Building an Emulation Environment for Cyber Security Analyses of Complex Networked Systems

Computer networks are undergoing a phenomenal growth, driven by the rapidly increasing number of nodes constituting the networks. At the same time, the number of security threats on Internet and intranet networks is constantly growing, and the testing and experimentation of cyber defense solutions requires the availability of separate, test environments that best emulate the complexity of a real system. Such environments support the deployment and monitoring of complex mission-driven network scenarios, thus enabling the study of cyber defense strategies under real and controllable traffic and attack scenarios. In this paper, we propose a methodology that makes use of a combination of techniques of network and security assessment, and the use of cloud technologies to build an emulation environment with adjustable degree of affinity with respect to actual reference networks or planned systems. As a byproduct, starting from a specific study case, we collected a dataset consisting of complete network traces comprising benign and malicious traffic, which is feature-rich and publicly available

Teollisuusautomaatiojärjestelmien tunnistus ja luokittelu IP-verkoissa

Industrial Control Systems (ICS) are an essential part of the critical infrastructure of society and becoming increasingly vulnerable to cyber attacks performed over computer networks. The introduction of remote access connections combined with mistakes in automation system configurations expose ICSs to attacks coming from public Internet. Insufficient IT security policies and weaknesses in security features of automation systems increase the risk of a successful cyber attack considerably. In recent years the amount of observed cyber attacks has been on constant rise, signaling the need of new methods for finding and protecting vulnerable automation systems. So far, search engines for Internet connected devices, such as Shodan, have been a great asset in mapping the scale of the problem. In this theses methods are presented to identify and classify industrial control systems over IP based networking protocols. A great portion of protocols used in automation networks contain specific diagnostic requests for pulling identification information from a device. Port scanning methods combined with more elaborate service scan probes can be used to extract identifying data fields from an automation device. Also, a model for automated finding and reporting of vulnerable ICS devices is presented. A prototype software was created and tested with real ICS devices to demonstrate the viability of the model. The target set was gathered from Finnish devices directly connected to the public Internet. Initial results were promising as devices or systems were identified at 99% success ratio. A specially crafted identification ruleset and detection database was compiled to work with the prototype. However, a more comprehensive detection library of ICS device types is needed before the prototype is ready to be used in different environments. Also, other features which help to further assess the device purpose and system criticality would be some key improvements for the future versions of the prototype.Yhteiskunnan kriittiseen infrastruktuuriin kuuluvat teollisuusautomaatiojärjestelmät ovat yhä enemmissä määrin alttiita tietoverkkojen kautta tapahtuville kyberhyökkäyksille. Etähallintayhteyksien yleistyminen ja virheet järjestelmien konfiguraatioissa mahdollistavat hyökkäykset jopa suoraa Internetistä käsin. Puutteelliset tietoturvakäytännöt ja teollisuusautomaatiojärjestelmien heikot suojaukset lisäävät onnistuneen kyberhyökkäyksen riskiä huomattavasti. Viime vuosina kyberhyökkäysten määrä maailmalla on ollut jatkuvassa kasvussa ja siksi tarve uusille menetelmille haavoittuvaisten järjestelmien löytämiseksi ja suojaamiseksi on olemassa. Internetiin kytkeytyneiden laitteiden hakukoneet, kuten Shodan, ovat olleet suurena apuna ongelman laajuuden kartoittamisessa. Tässä työssä esitellään menetelmiä teollisuusautomaatiojärjestelmien tunnistamiseksi ja luokittelemiseksi käyttäen IP-pohjaisia tietoliikenneprotokollia. Suuri osa automaatioverkoissa käytetyistä protokollista sisältää erityisiä diagnostiikkakutsuja laitteen tunnistetietojen selvittämiseksi. Porttiskannauksella ja tarkemmalla palvelukohtaisella skannauksella laitteesta voidaan saada yksilöivää tunnistetietoa. Työssä esitellään myös malli automaattiselle haavoittuvaisten teollisuusautomaatiojärjestelmien löytämiselle ja raportoimiselle. Mallin tueksi esitellään ohjelmistoprototyyppi, jolla mallin toimivuutta testattiin käyttäen testijoukkona oikeita Suomesta löytyviä, julkiseen Internetiin kytkeytyneitä teollisuusautomaatiolaitteita. Prototyypin alustavat tulokset olivat lupaavia: laitteille tai järjestelmille kyettiin antamaan jokin tunniste 99 % tapauksista käyttäen luokittelussa apuna prototyypille luotua tunnistekirjastoa. Ohjelmiston yleisempi käyttö vaatii kuitenkin kattavamman automaatiolaitteiden tunnistekirjaston luomista sekä prototyypin jatkokehitystä: tehokkaampi tunnistaminen edellyttää automaatiojärjestelmien toimintaympäristön ja kriittisyyden tarkempaa analysointia

D-FRI-Honeypot:A Secure Sting Operation for Hacking the Hackers Using Dynamic Fuzzy Rule Interpolation

