9 research outputs found

    AN ANALYSIS OF TRANSACTIONS IN E-PAYMENT SYSTEM USING MOBILE AGENTS

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    Commercial interactions between merchants and customers pose a significant concern as they are associated with a large volume of data and complex information, especially when there is a need for switching requirements. This paper presents an agent-based analysis of e-payment transactions with the switching operations. The model adopts an inter-bank transaction network and consists of a terminal point of sale (POI) and three essential players in e-payment: customer, bank (merchant), and the Switch. This study analyses the various payment interactions using agent technology. The agent coordinates movement while the negotiation protocol serves as an internal control of the payment agreements, while the interactive hosts are the platforms that determine the status of transactions. Each agent host is equipped with a Certification Authority (CA) to secure communication between the merchant and the customer. Different transactions that agents could make are examined with formal descriptions. The implementation is achieved in Jade and compares with the object serialization mechanism. The simulation results show higher quality adaptation of agent systems and evidence of agentisation of e-transaction with Switch.     &nbsp

    Robust and private computations of mobile agent alliances

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    Evidence-based Accountability Audits for Cloud Computing

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    Cloud computing is known for its on-demand service provisioning and has now become mainstream. Many businesses as well as individuals are using cloud services on a daily basis. There is a big variety of services that ranges from the provision of computing resources to services such as productivity suites and social networks. The nature of these services varies heavily in terms of what kind of information is being out-sourced to the cloud provider. Often, that data is sensitive, for instance when PII is being shared by an individual. Also, businesses that move (parts of) their processes to the cloud are actively participating in a major paradigm shift from having data on-premise to transfering data to a third-party provider. However, many new challenges come along with this trend, which are closely tied to the loss of control over data. When moving to the cloud, direct control over geographical storage location, who has access to it and how it is shared and processed is given up. Because of this loss of control, cloud customers have to trust cloud providers that they treat their data in an appropriate and responsible way. Cloud audits can be used to check how data has been processed in the cloud (i.e., by whom, for what purpose) and whether or not this happened in compliance with what has been defined in agreed-upon privacy and data storage, usage and maintenance (i.e., data handling) policies. This way, a cloud customer can regain some of the control he has given up by moving to the cloud. In this thesis, accountability audits are presented as a way to strengthen trust in cloud computing by providing assurance about the processing of data in the cloud according to data handling and privacy policies. In cloud accountability audits, various distributed evidence sources need to be considered. The research presented in this thesis discusses the use of various heterogeous evidence sources on all cloud layers. This way, a complete picture of the actual data handling practices that is based on hard facts can be presented to the cloud consumer. Furthermore, this strengthens transparency of data processing in the cloud, which can lead to improved trust in cloud providers, if they choose to adopt these mechanisms in order to assure their customers that their data is being handled according to their expectations. The system presented in this thesis enables continuous auditing of a cloud provider's adherence to data handling policies in an automated way that shortens audit intervals and that is based on evidence that is produced by cloud subsystems. An important aspect of many cloud offerings is the combination of multiple distinct cloud services that are offered by independent providers. Data is thereby freuqently exchanged between the cloud providers. This also includes trans-border flows of data, where one provider may be required to adhere to more strict data protection requirements than the others. The system presented in this thesis addresses such scenarios by enabling the collection of evidence at providers and evaluating it during audits. Securing evidence quickly becomes a challenge in the system design, when information that is needed for the audit is deemed sensitive or confidential. This means that securing the evidence at-rest as well as in-transit is of utmost importance, in order not to introduce a new liability by building an insecure data heap. This research presents the identification of security and privacy protection requirements alongside proposed solutions that enable the development of an architecture for secure, automated, policy-driven and evidence-based accountability audits

    Scalable discovery of networked data : Algorithms, Infrastructure, Applications

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    Harmelen, F.A.H. van [Promotor]Siebes, R.M. [Copromotor

