Experimental Validation of Architectural Solutions

In this deliverable the experimental results carried out in four different contexts are reported. The first contribution concerns an experimental campaign performed using the AJECT (Attack inJECTion) tool able to emulate different types of attackers behaviour and to collect information on the effect of such attacks on the target system performance. This tool is also used to perform some of the experiments described in the fourth part of the deliverable. The second contribution concerns a complementary approach using honeypots to cap- ture traces of attacker behaviours, to then study and characterize them. Different kinds of honeypots were deployed in the described experiments: low-interaction and high-interaction ones, exposing different kinds of services and protocols (general purpose network services as well as SCADA specific ones). The third and fourth contribution refer to experiments conducted on some com- ponents of the CRUTIAL architecture, namely FOSEL (Filtering with the help of Overlay Security Layer), the CIS-CS (Communication Service) and the CIS-PS (Protection Service). The experiments have been performed with the aim of evaluating the effectiveness of the proposed components from the point of view of the dependability improvement they bring, as well as the performance overhead introduced by their implementation.Project co-funded by the European Commission within the Sixth Framework Programme (2002-2006

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kwartalni

Privacy-Preserving intrusion detection over network data

Effective protection against cyber-attacks requires constant monitoring and analysis of system data such as log files and network packets in an IT infrastructure, which may contain sensitive information. To this end, security operation centers (SOC) are established to detect, analyze, and respond to cyber-security incidents. Security officers at SOC are not necessarily trusted with handling the content of the sensitive and private information, especially in case when SOC services are outsourced as maintaining in-house expertise and capability in cyber-security is expensive. Therefore, an end-to-end security solution is needed for the system data. SOC often utilizes detection models either for known types of attacks or for an anomaly and applies them to the collected data to detect cyber-security incidents. The models are usually constructed from historical data that contains records pertaining to attacks and normal functioning of the IT infrastructure under monitoring; e.g., using machine learning techniques. SOC is also motivated to keep its models confidential for three reasons: i) to capitalize on the models that are its propriety expertise, ii) to protect its detection strategies against adversarial machine learning, in which intelligent and adaptive adversaries carefully manipulate their attack strategy to avoid detection, and iii) the model might have been trained on sensitive information, whereby revealing the model can violate certain laws and regulations. Therefore, detection models are also private. In this dissertation, we propose a scenario in which privacy of both system data and detection models is protected and information leakage is either prevented altogether or quantifiably decreased. Our main approach is to provide an end-to-end encryption for system data and detection models utilizing lattice-based cryptography that allows homomorphic operations over the encrypted data. Assuming that the detection models are previously obtained from training data by SOC, we apply the models to system data homomorphically, whereby the model is encrypted. We take advantage of three different machine learning algorithms to extract intrusion models by training historical data. Using different data sets (two recent data sets, and one outdated but widely used in the intrusion detection literature), the performance of each algorithm is evaluated via the following metrics: i) the time that takes to extract the rules, ii) the time that takes to apply the rules on data homomorphically, iii) the accuracy of the rules in detecting intrusions, and iv) the number of rules. Our experiments demonstrates that the proposed privacy-preserving intrusion detection system (IDS) is feasible in terms of execution times and reliable in terms of accurac

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Corrélation d’alertes : un outil plus efficace d’aide à la décision pour répondre aux intrusions

