|Exam Name||:||IBM Security Access Manager V7.0(R) Implementation|
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|Updated On||:||April 22, 2019|
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C2150-198 exam Dumps Source : IBM Security Access Manager V7.0(R) Implementation
Test Code : C2150-198
Test Name : IBM Security Access Manager V7.0(R) Implementation
Vendor Name : IBM
Q&A : 111 Real Questions
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SAN DIEGO, Oct 02, 2017 (GLOBE NEWSWIRE by means of COMTEX) --
ImageWare techniques, Inc. (ImageWare or IWS) (otcqb:IWSY), a frontrunner in mobile and cloud-based mostly, multi-modal biometric identification administration solutions, nowadays announced it has acquired IBM PartnerWorld's ready for IBM security Intelligence designation for its GoVerifyID business Suite. due to this fact, ImageWare's GoVerifyID has been validated to integrate with IBM protection items to help improved protect its shoppers worldwide.
ImageWare's GoVerifyID offers multi-modal biometric user authentication using cell instruments and software-as-a-carrier (SaaS). GoVerifyID, mixed with IBM's flagship access management platform, IBM protection access manager (ISAM), makes it possible for clients to swipe a fingerprint, take a selfie, or provide a voice pattern on their mobile machine to authenticate for any ISAM managed resource. GoVerifyID business Suite is an end-to-conclusion, business-capable, safety answer that can also be seamlessly built-in into your current ISAM authentication methods, presenting a secure and user-pleasant journey, while enabling you to undertake new biometric modalities as they are available.
"flexible cellular biometric authentication, combined with comfy net utility access offers the top of the line in protection and pleasant person adventure," spoke of IWS Chairman and CEO Jim Miller. "ISAM clients can now delight in seamless integration and directly access all of their apps by means of simply taking a selfie, the use of a fingerprint or speakme a passphrase. And, of direction, as with any IWS cell authentication products, users can at all times avail themselves of the newest advancements in biometric expertise if they decide to do so as our GoVerifyID items are supported with the aid of our patented IWS Biometric Engine(R) that permits for unparalleled flexibility, scale, and protection."
The equipped for IBM security Intelligence alliance is designed to promote expertise collaboration and integration to extend and enhance security insurance, cave in silos of tips, and raise situational consciousness and insights. With the PartnerWorld application and equipped for safety Intelligence validation, IBM supports collaboration with its company partners to allow the mixing of product capabilities and improved security capabilities for mutual shoppers.
About ImageWare techniques, Inc.ImageWare methods, Inc. is a leading developer of cell and cloud-based identity administration options, presenting biometric authentication options for the business. The company offers next-era biometrics as an interactive and scalable cloud-based answer. ImageWare brings collectively cloud and cellular know-how to present multi-component authentication for smartphone clients, for the business, and throughout industries.
ImageWare's products help multi-modal biometric authentication together with, but no longer limited to, face, voice, fingerprint, iris, palm, and greater. all of the biometrics can also be combined with or used as replacements for authentication and entry control equipment, together with tokens, digital certificates, passwords, and PINS, to deliver the gold standard level of assurance, accountability, and ease of use for company networks, net purposes, mobile devices, and workstation computer environments.
ImageWare is headquartered in San Diego, Calif., with workplaces in Portland, OR, Ottawa, Ontario, and Mexico city, Mexico. To study extra about ImageWare, talk over with iwsinc.com; observe us on Twitter, LinkedIn, YouTube and fb.
Investor members of the family:
LioliosCody SlachTel 1-949-574-3860IWSY@liolios.com
Copyright (C) 2017 GlobeNewswire, Inc. All rights reserved.
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ThinkstockShare KuppingerCole document: management Compass of access management and Federation on Twitter Share KuppingerCole record: leadership Compass of access administration and Federation on fb Share KuppingerCole document: management Compass of access administration and Federation on LinkedIn
a part of fixing any IT subject is finding the appropriate answer for the problem and making certain the concern will now not ensue once again. one of the most major struggles for the IT trade is finding the right vendors to enlist as protectors.