As active network defence systems, honeypots are commonly used as a decoy to inspect attackers and their attack tactics in order to improve the cybersecurity infrastructure of an organisation. A honeypot may be successful provided that it disguises its identity. However, cyberattackers continuously endeavour to discover honeypots for evading any deception and bolstering their attacks. Active fingerprinting attack is one such technique that may be used to discover honeypots by sending specially designed traffic. Preventing a fingerprinting attack is possible but doing that may hinder the process of dealing with the attackers, counteracting the purpose of a honeypot. Instead, detecting an attempted fingerprinting attack in real-time can enhance a honeypot’s capability, uninterruptedly managing any immediate consequences and preventing the honeypot being identified. Nevertheless, it is difficult to detect and predict an attempted fingerprinting attack due to the challenge of isolating it from other similar attacks, particularly when imprecise observations are involved in the monitoring of the traffic. Dynamic fuzzy rule interpolation (D-FRI) enables an adaptive approach for effective reasoning with such situations by exploiting the best of both inference and interpolation. The dynamic rules produced by D-FRI facilitate approximate reasoning with perpetual changes that often occur in this type of application, where dynamic rules are required to cover new network conditions. This paper proposes a D-FRI-Honeypot, an enhanced honeypot running D-FRI framework in conjunction with Principal Component Analysis, to detect and predict an attempted fingerprinting attack on honeypots. This D-FRI-Honeypot works with a sparse rule base but is able to detect active fingerprinting attacks when it does not find any matching rules. Also, it learns from current network conditions and offers a dynamically enriched rule base to support more precise detection. This D-FRI-Honeypot is tested against five popular fingerprinting tools (namely, Nmap, Xprobe2, NetScanTools Pro, SinFP3 and Nessus), to demonstrate its successful applications

Response time optimization for vulnerability management system by combining the benchmarking and scenario planning models

The growth of information and communication technology has made the internet network have many users. On the other side, this increases cybercrime and its risks. One of the main attack targets is network weakness. Therefore, cyber security is required, which first does a network scan to stop the attack. Points of vulnerability on the network can be discovered using scanning techniques. Furthermore, mitigation or recovery measures can be implemented. However, it needs a short response time and high accuracy while scanning to reduce the level of damage caused by cyber-attacks. In this paper, the proposed method improves the performance of a vulnerability management system based on network and port scanning by combining the benchmarking and scenario planning models. On a network scanning to discover open ports on a subnet, Masscan can achieve response times of less than 2 seconds, and on scenario planning for detection on a single host by Nmap can reach less than 4 seconds. It was combining both models obtained an adequate optimization response time. The total response time is less than 6 seconds

The Vulnerability Assessment and Penetration Testing of Two Networks

Vulnerability assessments and penetration testing are two approaches available for use by internet security practitioners to determine the security posture of information networks. By assessing network vulnerabilities and attempting to exploit found vulnerabilities through penetration testing security professionals are able to evaluate the effectiveness of their network defenses by identifying defense weaknesses, affirming the defense mechanisms in place, or some combination of the two. This project is a discussion of the methods and tools used during the vulnerability assessment and penetration testing, and the respective test results of two varied and unique networks. The assessment and testing of the first network occurred from an internal perspective, while the assessment and testing of the second occurred from an external perspective. While the tools and methodologies used across both networks were consistent, the test results differed significantly. The paper concludes with a series of recommendations regarding practical methods and tools that may prove useful to anyone interested in network security, and vulnerability assessments and penetration testing in particular

Improving the National Cyber-security by Finding Vulnerable Industrial Control Systems from the Internet