    Security Audit Compliance for Cloud Computing

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    Cloud computing has grown largely over the past three years and is widely popular amongst today's IT landscape. In a comparative study between 250 IT decision makers of UK companies they said, that they already use cloud services for 61% of their systems. Cloud vendors promise "infinite scalability and resources" combined with on-demand access from everywhere. This lets cloud users quickly forget, that there is still a real IT infrastructure behind a cloud. Due to virtualization and multi-tenancy the complexity of these infrastructures is even increased compared to traditional data centers, while it is hidden from the user and outside of his control. This makes management of service provisioning, monitoring, backup, disaster recovery and especially security more complicated. Due to this, and a number of severe security incidents at commercial providers in recent years there is a growing lack of trust in cloud infrastructures. This thesis presents research on cloud security challenges and how they can be addressed by cloud security audits. Security requirements of an Infrastructure as a Service (IaaS) cloud are identified and it is shown how they differ from traditional data centres. To address cloud specific security challenges, a new cloud audit criteria catalogue is developed. Subsequently, a novel cloud security audit system gets developed, which provides a flexible audit architecture for frequently changing cloud infrastructures. It is based on lightweight software agents, which monitor key events in a cloud and trigger specific targeted security audits on demand - on a customer and a cloud provider perspective. To enable these concurrent cloud audits, a Cloud Audit Policy Language is developed and integrated into the audit architecture. Furthermore, to address advanced cloud specific security challenges, an anomaly detection system based on machine learning technology is developed. By creating cloud usage profiles, a continuous evaluation of events - customer specific as well as customer overspanning - helps to detect anomalies within an IaaS cloud. The feasibility of the research is presented as a prototype and its functionality is presented in three demonstrations. Results prove, that the developed cloud audit architecture is able to mitigate cloud specific security challenges

    Mitigating Stealthy Link Flooding DDoS Attacks Using SDN-Based Moving Target Defense

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    With the increasing diversity and complication of Distributed Denial-of-Service (DDoS) attacks, it has become extremely challenging to design a fully protected network. For instance, recently, a new type of attack called Stealthy Link Flooding Attack (SLFA) has been shown to cause critical network disconnection problems, where the attacker targets the communication links in the surrounding area of a server. The existing defense mechanisms for this type of attack are based on the detection of some unusual traffic patterns; however, this might be too late as some severe damage might already be done. These mechanisms also do not consider countermeasures during the reconnaissance phase of these attacks. Over the last few years, moving target defense (MTD) has received increasing attention from the research community. The idea is based on frequently changing the network configurations to make it much more difficult for the attackers to attack the network. In this dissertation, we investigate several novel frameworks based on MTD to defend against contemporary DDoS attacks. Specifically, we first introduce MTD against the data phase of SLFA, where the bots are sending data packets to target links. In this framework, we mitigate the traffic if the bandwidth of communication links exceeds the given threshold, and experimentally show that our method significantly alleviates the congestion. As a second work, we propose a framework that considers the reconnaissance phase of SLFA, where the attacker strives to discover critical communication links. We create virtual networks to deceive the attacker and provide forensic features. In our third work, we consider the legitimate network reconnaissance requests while keeping the attacker confused. To this end, we integrate cloud technologies as overlay networks to our system. We demonstrate that the developed mechanism preserves the security of the network information with negligible delays. Finally, we address the problem of identifying and potentially engaging with the attacker. We model the interaction between attackers and defenders into a game and derive a defense mechanism based on the equilibria of the game. We show that game-based mechanisms could provide similar protection against SLFAs like the extensive periodic MTD solution with significantly reduced overhead. The frameworks in this dissertation were verified with extensive experiments as well as with the theoretical analysis. The research in this dissertation has yielded several novel defense mechanisms that provide comprehensive protection against SLFA. Besides, we have shown that they can be integrated conveniently and efficiently to the current network infrastructure