KuppingerCole’s leadership Compass record on entry administration and federation aims to close the hole between the correct answer and the right supplier.
rising business requirements, corresponding to onboarding company partners, featuring consumer access to services and adopting new cloud capabilities, require IT to react and find options to those communications and collaboration circumstances. access management and federation providers are closing in to tackle these needs and enable enterprise agility.
With many vendors during this market segment, the KuppingerCole leadership Compass gives a view and evaluation of the leading carriers and their strengths and weaknesses. The document acts as a ebook for the consumer to compare product points and particular person product necessities.
study the KuppingerCole management Compass fileBreaking Down the management rankings
When evaluating the distinct carriers and products, KuppingerCole looked into the elements of standard performance, dimension of the business, number of consumers, number of developers, companion ecosystems, licensing models and platform assist. particular facets, such as federation inbound, federation outbound, backend integration, adaptive authentication, registration, consumer studies, protection fashions, deployment models, customization and multitenancy, had been regarded as neatly.
KuppingerCole created numerous leadership scores, including “Product leadership,” “Innovation management,” and “Market leadership,” to mix for the “ordinary leadership” ranking. With this view, KuppingerCole gives an ordinary impact of each and every vendor’s providing within the specific market section.
Product leadership is in keeping with evaluation of product and features points and capabilities. This view focuses on the purposeful power and completeness of each product.
Innovation management focuses on a customer-oriented method that ensures the product or provider has compatibility with earlier models, in addition to helps new features that carry emerging client requirements.
Market management is according to market criteria, corresponding to number of clients, the companion ecosystem, the world attain and the nature of responses to components affecting the market outlook. This view focuses on global attain, sales and service aid, and successful execution of advertising and marketing method.
How IBM Ranks
IBM security access supervisor (ISAM) is ranked as a frontrunner in the Product, marketing and know-how leadership categories. This rating comes from IBM ISAM having one of the greatest consumer bases of all carriers in the market section, a robust accomplice ecosystem, mature access management and robust adaptive authentication. ISAM is among the many main products in the entry administration and federation market and meets organizations’ starting to be lists of IT security requirements with wide characteristic support.study the entire report
check out the complete file to find:
read the KuppingerCole leadership Compass documentTags: entry administration | IBM protection | identity and entry administration (IAM) | Kuppingercole | protection products | protection options Kelly Lappin Kelly Lappin is a advertising and marketing professional working on the IBM safety SaaS portfolio. 2 Posts proceed studying What’s new
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Last we heard from SkyGiraffe, a platform to extend enterprise systems with mobile devices, it had raised a seed round from Angels (including Parker Thompson, a partner at 500 Startups) back in May. Today it announces it has taken a strategic investment from Microsoft Ventures. Terms were not disclosed but we understand from sources that the investment is more about strategy than injecting large amounts of cash. Because SkyGiraffe has key integrations with Microsoft technologies, this will give it significant distribution, and presumably, way more traction than if it was out there on its own.
The company was started by and Itay Braun, VP R&D, and Boaz Hecht, CEO. The latter says they make it “easy for businesses to perform” on mobile. How it works is this: An IT manager downloads the client, installs SkyGiraffe Studio and then selects the back-end and data source to connect. IT can then define security access and other IT policies. Inside 30 minutes they say an enterprise can provide employees with secure access to on-premise data from several backend systems. Thus, any Oracle or MS SQL DBA can build a mobile app that reads and writes from tables/views and stored procedures within a few minutes.
In practical terms that means the ability to read and write-back live data to the company’s systems, both ERP and CRM. Normally this would require either a big system integration project or hiring dedicated developers – but with their platform they say it’s a very simple integration. The native apps are built for both iOS and Android devices so implementation and compatibility issues don’t really figure. Technically speaking, it’s biggest competitors are Capriza and IBM Worklight.
SkyGiraffe’s platform provides secure access to live data, such as sales, finance, inventory, and operational information through a customizable mobile platform that can be implemented across an organisation.
