d u rin g the conference sessions
20-21 September 2018, BULGARIA 87 Proceedings o f the International Conference on
Information Technologies (InfoTech-2018) 20-21 September 2018, Bulgaria
A P P L I C A T I O N O F D E E P L E A R N I N G A P P R O A C H I N S E Q U E N T I A L G A M E S
V anya M arkova, Ventseslav Shopov
Bulgarian Academy o f Sciences - Institute o f Robotics e-mails: markovavanya@yahoo.com, vkshopov@yahoo.com
Bulgaria
Abstract:
This article focuses on the application o f deep learning techniques in sequential games. The main hypothesis is that sequence to sequence learning approach is applicable and demonstrate better performance than classic reinforcement learning. So autonomous agents trough sequence to sequence approach are capable o f discovering good solutions to the problem at hand by learning in dynamic environment.Key words:
sequence to sequence, sequential games, autonomous agentsThis p ap e r is published in IE E E X plore D igital L ib ra ry and the inform ation can be accessed by URL:
https://ieeexplore.ieee.org/xpl/mostRecentIssue.isp7punumbeF8500053
Proceedings o f the International Conference on Information Technologies (InfoTech-2018) 20-21 September 2018, Bulgaria
S O L V I N G T H E G L O B A L T R A J E C T O R Y O P T I M I Z A T I O N P R O B L E M W I T H A R C H I V E - B A S E D D I F F E R E N T I A L
E V O L U T I O N
V ladim ir Stanovov, Shakhnaz Akhm edova, Eugene Semenkin
Reshetnev Siberian State University o f Science and Technology e-mails: vladimirstanovov@yandex.ru, eugenesemenkin@yandex.ru,
shahnaz@inbox. ru Russian Federation
Abstract:
The paper describes application o f differential evolution with modified mutation strategy to the global trajectory optimization problems. The problems are provided by the European Space Agency and represent trajectories o f several well- known spacecraft, namely, Cassini, Rosetta and Messenger. Using archive based differential evolution, global best solutions were found for these problems, and the best known solution was found for the Cassini mission.Key words:
Differential evolution, global trajectory optimization, spacecraft trajectory optimization.This p ap e r is published in IE E E X plore D igital L ib ra ry and the inform ation can be accessed by URL:
https://ieeexplore.ieee.org/xpl/mostRecentIssue.isp7punumbeF8500053
20-21 September 2018, BULGARIA 11 Proceedings o f the International Conference on Information Technologies (InfoTech-2018) 20-21 September 2018, Bulgaria
E D U C A T I O N A N D P R A C T I C A L K N O W L E D G E F O R P R O J E C T A N D R I S K M A N A G E M E N T I N I C T A R E A
Pl e n a r yRe p o r tSu m m a r y 1
V angel F ustik