Person:
Izal Azcárate, Mikel

person.page.identifierURI

https://academica-e.unavarra.es/handle/2454/49304

Last Name

Izal Azcárate

First Name

Mikel

person.page.departamento

Ingeniería Eléctrica, Electrónica y de Comunicación

person.page.instituteName

ISC. Institute of Smart Cities

ORCID

0000-0002-2770-912X

person.page.upna

2083

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Now showing 1 - 10 of 20

Open Access
Computation of traffic time series for large populations of IoT devices
(MDPI, 2018) Izal Azcárate, Mikel; Morató Osés, Daniel; Magaña Lizarrondo, Eduardo; García-Jiménez, Santiago; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación
En este artículo se estudian las tecnicas para clasificar paquetes de tráfico de red en múltiples clases orientadas a la realización de series temporales de tráfico en escenarios de un elevado numero de clases como pueden ser los proveedores de red para dispositivos IoT. Se muestra que usando técnicas basadas en DStries se pueden monitorizar en tiempo real redes con decenas de miles de dispositivos.
Open Access
Ransomware encrypted your files but you restored them from network traffic
(IEEE, 2019) Berrueta Irigoyen, Eduardo; Morató Osés, Daniel; Magaña Lizarrondo, Eduardo; Izal Azcárate, Mikel; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación
In a scenario where user files are stored in a network shared volume, a single computer infected by ransomware could encrypt the whole set of shared files, with a large impact on user productivity. On the other hand, medium and large companies maintain hardware or software probes that monitor the traffic in critical network links, in order to evaluate service performance, detect security breaches, account for network or service usage, etc. In this paper we suggest using the monitoring capabilities in one of these tools in order to keep a trace of the traffic between the users and the file server. Once the ransomware is detected, the lost files can be recovered from the traffic trace. This includes any user modifications posterior to the last snapshot of periodic backups. The paper explains the problems faced by the monitoring tool, which is neither the client nor the server of the file sharing operations. It also describes the data structures in order to process the actions of users that could be simultaneously working on the same file. A proof of concept software implementation was capable of successfully recovering the files encrypted by 18 different ransomware families.
Open Access
A proposal of burst cloning for video quality improvement in optical burst switching networks
(2013) Espina Antolín, Félix; Morató Osés, Daniel; Izal Azcárate, Mikel; Magaña Lizarrondo, Eduardo; Automática y Computación; Automatika eta Konputazioa
Open Access
A survey on detection techniques for cryptographic ransomware
(IEEE, 2019) Berrueta Irigoyen, Eduardo; Morató Osés, Daniel; Magaña Lizarrondo, Eduardo; Izal Azcárate, Mikel; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación
Crypto-ransomware is a type of malware that encrypts user files, deletes the original data, and asks for a ransom to recover the hijacked documents. It is a cyber threat that targets both companies and residential users, and has spread in recent years because of its lucrative results. Several articles have presented classifications of ransomware families and their typical behaviour. These insights have stimulated the creation of detection techniques for antivirus and firewall software. However, because the ransomware scene evolves quickly and aggressively, these studies quickly become outdated. In this study, we surveyed the detection techniques that the research community has developed in recent years. We compared the different approaches and classified the algorithms based on the input data they obtain from ransomware actions, and the decision procedures they use to reach a classification decision between benign or malign applications. This is a detailed survey that focuses on detection algorithms, compared to most previous studies that offer a survey of ransomware families or isolated proposals of detection algorithms. We also compared the results of these proposals.
Open Access
Ingress traffic classification versus aggregation in video over OBS networks
(2010) Izal Azcárate, Mikel; Espina Antolín, Félix; Morató Osés, Daniel; Magaña Lizarrondo, Eduardo; Automática y Computación; Automatika eta Konputazioa
Optical Burst Switched (OBS) networks may become a backbone technology for video-on-demand providers. This work addresses the problem of dimensioning the access link of an ingress node to the optical core network in a video over OBS scenario. A video-ondemand provider using an OBS transport network will have to deliver traffic to a set of egress destinations. A large part of this traffic would be composed of video streaming traffic. However, in a real network there would be also a fraction of non video traffic related to non video services. This work studies the decision whether it is better to gather all traffic to the same destination in a joint burst assembler or separate video and general data traffic on different burs assemblers. The later may increase burst blocking probability but also allow for better tuning of OBS parameters that help improve video reception quality. Result show that this tuning of parameters is not enough to compensate the drop probability increase and thus it is better to aggregate video and general data traffic.
Open Access
ETOMIC advanced network monitoring system for future Internet experimentation
(Springer-Verlag Berlin Heidelberg, 2010) Csabai, István; Fekete, Attila; Hága, Péter; Hullár, Béla; Kurucz, Gábor; Laki, Sándor; Mátray, Péter; Stéger, József; Vattay, Gábor; Espina Antolín, Félix; García-Jiménez, Santiago; Izal Azcárate, Mikel; Magaña Lizarrondo, Eduardo; Morató Osés, Daniel; Aracil Rico, Javier; Gómez, Francisco; González, Iván; López Buedo, Sergio; Moreno, Víctor; Ramos, Javier; Automática y Computación; Automatika eta Konputazioa