Rahul Sood, General Manager of Microsoft Ventures says the investment means SkyGiraffe is a “great example of talented founders that have utilized Microsoft’s programs for startups to increase their opportunity to succeed.”
SkyGiraffe started their relationship with Microsoft through the BizSpark program and later were accepted into the Microsoft Ventures Accelerator in Israel.
Enterprise companies can request an invite via their site, which is in private beta.
This article first appeared in IEEE Software magazine and is brought to you by InfoQ & IEEE Computer Society.
The growing popularity of cloud computing draws attention to its security challenges, which are particularly exacerbated due to resource sharing.1 Cloud computing’s multitenancy and virtualization features pose unique security and access control challenges due to sharing of physical resources among potential untrusted tenants, resulting in an increased risk of side-channel attacks.2 Additionally, the interference of multitenancy computation can result in unauthorized information flow. Heterogeneity of services in cloud computing environments demands varying degrees of granularity in access control mechanisms. Therefore, an inadequate or unreliable authorization mechanism can significantly increase the risk of unauthorized use of cloud resources and services. In addition to preventing such attacks, a fine-grained authorization mechanism can assist in implementing standard security measures. Such access control challenges and the complexities associated with their management call for a sophisticated security architecture that not only adequately captures access management requirements but also ensures secure interoperation across multiple clouds.
We present a distributed access control architecture for multitenant and virtualized environments. The design of this architecture is based on the principles from security management and software engineering. From a security management perspective, the goal is to meet cloud users’ access control requirements. From a software engineering perspective, the goal is to generate detailed specifications of such requirements.
Several researchers have previously addressed access control issues for cloud computing. Daniel Nurmi and his colleagues provided an authorization system to control the execution of virtual machines (VMs) to ensure that only administrators and owners could access them.3 Stefan Berger and his colleagues promoted an authorization model based on both role-based access control (RBAC) and security labels to control access to shared data, VMs, and network resources.4 Jose Alcaraz Calero and his colleagues presented a centralized authorization system that provides a federated path-based access control mechanism.5 What distinguishes our work is that we present an architecture that can be implemented using an XML-based formalism.6 We also address the problems of side-channel attacks and noninterference in the presence of multitenancy and resource virtualization. Accordingly, we present an access control architecture that addresses these challenges.Authorization Requirements
In order to build a secure and trusted distributed cloud computing infrastructure, the cloud architecture’s designer must address several authorization requirements.Multitenancy and Virtualization
Side-channel attacks and interference among different policy domains pose daunting challenges in distributed clouds. Side-channel attacks are based on information obtained from physical implementation (for example, via time- or bandwidth-monitoring attacks). Side-channel attacks arise due to lack of authorization mechanisms for sharing physical resources. The interference among tenants exists primarily because of covert channels with flawed access control policies that allow unauthorized information flow.7Decentralized Administration
Decentralized administration is characterized by the principle of local autonomy, which implies that each service model retains administrative control over its resources. This is in contrast to a centralized administration approach, which implies loss of autonomy in controlling resources; it’s not a desirable system feature when dealing with several independent clouds. Moreover, the need for a fine-grained access control can enact substantial requirements in designing an access control policy employing a large number of authorization rules. These rules can grow significantly with an increase in the granularity of resources, as well as with the number of users and services supported by the cloud. A centralized design based on the integration of all global rules can pose significant challenges.Secure Distributed Collaboration
To support a decentralized environment, the cloud infrastructure should allow both horizontal and vertical policy interoperation for service delivery. Due to the heterogeneous nature of the cloud, resource and service policies might use different models requiring seamless interoperation among policies. These policies must be correctly specified, verified, and enforced. A service-level agreement (SLA) can provide secure collaboration and assure that services are provided according to pre-established rules.Credential Federation
Because a user might invoke services across multiple clouds, access control policies must support a mechanism to transfer a customer’s credentials across layers to access services and resources. This requirement includes a provision for a decentralized single-sign-on mechanism within the authorization model, which can enable persistent authorization for customers in terms of their identity and entitlement across multiple clouds.6Constraint Specification
