periodic path changes in ripe atlas

Large-scale data sets of the Internet measurements are commonly used by researchers and operators for investigating Internet performance or for tackling network issues. Looking at sequences of traceroutes in such data sets, it is common to observe paths that change over time. We are interested in verifying if there are periodic phenomena affecting such path changes and, if yes, in determining if they depend on artifacts of the used data set or on topology changes of the network. For this purpose, we devise a novel algorithm for detecting periodicities in sequences of traceroutes. Then, we exploit the algorithm for analyzing the traceroutes produced by the RIPE Atlas, a popular public measurement platform. We study and report the features of the found periodicities and some of their causes. We found that: 1) a surprisingly large percentage of the traceroutes exhibit a periodic behavior; 2) a large number of periodicities depend on the RIPE Atlas platform itself; and 3) a smaller amount is related to the MPLS and load balancing

Ethercat tabanlı bir scada sisteminde kural ve makine öğrenmesine dayalı saldırı ve anomali tespiti

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Endüstriyel kontrol sistemleri (EKS) bulundukları konum ve bileşenleri bakımından kritik altyapıya sahip sistemler olup, bilişim teknolojilerinden (BT) bağımsız olarak uygulama alanına göre kendilerine ait kabul ve işleyişleri bulunmaktadır. Bu sistemler, günümüzde otomasyon hiyerarşisinde yer alan seviyeler arası yatay ve dikey entegrasyonun tek bir protokolle sağlanması fikrinden yola çıkılarak Ethernet ile de adapte edilmiş durumdadır. Dolayısıyla EKS'ler hem doğalarından hem de Ethernet üzerinden bilişim teknolojilerinin sunduğu hizmetlerin içerisine dahil edildiklerinden dolayı siber saldırılara karşı tehdit altındadır. Bu durum, çoğunlukla iletişim altyapısı üzerinden gelen saldırıların tespiti için özelinde EKS çözümlerini gerektirir. Bu çalışmada, otomasyon uygulamalarında yaygın bir kullanıma sahip olan, Ethernet tabanlı gerçek zamanlı EtherCAT protokolü için Snort saldırı tespit sistemi üzerinde bilinen ve bilinmeyen saldırıları tespit eden bütüncül bir yapı ve makine öğrenmesi teknikleriyle anomali tespiti olmak üzere ikisi kural biri anomali tespitine dayanan 3 farklı yaklaşım sunulmaktadır. Sistem, geliştirilen önişlemci yardımıyla, bilinen saldırılar için güvenli düğüm yaklaşımı, bilinmeyen saldırılar için ise saha veri yolu tekrar periyodunu tespit ederek istatistiksel tekniklerle ve özgün çözümlerle kural tabanlı olarak saldırı tespitini kapsamaktadır. Tespitler bir günlükleme ve izleme yapısı olan ELK yığını üzerinde kullanıcıya sunulmaktadır. Ayrıca, yine bilinmeyen saldırılar için oluşturulan su seviye kontrol otomasyonu test ortamı üzerinde olaylar gerçeklenerek bir veri seti hazırlanması ve çeşitli öğrenme tekniklerinin veri seti üzerinde anomali tespitini kapsamaktadır. Bilinmeyen saldırıların tespiti kapsamında uygulanan periyot tespitinin %95-%99 doğrulukla yapılabildiği görülmüştür. Önerilen sistem üzerinde ise MAC aldatma, veri enjeksiyonu, DoS, köle saldırıları gibi ataklar gerçeklenmiş, alarm ve günlüklemeler incelendiğinde saldırıların başarıyla tespit edildiği görülmüştür. Ayrıca, k-NN ve SVM GA tekniklerinin olay tespitinde başarılı sonuç verdikleri belirlenmiştir.Industrial control systems (ICS) are critical infrastructures in terms of their location and components. These systems have their own features and operation related to the application field independent from the information technologies (IT). They are also adapted with the Ethernet technologies based on the idea of providing horizontal and vertical integration between the levels in the automation hierarchy with a single protocol. Therefore, ICSs are threatened by cyber attacks, due to both their nature and support of IT services through Ethernet. This risk requires ICS specific solutions to detect and prevent attacks which use communication infrastructure. In this study, two rule based which detect known and unknown attacks on the Snort system and one anomaly based which uses machine learning techniques, in total of three different approaches were presented as a holistic structure for Ethernet based real-time EtherCAT protocol, which is widely used in automation applications. In the case of rule based intrusion detection, the EtherCAT preprocessor was proposed, which applies the trust node approach for known attacks, and identifies the field bus repetition period for unknown attacks, with statistical techniques and novel solutions. The findings were presented to the user on the ELK stack, which is a logging and monitoring structure. For anomaly based intrusion detection, the water level control automation testbed was developed, a dataset was prepared by generating events and various machine learning techniques were applied on the dataset. According to the findings obtained in this research, it was concluded that the period determination which was applied within the scope of unknown attack detection can be made with 95% - 99% accuracy. When the logs and alerts of the realized MAC spoofing, data injection, DoS, slave attacks were investigated, it was seen that the attacks were able to be detected successfully. For anomaly detection part of the study, k-NN and SVM GA techniques were found to be successful in detecting events

Anomaly detection in SCADA systems: a network based approach

Supervisory Control and Data Acquisition (SCADA) networks are commonly deployed to aid the operation of large industrial facilities, such as water treatment facilities. Historically, these networks were composed by special-purpose embedded devices communicating through proprietary protocols. However, modern deployments commonly make use of commercial off-the-shelf devices and standard communication protocols, such as TCP/IP. Furthermore, these networks are becoming increasingly interconnected, allowing communication with corporate networks and even the Internet. As a result, SCADA networks become vulnerable to cyber attacks, being exposed to the same threats that plague traditional IT systems.\ud \ud In our view, measurements play an essential role in validating results in network research; therefore, our first objective is to understand how SCADA networks are utilized in practice. To this end, we provide the first comprehensive analysis of real-world SCADA traffic. We analyze five network packet traces collected at four different critical infrastructures: two water treatment facilities, one gas utility, and one electricity and gas utility. We show, for instance, that exiting network traffic models developed for traditional IT networks cannot be directly applied to SCADA network traffic. \ud \ud We also confirm two SCADA traffic characteristics: the stable connection matrix and the traffic periodicity, and propose two intrusion detection approaches that exploit them. In order to exploit the stable connection matrix, we investigate the use of whitelists at the flow level. We show that flow whitelists have a manageable size, considering the number of hosts in the network, and that it is possible to overcome the main sources of instability in the whitelists. In order to exploit the traffic periodicity, we focus our attention to connections used to retrieve data from devices in the field network. We propose PeriodAnalyzer, an approach that uses deep packet inspection to automatically identify the different messages and the frequency at which they are issued. Once such normal behavior is learned, PeriodAnalyzer can be used to detect data injection and Denial of Service attacks