Teollisuusautomaatiojärjestelmiä, joita käytetään muun muassa voimantuotannon, sähkönjakelun ja jätevedenpuhdistuksen järjestelmissä, voidaan löytää julkisesta Internetistä. Tarve etähallinnalle ja keskittämiselle, sekä tuotteiden huono suunnittelu ja virheet järjestelmien käyttöönotossa, ovat altistaneet automaatiojärjestelmiä kenen tahansa ulottuville. Yhteiskunnalle tärkeiden kriittisen infrastruktuuriin kuuluvien järjestelmien turvalliseksi saattaminen on tärkeää kansalliselle kyberturvallisuudelle: ongelmat kriittisessä infrastruktuurissa voivat aiheuttaa voimakkaita häiriöitä eri puolilla yhteiskuntaa. Viime vuosina on havaittu kasvava määrä kyberhyökkäyksiä. Sekä rikolliset, että valtiolliset toimijat kehittävät kyberaseita ja myös teollisuusautomaatiojärjestelmiin on kohdistettu hyökkäyksiä. Vuonna 2010 Stuxnet haittaohjelma onnistui tunkeutumaan iranilaisen ydinpolttoaineenrikastamon järjestelmiin ja aiheuttamaan mittavaa fyysistä tuhoa. Tässä työssä esitellään konsepti, jonka avulla voidaan automaattisesti löytää haavoittuvia teollisuusautomaatiojärjestelmiä, ja raportoida löydökset viranomaisille jatkotoimenpiteitä varten. Työssä esitellään myös prototyyppi, jolla testattiin konseptin toimivuutta oikeilla suomalaisilla järjestelmillä Internetin yli: sormenjälkitietokannan ja porttiskannauksen avulla 2913 IP-osoitteesta löydettiin 91 mahdollista teollisuusautomaatiolaitetta. Epäiltyjä teollisuusautomaatiojärjestelmiä pystytään löytämään Internetistä, mutta löydettyjen järjestelmien kriittisyyden ja tärkeyden arvionti ilman tunkeutumista kohteeseen on vaikeaa. Konseptia tehostaisi huomattavasti automaattinen tietoturva-auditointi, jolla tärkeimmät ja haavoittuvaisimmat kohteet voitaisiin paikallistaa ja poistaa näkyviltä nopeasti. Auditointi ilman järjestelmien omistajien lupaa vaatisi kuitenkin muutoksia lainsäädäntöön.Industrial control systems (ICS), which are used to control critical elements of the society's maintenance such as power generation and electricity distribution, are exposed to the Internet as a result of insecure design, and installation faults. Securing critical industrial systems is important for national cyber-security; malfunctioning elements in the critical infrastructure can quickly cascade into wide range of problems in the society. In the recent years increasing amount of cyber-attacks have been observed, and nations and criminals are developing offensive cyber-capabilities; industrial systems are also targeted as was seen with the Stuxnet-malware in 2010 causing havoc in an Iranian uranium enrichment facility. In this thesis a concept is presented to automatically find and evaluate exposed ICSs and report vulnerable devices to authorities for remediation. A prototype of the concept is built to prove the viability of the concept and to get data from port scanning real ICS devices in the Internet. With the prototype, 91 ICS devices were found out of the assigned 2913 IP addresses. Traffic volume produced by the scanner was insignificant compared to overall Finnish Internet traffic. The concept, called KATSE, is viable but not without challenges: ICS devices can definitely be identified from the Internet but analyzing the actual importance and purpose of the devices is difficult. Currently the Finnish legislation does not allow system intrusions or unauthorized security auditing even by authorities. Automated security auditing for the found devices would be useful to find the most vulnerable devices first but such auditing would require a change in legislation

System for Continuous Collection of Contextual Information for Network Security Management and Incident Handling

In this paper, we describe a system for the continuous collection of data for the needs of network security management. When a cybersecurity incident occurs in the network, the contextual information on the involved assets facilitates estimating the severity and impact of the incident and selecting an appropriate incident response. We propose a system based on the combination of active and passive network measurements and the correlation of the data with third-party systems. The system enumerates devices and services in the network and their vulnerabilities via fingerprinting of operating systems and applications. Further, the system pairs the hosts in the network with contacts on responsible administrators and highlights critical infrastructure and its dependencies. The system concentrates all the information required for common incident handling procedures and aims to speed up incident response, reduce the time spent on the manual investigation, and prevent errors caused by negligence or lack of information

Cyber Attack Surface Mapping For Offensive Security Testing

Security testing consists of automated processes, like Dynamic Application Security Testing (DAST) and Static Application Security Testing (SAST), as well as manual offensive security testing, like Penetration Testing and Red Teaming. This nonautomated testing is frequently time-constrained and difficult to scale. Previous literature suggests that most research is spent in support of improving fully automated processes or in finding specific vulnerabilities, with little time spent improving the interpretation of the scanned attack surface critical to nonautomated testing. In this work, agglomerative hierarchical clustering is used to compress the Internet-facing hosts of 13 representative companies as collected by the Shodan search engine, resulting in an average 89% reduction in attack surface complexity. The work is then extended to map network services and also analyze the characteristics of the Log4Shell security vulnerability and its impact on attack surface mapping. The results highlighted outliers indicative of possible anti-patterns as well as opportunities to improve how testers and tools map the web attack surface. Ultimately the work is extended to compress web attack surfaces based on security relevant features, demonstrating via accuracy measurements not only that this compression is feasible but can also be automated. In the process a framework is created which could be extended in future work to compress other attack surfaces, including physical structures/campuses for physical security testing and even humans for social engineering tests

Securing Distributed Computer Systems Using an Advanced Sophisticated Hybrid Honeypot Technology

Computer system security is the fastest developing segment in information technology. The conventional approach to system security is mostly aimed at protecting the system, while current trends are focusing on more aggressive forms of protection against potential attackers and intruders. One of the forms of protection is also the application of advanced technology based on the principle of baits - honeypots. Honeypots are specialized devices aimed at slowing down or diverting the attention of attackers from the critical system resources to allow future examination of the methods and tools used by the attackers. Currently, most honeypots are being configured and managed statically. This paper deals with the design of a sophisticated hybrid honeypot and its properties having in mind enhancing computer system security. The architecture of a sophisticated hybrid honeypot is represented by a single device capable of adapting to a constantly changing environment by using active and passive scanning techniques, which mitigate the disadvantages of low-interaction and high-interaction honeypots. The low-interaction honeypot serves as a proxy for multiple IP addresses and filters out traffic beyond concern, while the high-interaction honeypot provides an optimum level of interaction. The proposed architecture employing the prototype of a hybrid honeypot featuring autonomous operation should represent a security mechanism minimizing the disadvantages of intrusion detection systems and can be used as a solution to increase the security of a distributed computer system rapidly, both autonomously and in real-time