The collaborative nature of a cloud computing environment requires the specification of semantic and contextual constraints to ensure adequate protection of services and resources, especially for mobile services. Semantic constraints (for example, separation of duties) and contextual constraints (such as temporal or environmental constraints included in an access request) must be evaluated when determining access to services and resources.8 Semantic and contextual constraints are specified in the access control policy.Designing a Distributed Cloud Architecture
The nature of assuring resource sharing across multiple clouds depends on the collaborative environment. Figure 1 shows three types of collaborations (federated, loosely coupled, and ad hoc) that can fulfill the aforementioned authorization requirements.Federated Collaboration
Federated collaboration is characterized by a high degree of mutual dependence and trust among collaborating clouds and supports a long-term interoperation. To be secure, this collaboration requires a global metapolicy that’s consistent with local policies of the collaborating clouds. A policy-composition framework (top block of Figure 1) is necessary if a global metapolicy needs to be generated by integrating the policies of individual clouds.8Loosely Coupled Collaboration
In a loosely coupled collaborative environment, local policies govern interactions among multiple clouds. In contrast to a federated collaboration, this collaboration is more flexible and autonomous in terms of access policies and resource management. Two collaborating clouds can virtualize their resources and allow autonomous sharing of resources. The information about the virtualized shareable resources and services of each cloud is stored in a virtual global directory service (VGDS), which is manifested across service-level agreement (SLAs). The middle block of Figure 1 shows the verification for conformance of individual clouds’ security and privacy policies for loosely coupled collaboration.Ad Hoc Collaboration
In ad hoc collaboration, a user is only aware of a few remote sharable services. Because a priori information about an application’s overall service requirements might not be available to the user or cloud at the start of a session, a cloud might deny access to its resources. To ensure secure interoperation via discovered resources and services in a dynamic interoperation environment where clouds can join and leave in an ad hoc manner, appropriate authentication and authorization mechanisms need to be developed.Evaluation
Several metrics can be used to evaluate these collaborations, including
Figure 1 shows the tradeoffs among collaboration types and these metrics; the collaboration metrics’ arrows point toward higher values. For example, ad hoc collaboration supports a higher level of privacy than federated or loosely coupled collaborations do.
(Click on the image to enlarge it)
FIGURE 1. Characterization of collaboration in a mutlicloud environment. In a distributed environment, we can build a security architecture based on the design of these collaborations. Their comparison is based on degree of interoperation, autonomy, privacy, and verification complexity. The architecture we present in this article is based on federated and loosely coupled collaborations.A Distributed Cloud Security Architecture
The proposed distributed architecture that addresses and incorporates the aforementioned authorization requirements can be built using three types of components: a virtual resource manager (VRM), a distributed access control module (ACM; Figure 2), and an SLA (Figure 3). The proposed architecture (Figure 4) uses the RBAC model, which is recognized for its support for simplified administration and scalability.6 However, the design of this architecture is generic enough to support other access control policies, such as discretionary access control and multilevel security.
FIGURE 2. Access control module architecture. This component can be used to build the proposed distributed architecture.
FIGURE 3. Service-level agreement (SLA) architecture. This component can be used to build the proposed distributed architecture.
FIGURE 4. Intercloud and intracloud interoperations for the distributed security architecture. Shaded SLAs correspond to alternate architectures involving peer-to-peer interoperation.VRM Design Specification
The heterogeneity and granularity of virtual resources in a cloud environment call for a VRM at each layer of the cloud, as depicted in Figure 4. The VRM is responsible for providing and deploying virtual resources. Consequently, it maintains a list of required virtual resources with their configuration, including both local and remote resources through VGDS-the one shown in Figure 1. SLAs provide access to remote resources, whereas the VRM is responsible for monitoring deployed resources and might allocate or release them to ensure SLA compliance, including guarantees for quality of service. To manage the scalability issue in cloud computing in term of users and resources, the VRM uses a distributed architecture.3ACM Design Specification
An ACM resides at each layer to enforce the access control policy at its resident layer. As shown in Figure 2, the main components of an ACM include
The authorization request (Figure 2, step 1) submitted to the PEP includes the requesting subject, the requested service or resource, and the type of permissions requested for that service or resource (such as read or write privileges). The request might also include the credentials needed for authentication and authorization. The PEP extracts the authentication credentials and the context information from the authorization request and forwards them to the credential evaluator and context evaluator (Figure 2, step 2). The PEP receives the decision about granting the request (Figure 2, step 3) and either grants or denies the user’s authorization request.