ETOMIC is a network traffic measurement platform with high precision GPS-synchronized monitoring nodes. The infrastructure is publicly available to the network research community, supporting advanced experimental techniques by providing high precision hardware equipments and a Central Management System. Researchers can deploy their own active measurement codes to perform experiments on the public Internet. Recently, the functionalities of the original system were significantly extended and new generation measurement nodes were deployed. The system now also includes well structured data repositories to archive and share raw and evaluated data. These features make ETOMIC as one of the experimental facilities that support the design, development and validation of novel experimental techniques for the future Internet. In this paper we focus on the improved capabilities of the management system, the recent extensions of the node architecture and the accompanying database solutions.
Open Access
Ransomware early detection by the analysis of file sharing traffic
(Elsevier, 2018) Morató Osés, Daniel; Berrueta Irigoyen, Eduardo; Magaña Lizarrondo, Eduardo; Izal Azcárate, Mikel; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de Comunicación
Crypto ransomware is a type of malware that locks access to user files by encrypting them and demands a ransom in order to obtain the decryption key. This type of malware has become a serious threat for most enterprises. In those cases where the infected computer has access to documents in network shared volumes, a single host can lock access to documents across several departments in the company. We propose an algorithm that can detect ransomware action and prevent further activity over shared documents. The algorithm is based on the analysis of passively monitored traffic by a network probe. 19 different ransomware families were used for testing the algorithm in action. The results show that it can detect ransomware activity in less than 20 s, before more than 10 files are lost. Recovery of even those files was also possible because their content was stored in the traffic monitored by the network probe. Several days of traffic from real corporate networks were used to validate a low rate of false alarms. This paper offers also analytical models for the probability of early detection and the probability of false alarms for an arbitrarily large population of users.
Open Access
Pamplona-traceroute: topology discovery and alias resolution to build router level Internet maps
(IEEE, 2013) García-Jiménez, Santiago; Magaña Lizarrondo, Eduardo; Morató Osés, Daniel; Izal Azcárate, Mikel; Automática y Computación; Automatika eta Konputazioa
An Internet topology map at the router level not only needs to discover IP addresses in Internet paths (traceroute) but also needs to identify IP addresses belonging to the same router (IP aliases). Both processes, discovery and IP alias resolution, have traditionally been independent tasks. In this paper, a new tool called Pamplona-traceroute is proposed to improve upon current results in a state of the art for Internet topology construction at the router level. Indirect probing using TTLscoped UDP packets, usually present in the discovery phases, is reused in IP alias resolution phases, providing high identification rates, especially in access routers.
Open Access
A popularity-aware method for discovering server IP addresses related to websites
(IEEE, 2013) Torres García, Luis Miguel; Magaña Lizarrondo, Eduardo; Izal Azcárate, Mikel; Morató Osés, Daniel; Automática y Computación; Automatika eta Konputazioa
The complexity of web traffic has grown in the past years as websites evolve and new services are provided over the HTTP protocol. When accessing a website, multiple connections to different servers are opened and it is usually difficult to distinguish which servers are related to which sites. However, this information is useful from the perspective of security and accounting and can also help to label web traffic and use it as ground truth for traffic classification systems. In this paper we present a method to discover server IP addresses related to specific websites in a traffic trace. Our method uses NetFlow-type records which makes it scalable and impervious to encryption of packet payloads. It is, moreover, popularity-aware in the sense that it takes into consideration the differences in the number of accesses to each site in order to provide a better identification of servers. The method can be used to gather data from a group of interesting websites or, by applying it to a representative set of websites, it can label a sizeable number of connections in a packet trace.
Open Access
TBDClust: time-based density clustering to enable free browsing of sites in pay-per-use mobile Internet providers
(Elsevier, 2017) Torres García, Luis Miguel; Magaña Lizarrondo, Eduardo; Morató Osés, Daniel; García-Jiménez, Santiago; Izal Azcárate, Mikel; Automatika eta Konputazioa; Institute of Smart Cities - ISC; Automática y Computación
The World Wide Web has evolved rapidly, incorporating new content types and becoming more dynamic. The contents from a website can be distributed between several servers, and as a consequence, web traffic has become increasingly complex. From a network traffic perspective, it can be difficult to ascertain which websites are being visited by a user, let alone which part of the user's traffic each website is responsible for. In this paper we present a method for identifying the TCP connections involved in the same full webpage download without the need of deep packet inspection. This identification is needed for example to enable free browsing of specific websites in a pay per use mobile Internet access. It could be not only for third party promoted websites but also portals to gubernamental or medical emergency websites. The proposal is based on a modification of the DBSCAN clustering algorithm to work online and over one-dimensional sorted data. In order to validate our results we use both real traffic and packet captures from a controlled environment. The proposal achieves excellent results in consistency (99%) and completeness (92%), meaning that its error margin identifying the webpage downloads is minimal.