    Counteracting phishing through HCI

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    Computer security is a very technical topic that is in many cases hard to grasp for the average user. Especially when using the Internet, the biggest network connecting computers globally together, security and safety are important. In many cases they can be achieved without the user's active participation: securely storing user and customer data on Internet servers is the task of the respective company or service provider, but there are also a lot of cases where the user is involved in the security process, especially when he or she is intentionally attacked. Socially engineered phishing attacks are such a security issue were users are directly attacked to reveal private data and credentials to an unauthorized attacker. These types of attacks are the main focus of the research presented within my thesis. I have a look at how these attacks can be counteracted by detecting them in the first place but also by mediating these detection results to the user. In prior research and development these two areas have most often been regarded separately, and new security measures were developed without taking the final step of interacting with the user into account. This interaction mainly means presenting the detection results and receiving final decisions from the user. As an overarching goal within this thesis I look at these two aspects united, stating the overall protection as the sum of detection and "user intervention". Within nine different research projects about phishing protection this thesis gives answers to ten different research questions in the areas of creating new phishing detectors (phishing detection) and providing usable user feedback for such systems (user intervention): The ten research questions cover five different topics in both areas from the definition of the respective topic over ways how to measure and enhance the areas to finally reasoning about what is making sense. The research questions have been chosen to cover the range of both areas and the interplay between them. They are mostly answered by developing and evaluating different prototypes built within the projects that cover a range of human-centered detection properties and evaluate how well these are suited for phishing detection. I also take a look at different possibilities for user intervention (e.g. how should a warning look like? should it be blocking or non-blocking or perhaps even something else?). As a major contribution I finally present a model that combines phishing detection and user intervention and propose development and evaluation recommendations for similar systems. The research results show that when developing security detectors that yield results being relevant for end users such a detector can only be successful in case the final user feedback already has been taken into account during the development process.Sicherheit rund um den Computer ist ein, für den durchschnittlichen Benutzer schwer zu verstehendes Thema. Besonders, wenn sich die Benutzer im Internet - dem größten Netzwerk unserer Zeit - bewegen, ist die technische und persönliche Sicherheit der Benutzer extrem wichtig. In vielen Fällen kann diese ohne das Zutun des Benutzers erreicht werden. Datensicherheit auf Servern zu garantieren obliegt den Dienstanbietern, ohne dass eine aktive Mithilfe des Benutzers notwendig ist. Es gibt allerdings auch viele Fälle, bei denen der Benutzer Teil des Sicherheitsprozesses ist, besonders dann, wenn er selbst ein Opfer von Attacken wird. Phishing Attacken sind dabei ein besonders wichtiges Beispiel, bei dem Angreifer versuchen durch soziale Manipulation an private Daten des Nutzers zu gelangen. Diese Art der Angriffe stehen im Fokus meiner vorliegenden Arbeit. Dabei werfe ich einen Blick darauf, wie solchen Attacken entgegen gewirkt werden kann, indem man sie nicht nur aufspürt, sondern auch das Ergebnis des Erkennungsprozesses dem Benutzer vermittelt. Die bisherige Forschung und Entwicklung betrachtete diese beiden Bereiche meistens getrennt. Dabei wurden Sicherheitsmechanismen entwickelt, ohne den finalen Schritt der Präsentation zum Benutzer hin einzubeziehen. Dies bezieht sich hauptsächlich auf die Präsentation der Ergebnisse um dann den Benutzer eine ordnungsgemäße Entscheidung treffen zu lassen. Als übergreifendes Ziel dieser Arbeit betrachte ich diese beiden Aspekte zusammen und postuliere, dass Benutzerschutz die Summe aus Problemdetektion und Benutzerintervention' ("user intervention") ist. Mit Hilfe von neun verschiedenen Forschungsprojekten über Phishingschutz beantworte ich in dieser Arbeit zehn Forschungsfragen über die Erstellung von Detektoren ("phishing detection") und das Bereitstellen benutzbaren Feedbacks für solche Systeme ("user intervention"). Die zehn verschiedenen Forschungsfragen decken dabei jeweils fünf verschiedene Bereiche ab. Diese Bereiche erstrecken sich von der Definition des entsprechenden Themas über Messmethoden und Verbesserungsmöglichkeiten bis hin zu Überlegungen über das Kosten-Nutzen-Verhältnis. Dabei wurden die Forschungsfragen so gewählt, dass sie die beiden Bereiche breit abdecken und auf die Abhängigkeiten zwischen beiden Bereichen eingegangen werden kann. Die Forschungsfragen werden hauptsächlich durch das Schaffen verschiedener Prototypen innerhalb der verschiedenen Projekte beantwortet um so einen großen Bereich benutzerzentrierter Erkennungsparameter abzudecken und auszuwerten wie gut diese für die Phishingerkennung geeignet sind. Außerdem habe ich mich mit den verschiedenen Möglichkeiten der Benutzerintervention befasst (z.B. Wie sollte eine Warnung aussehen? Sollte sie Benutzerinteraktion blockieren oder nicht?). Ein weiterer Hauptbeitrag ist schlussendlich die Präsentation eines Modells, dass die Entwicklung von Phishingerkennung und Benutzerinteraktionsmaßnahmen zusammenführt und anhand dessen dann Entwicklungs- und Analyseempfehlungen für ähnliche Systeme gegeben werden. Die Forschungsergebnisse zeigen, dass Detektoren im Rahmen von Computersicherheitsproblemen die eine Rolle für den Endnutzer spielen nur dann erfolgreich entwickelt werden können, wenn das endgültige Benutzerfeedback bereits in den Entwicklungsprozesses des Detektors einfließt

    Computer Aided Verification

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    The open access two-volume set LNCS 12224 and 12225 constitutes the refereed proceedings of the 32st International Conference on Computer Aided Verification, CAV 2020, held in Los Angeles, CA, USA, in July 2020.* The 43 full papers presented together with 18 tool papers and 4 case studies, were carefully reviewed and selected from 240 submissions. The papers were organized in the following topical sections: Part I: AI verification; blockchain and Security; Concurrency; hardware verification and decision procedures; and hybrid and dynamic systems. Part II: model checking; software verification; stochastic systems; and synthesis. *The conference was held virtually due to the COVID-19 pandemic
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