If the request contains an authenticating credential, the credential evaluator assigns a user a local role based on the user-to-role assignment rules stored in the RBAC policy base. The process of user-to-role assignment requires input from the context evaluator regarding contextual constraints. If the request contains an authorization credential, the credential evaluator assesses if the role corresponds to a local role. If not, the implication is that this is a single-sign-on request and requires role mapping by a relevant SLA. Subsequently, the user acquires the privileges of the locally assigned role or of a mapped role in a remote cloud.6SLA Specification
To allow interoperation among autonomous policies manifested through ACMs, an SLA implements a mediated policy. For this purpose, an SLA performs role mapping, specifies isolation constraints for resource sharing to prevent side-channel attacks, and presents a virtualized view of resources at the levels for which the SLA is negotiated. In addition, an SLA usually includes quality-of-service parameters, as well as billing and auditing functions. Figure 3 depicts the authorization flow within an SLA.
Role mapping is a function that maps a local role to a role in a remote cloud and grants access to all the mapped role’s permissions. The mutually agreed upon mediated policy, which is generally a subset of the policies of the participating ACMs, enforces access control for distributed services or resources through this mapping. In addition, the SLA physically isolates resources to prevent side-channel attacks at the remote cloud.2 Such isolation can prevent multiple VMs from residing on the same physical machine. Physical isolation can be explicitly enforced in the form of cardinality constraint rules in the RBAC policy.6 By setting the cardinality constraint parameter to one, we can enforce such isolation.RBAC Policy Specification for Proposed Architecture
We adopted an XML-based specification due to its compatibility with the emerging standards for cloud systems and security protocols, with the ultimate goal being that the proposed architecture should be interoperable with complementary security protocols for cloud systems. Figures 5a and 5b show the XML-based specifications of ACMs and SLAs, respectively. (The full details of RBAC XML declaration appear elsewhere.6)
The ACM’s XML user sheet defines the authenticating credentials and the XML role sheet defines the authorization credentials. The XML user-to-role assignment sheet defines user-to-role assignment rules, which can be based on attributes associated with users’ credentials as defined in the XML user sheet. XML permission-to-role assignment sheets define permission-to-role assignment rules. Permission-to-role constraints can be based on attributes associated with a role’s credential or the resource type as defined in XML virtual resource sheets (see Figure 5c). The constraints can be semantic (for instance, separation of duty) or temporal. To represent authorization requirements as a set of predicates, predicate function definitions sheets define the formal notion of predicate expression. A predicate function definition sheet can include mediated rules for intercloud resource sharing; a predicate expression can help evaluate sets of temporal or non-temporal constraints.6
(Click on the image to enlarge it)
FIGURE 5. High-level XML declaration: (a) access control module, (b) mediated service-level agreement policy, and (c) virtual resource definition and sharing constraint (local and remote).
