2,687 research outputs found

    Provenance Threat Modeling

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    Provenance systems are used to capture history metadata, applications include ownership attribution and determining the quality of a particular data set. Provenance systems are also used for debugging, process improvement, understanding data proof of ownership, certification of validity, etc. The provenance of data includes information about the processes and source data that leads to the current representation. In this paper we study the security risks provenance systems might be exposed to and recommend security solutions to better protect the provenance information.Comment: 4 pages, 1 figure, conferenc

    Security and computer forensics in web engineering education

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    The integration of security and forensics into Web Engineering curricula is imperative! Poor security in web-based applications is continuing to cost organizations millions and the losses are still increasing annually. Security is frequently taught as a stand-alone course, assuming that security can be 'bolted on' to a web application at some point. Security issues must be integrated into Web Engineering processes right from the beginning to create secure solutions and therefore security should be an integral part of a Web Engineering curriculum. One aspect of Computer forensics investigates failures in security. Hence, students should be aware of the issues in forensics and how to respond when security failures occur; collecting evidence is particularly difficult for Web-based applications

    Trustee: A Trust Management System for Fog-enabled Cyber Physical Systems

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    In this paper, we propose a lightweight trust management system (TMS) for fog-enabled cyber physical systems (Fog-CPS). Trust computation is based on multi-factor and multi-dimensional parameters, and formulated as a statistical regression problem which is solved by employing random forest regression model. Additionally, as the Fog-CPS systems could be deployed in open and unprotected environments, the CPS devices and fog nodes are vulnerable to numerous attacks namely, collusion, self-promotion, badmouthing, ballot-stuffing, and opportunistic service. The compromised entities can impact the accuracy of trust computation model by increasing/decreasing the trust of other nodes. These challenges are addressed by designing a generic trust credibility model which can countermeasures the compromise of both CPS devices and fog nodes. The credibility of each newly computed trust value is evaluated and subsequently adjusted by correlating it with a standard deviation threshold. The standard deviation is quantified by computing the trust in two configurations of hostile environments and subsequently comparing it with the trust value in a legitimate/normal environment. Our results demonstrate that credibility model successfully countermeasures the malicious behaviour of all Fog-CPS entities i.e. CPS devices and fog nodes. The multi-factor trust assessment and credibility evaluation enable accurate and precise trust computation and guarantee a dependable Fog-CPS system

    A Forensically Sound Adversary Model for Mobile Devices

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    In this paper, we propose an adversary model to facilitate forensic investigations of mobile devices (e.g. Android, iOS and Windows smartphones) that can be readily adapted to the latest mobile device technologies. This is essential given the ongoing and rapidly changing nature of mobile device technologies. An integral principle and significant constraint upon forensic practitioners is that of forensic soundness. Our adversary model specifically considers and integrates the constraints of forensic soundness on the adversary, in our case, a forensic practitioner. One construction of the adversary model is an evidence collection and analysis methodology for Android devices. Using the methodology with six popular cloud apps, we were successful in extracting various information of forensic interest in both the external and internal storage of the mobile device

    IPCFA: A Methodology for Acquiring Forensically-Sound Digital Evidence in the Realm of IAAS Public Cloud Deployments

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    Cybercrimes and digital security breaches are on the rise: savvy businesses and organizations of all sizes must ready themselves for the worst. Cloud computing has become the new normal, opening even more doors for cybercriminals to commit crimes that are not easily traceable. The fast pace of technology adoption exceeds the speed by which the cybersecurity community and law enforcement agencies (LEAs) can invent countermeasures to investigate and prosecute such criminals. While presenting defensible digital evidence in courts of law is already complex, it gets more complicated if the crime is tied to public cloud computing, where storage, network, and computing resources are shared and dispersed over multiple geographical areas. Investigating such crimes involves collecting evidence data from the public cloud that is court-sound. Digital evidence court admissibility in the U.S. is governed predominantly by the Federal Rules of Evidence and Federal Rules of Civil Procedures. Evidence authenticity can be challenged by the Daubert test, which evaluates the forensic process that took place to generate the presented evidence. Existing digital forensics models, methodologies, and processes have not adequately addressed crimes that take place in the public cloud. It was only in late 2020 that the Scientific Working Group on Digital Evidence (SWGDE) published a document that shed light on best practices for collecting evidence from cloud providers. Yet SWGDE’s publication does not address the gap between the technology and the legal system when it comes to evidence admissibility. The document is high level with more focus on law enforcement processes such as issuing a subpoena and preservation orders to the cloud provider. This research proposes IaaS Public Cloud Forensic Acquisition (IPCFA), a methodology to acquire forensic-sound evidence from public cloud IaaS deployments. IPCFA focuses on bridging the gap between the legal and technical sides of evidence authenticity to help produce admissible evidence that can withstand scrutiny in U.S. courts. Grounded in design research science (DSR), the research is rigorously evaluated using two hypothetical scenarios for crimes that take place in the public cloud. The first scenario takes place in AWS and is hypothetically walked-thru. The second scenario is a demonstration of IPCFA’s applicability and effectiveness on Azure Cloud. Both cases are evaluated using a rubric built from the federal and civil digital evidence requirements and the international best practices for iv digital evidence to show the effectiveness of IPCFA in generating cloud evidence sound enough to be considered admissible in court
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