Security Information and Event Management (SIEM) systems provide the security analysts with a huge amount of alerts. Managing and analyzing such tremendous number of alerts is a challenging task for the security administrator. Alert correlation has been designed in order to alleviate this problem. Current alert correlation techniques provide the security administrator with a better description of the detected attack and a more concise view of the generated alerts. That way, it usually reduces the volume of alerts in order to support the administrator in tackling the amount of generated alerts. Unfortunately, none of these techniques consider neither the knowledge about the attacker’s behavior nor the enforcement functionalities and the defense perimeter of the protected network (Firewalls, Proxies, Intrusion Detection Systems, etc). It is still challenging to first improve the knowledge about the attacker and second to identify the policy enforcement mechanisms that are capable to process generated alerts. Several authors have proposed different alert correlation methods and techniques. Although these approaches support the administrator in processing the huge number of generated alerts, they remain limited since these solutions do not provide us with more information about the attackers’ behavior and the defender’s capability in reacting to detected attacks. In this dissertation, we propose two novel alert correlation approaches. The first approach, which we call honeypot-based alert correlation, is based on the use of knowledge about attackers collected through honeypots. The second approach, which we call enforcement-based alert correlation, is based on a policy enforcement and defender capabilities’ modelLes SIEMs (systèmes pour la Sécurité de l’Information et la Gestion des Événements) sont les cœurs des centres opérationnels de la sécurité. Ils corrèlent un nombre important d’événements en provenance de différents capteurs (anti-virus, pare-feux, systèmes de détection d’intrusion, etc), et offrent des vues synthétiques pour la gestion des menaces ainsi que des rapports de sécurité. La gestion et l’analyse de ce grand nombre d’alertes est une tâche difficile pour l’administrateur de sécurité. La corrélation d’alertes a été conçue afin de remédier à ce problème. Des solutions de corrélation ont été développées pour obtenir une vue plus concise des alertes générées et une meilleure description de l’attaque détectée. Elles permettent de réduire considérablement le volume des alertes remontées afin de soutenir l’administrateur dans le traitement de ce grand nombre d’alertes. Malheureusement, ces techniques ne prennent pas en compte les connaissances sur le comportement de l’attaquant, les fonctionnalités de l’application et le périmètre de défense du réseau supervisé (pare-feu, serveurs mandataires, Systèmes de détection d’intrusions, etc). Dans cette thèse, nous proposons deux nouvelles approches de corrélation d’alertes. La première approche que nous appelons corrélation d’alertes basée sur les pots de miel utilise des connaissances sur les attaquants recueillies par le biais des pots de miel. La deuxième approche de corrélation est basée sur une modélisation des points d’application de politique de sécurit

Enhancing the security of wireless sensor network based home automation systems

Home automation systems (HASs)seek to improve the quality of life for individuals through the automation of household devices. Recently, there has been a trend, in academia and industry, to research and develop low-cost Wireless Sensor Network (WSN) based HASs (Varchola et al. 2007). WSNs are designed to achieve a low-cost wireless networking solution, through the incorporation of limited processing, memory, and power resources. Consequently, providing secure and reliable remote access for resource limited WSNs, such as WSN based HASs, poses a significant challenge (Perrig et al. 2004). This thesis introduces the development of a hybrid communications approach to increase the resistance of WSN based HASs to remote DoS flooding attacks targeted against a third party. The approach is benchmarked against the dominant GHS remote access approach for WSN based HASs (Bergstrom et al. 2001), on a WSN based HAS test-bed, and shown to provide a minimum of a 58.28%, on average 59.85%, and a maximum of 61.45% increase in remote service availability during a DoS attack. Additionally, a virtual home incorporating a cryptographic based DoS detection algorithm, is developed to increase resistance to remote DoS flooding attacks targeted directly at WSN based HASs. The approach is benchmarked against D-WARD (Mirkovic 2003), the most effective DoS defence identified from the research, and shown to provide a minimum 84.70%, an average 91.13% and a maximum 95.6% reduction in packets loss on a WSN based HAS during a DoS flooding attack. Moreover, the approach is extended with the integration of a virtual home, hybrid communication approach, and a distributed denial of defence server to increase resistance to remote DoS attacks targeting the home gateway. The approach is again benchmarked against the D-WARD defence and shown to decrease the connection latency experienced by remote users by a minimum of 90.14%, an average 90.90%, and a maximum 91.88%.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Web感染型攻撃における潜在的特徴の解析法

早大学位記番号:新7789早稲田大

Decision support for choice of security solution: the Aspect-Oriented Risk Driven Development (AORDD)framework

In security assessment and management there is no single correct solution to the identified security problems or challenges. Instead there are only choices and tradeoffs. The main reason for this is that modern information systems and security critical information systems in particular must perform at the contracted or expected security level, make effective use of available resources and meet end-users' expectations. Balancing these needs while also fulfilling development, project and financial perspectives, such as budget and TTM constraints, mean that decision makers have to evaluate alternative security solutions.\ud \ud This work describes parts of an approach that supports decision makers in choosing one or a set of security solutions among alternatives. The approach is called the Aspect-Oriented Risk Driven Development (AORDD) framework, combines Aspect-Oriented Modeling (AOM) and Risk Driven Development (RDD) techniques and consists of the seven components: (1) An iterative AORDD process. (2) Security solution aspect repository. (3) Estimation repository to store experience from estimation of security risks and security solution variables involved in security solution decisions. (4) RDD annotation rules for security risk and security solution variable estimation. (5) The AORDD security solution trade-off analysis and trade-o¤ tool BBN topology. (6) Rule set for how to transfer RDD information from the annotated UML diagrams into the trad-off tool BBN topology. (7) Trust-based information aggregation schema to aggregate disparate information in the trade-o¤ tool BBN topology. This work focuses on components 5 and 7, which are the two core components in the AORDD framework