A permission defined in the XML permission sheet comprises a specified operation on a given resource type. Thus, a role assigned a permission defined on a given resource type receives access to all instances of that resource type. XML allows access granularity at individual levels within a resource type to provide support for individual virtual resources-for example, as mentioned earlier, we can specify the physical isolation attribute of a virtual resource at the individual resource level in the form of a cardinality constraint to prevent side-channel attacks in the local cloud. Note that depending on if the requested resources are local or remote, the ACM decides whether or not to invoke SLA. The XML specification of the SLA depicted in Figure 5b provides a limited view of advertised virtual resources, role mapping, and cardinality constraints.Ensuring Noninterference
To avoid security risk due to potential interference as a result of multitenancy, we must abstract policies by participating ACMs and SLAs as an information flow model. Subsequently, this model can be verified to ensure the property of noninterference.7 Such verification ensures that each domain remains unaffected by the actions of other domains. As side-channel attacks can be managed through cardinality constraints, unauthorized information flow can only occur when there’s conflict among cloud policies. In conjunction with the data model, verification models8 or verification tools (such as Alloy9) can detect conflicts among policies, which causes unauthorized information flow.Distributed Authorization Process and Use Cases
Three types of interoperations related to authorization flow can occur at various layers of the distributed architecture, as illustrated in Figure 4. Type 1 depicts a horizontal (peer-to-peer) interoperation between the same levels of different cloud providers; type 2 represents a vertical interoperation between layers within the same cloud; and type 3 indicates a cross-layered interoperation between different clouds at different layers. Both type 1 and 3 interoperations require SLAs among the participating clouds. These three types of interoperation also establish distributed authorization mechanisms among ACMs.
For distributed authorization, VRMs use their peer-to-peer or cross- layered interoperations through VGDSs in order to provide the required re- sources. VGDSs have both the local virtual resource IDs and the paths of the physical resources they map to, as well as remote virtual resource IDs consistent with the SLAs that advertise these resources. Therefore, a VGDS can manifest either through peer-to-peer or cross-layered SLAs (shown in dotted SLA blocks at the PaaS and IaaS levels of Figure 4). Assessment of these architectural choices is an open problem.
For interoperations among ACMs, we envision loosely coupled collaboration consistent with type 1 and type 3 interoperations because individual clouds need to reveal only limited in- formation about their services and policies. Federated cloud collaboration requires an extensive analysis prior to generating the global metapolicy, which can result in a high degree of complexity and rule explosion. Therefore, this approach isn’t scalable for distributed collaboration. Also, generating a consistent global metapolicy could require extensive mediation to resolve conflicts among heterogeneous policies.8 Similarly, ad hoc collaboration doesn’t federate credentials across clouds because it lacks SLA support.
For type 2 interoperation, federated collaboration can be an appropriate approach because it requires only vertical integration of polices. Therefore, the high complexity for generating a global metapolicy within a cloud is justified because the cloud provider has access to all its local policies belonging to the three service models. However, the provider must address the challenge of conflict resolution and mediation for generating such a metapolicy. Figure 5a shows an example of a high-level metapolicy specification; further details appear elsewhere.6Authorization Process
When a customer requests a service or virtual resource, the request goes to the local ACM (Figure 6, step 1). If the ACM grants this request, it routes the request to the local VRM (step 2). If the requested resources reside in the local cloud, the VRM (after consulting the VGDS) forwards the request to the local ACM of the lower level-for example, from SaaS to PaaS (step 3). Ultimately, the request goes to the infrastructure as a service (IaaS)-level VRM in order to deploy the required physical resources. If the required resources are in a remote cloud, the local VRM, after consulting the VGDS, issues a remote request to the appropriate SLA (step 3). The SLA, after performing its functions involving role mapping and evaluating the policy constraints, forwards the request to the remote ACM (step 4). After verifying its own constraints (including cardinality constraints), the ACM informs its local VRM to allocate the desired resources (step 5). Finally, the VRM identifies and configures the local physical resources (step 6).
(Click on the image to enlarge it)
FIGURE 6. Flow of request via the access control module and virtual resource manager across multiple clouds.Use Cases
This authorization process is a generic representation of a set of use cases. To specify these cases, we adopt Alcaraz Calero and colleagues’ authorization model4 by extending it to support multitenancy and virtualization in a distributed environment. Figure 7 illustrates two classes of scenarios covering all possible interactions within and across multiple clouds. These scenarios involve the three types of interoperations discussed earlier in this article. Assuming an RBAC model, the authorization request can be represented using a four-tuple expression (subject, permission, interface, object [attributes]), which can be interpreted in the following way: the subject (as a role) asking for a permission to be performed over the object (virtual resource or service) with its attributes (such as isolation constraint) and that object’s interface type. We assume the authorization request is time stamped to accommodate temporal contextual constraint. From an RBAC perspective, the subject is represented as a role. In addition, users of the XML user sheet specified in Figure 5a, which identifies user-to-role assignments, can assume their respective roles. Along with this assignment, the proposed four-tuple can fully specify an authorization request.
When user X initiates the authorization process to access an application (app) at the SaaS level of its local cloud (SaaSCP1), the corresponding ACM’s PEP needs to authenticate the user prior to assigning a local role (for example, Rx) based on its credentials. If X requires a remote resource, the participating SLA assigns it a mapped role (say, Ry).
The local SaaS verifi es this request, represented as Rx, execute, SaaSCP1, app, for authorization. Consequently, one of the following scenarios can occur.
Scenario A. Figure 7a depicts this scenario. We assume the requested resources are locally available, resulting in type 2 collaboration within the local cloud. Accordingly, the SaaS’s local VRM identifies virtual resources-for example, computation instance (CompInstx) and storage (Storex). Assuming that the local policy verifi es the authorization request, the VRM, after consulting with the VGDS, requests the two desired resources through the following two authorization requests: Rx, execute, PaaSCP1, CompInstx(isolation=1) and Rx, execute, IaaSCP1, StoreX. Here, we assume X is requesting fully isolated computation resources to avoid side-channel attacks.
Scenario B. Figure 7b shows four scenarios depicting ACM interaction across multiple clouds at different levels:
FIGURE 7. Scenario-based policy interoperation. (a) Secure interoperation within a local cloud to acquire resources that are locally available. (b) Secure interoperation involving SLAs at different levels to acquire resources among multiple clouds.
These use cases represent high-level design requirements for the proposed architecture and cover all possible authorization flow processes that can be used to design and develop the distributed architecture. Currently, development for a prototype of this architecture is underway; it uses the Microsoft Azure platform to develop a health surveillance and rapid response infrastructure with the capability of collecting and analyzing real-time epidemic data from various hospitals. This cloud computing environment consists of compute clusters, reliable data storage, and software services. The stakeholders include researchers, physicians, and government public health management personnel in the chain of reporting. The services provided to stakeholders include visual analytics, statistical data analysis, and scenario simulations.10
The architecture we present in this article represents a precise but comprehensive authorization design for access management. Using an XML-based declaration of the access control policy for this architecture is a step toward its implementation. However, we must address several open challenges in order to implement a fully secure and trusted cloud environment. These include design of an authentication mechanism, cryptography and key management, mediation for conflict resolution of heterogeneous policies, software design for virtualized resources, integrating information flow verification tools to ensure noninterference, and architectural choices for SLAs. We plan to address these challenges in our future work.Acknowledgments
The research in this article is partially funded by the US National Science Foundation under grant IIS-0964639.References
1. H. Takabi, J.B.D. Joshi, and G.-J. Ahn, "Security and Privacy Challenges in Cloud Computing Environments," IEEE Security & Privacy, vol. 8, no. 6, 2010, pp. 24-31.2. T. Ristenpart et al., "Hey, You, Get off of My Cloud: Exploring Information Leakage in Third-Party Compute Clouds," Proc. 16th ACM Conf. Computer and Communications Security (CCS 09), ACM, 2009, pp. 199-212.3. D. Nurmi et al., "The Eucalyptus Open- Source Cloud-Computing System," Proc. 9th IEEE/ACM Int’l Symp. Cluster Computing and the Grid (CCGRID 09), IEEE CS, 2009, pp. 124-131.4. S. Berger et al., "Security for the Cloud Infrastructure: Trusted Virtual Data Center Implementation," IBM J. Research and Development, vol. 53, no. 4, 2009, pp. 560-571.5. J.M. Alcaraz Calero et al., "Toward a Multitenancy Authorization System for Cloud Services," IEEE Security & Privacy, vol. 8, no. 6, 2010, pp. 48-55.6. R. Bhatti, E. Bertino, and A. Ghafoor, "X- Federate: A Policy Engineering Framework for Federated Access Management," IEEE Trans. Software Eng., vol. 32, no. 5, 2006, pp. 330-346.7. J. Rushby, Noninterference, Transitivity, and Channel-Control Security Policies, tech. report CSL-92-02, Computer Science Lab, SRI Int’l, 1992.8. B. Shafi q et al., "Secure Interoperation in a Multidomain Environment Employing RBAC Policies," IEEE Trans. Knowledge and Data Eng., vol. 17, no. 11, 2005, pp. 1557-1577.9. D. Jackson, I. Schechter, and I. Shlyakhter, "ALCOA: The Alloy Constraint Analyzer," Proc. 22nd Int’l Conf. Software Eng., ACM, 2000, pp. 730-733.10. S. Afzal, R. Maciejewski, and D.S. Ebert, "Visual Analytics Decision Support Environment for Epidemic Modeling and Response Evaluation," IEEE Conf. Visual Analytics Science and Technology (VAST 11), IEEE CS, 2011, pp. 191-200.About the Authors
This article first appeared in IEEE Software magazine. IEEE Software's mission is to build the community of leading and future software practitioners. The magazine delivers reliable, useful, leading-edge software development information to keep engineers and managers abreast of rapid technology change.
Latest results bring device performance near the minimum requirements for implementation of a practical quantum computer.
Scaling up to hundreds or thousands of quantum bits becomes a possibility.
YORKTOWN HEIGHTS, NY – 28 Feb 2012: Scientists at IBM Research (NYSE: IBM)/ (#ibmresearch) have achieved major advances in quantum computing device performance that will accelerate the realization of a practical, full-scale quantum computer. For specific applications, quantum computing which leverages the underlying quantum mechanical behavior of matter has the potential to deliver computational power that is unrivaled by any supercomputer today.
Using a variety of techniques in the IBM labs, scientists have established three new records for reducing the error in elementary computations and retaining the integrity of quantum mechanical properties in quantum bits (qubits) – the basic units that carry information within quantum computing. Furthermore, IBM has chosen to employ superconducting qubits which use established microfabrication techniques developed for silicon technology, providing the potential to one day scale up to and manufacture thousands or millions of qubits.
IBM researchers will be presenting their latest results today at the annual American Physical Society meeting taking place February 27-March 1, 2012 in Boston, MA.
The Possibilities of Quantum Computing
The special properties of qubits allow a quantum computer to work on millions of computations at once, while a desktop PC can typically handle minimal computations at a time. For example, a single 250-qubit state contains more bits of information than there are particles in the universe.
These properties will have wide-spread implications foremost for the field of data encryption where quantum computers could factor very large numbers like those used to decode and encode sensitive information.
"The quantum computing work we are doing shows it is no longer just a brute force physics experiment. It's time to start creating systems based on this science that will take computing to a whole new level," says IBM scientist Matthias Steffen, manager of the IBM Research team that's focused on developing quantum computing systems to a point where it can be applied to real-world problems.
Numerous other applications could include searching databases of unstructured information, performing a range of optimization tasks and solving new interesting mathematical problems.
How Quantum Computing Works
The most basic piece of information that a classical computer understands is a bit. Much like a light that can be switched on or off, a bit can have only one of two values: "1" or "0". For qubits, they can hold a value of "1" or "0" as well as both values at the same time. Described as superposition, this is what allows quantum computers to perform millions of calculations at once.
One of the great challenges for scientists seeking to harness the power of quantum computing is controlling or removing quantum decoherence – the creation of errors in calculations caused by interference from factors such as heat, electromagnetic radiation, and materials defects. To deal with this problem, scientists have been experimenting for years to discover ways of reducing the number of errors and of lengthening the time periods over which the qubits retain their quantum mechanical properties. When this time is sufficiently long, error correction schemes become effective making it possible to perform long and complex calculations.
There are many viable systems that can potentially lead to a functional quantum computer. IBM is focusing on using superconducting qubits that will allow a more facile transition to scale up and manufacturing.
IBM has recently been experimenting with a unique "three dimensional" superconducting qubit (3D qubit), an approach that was initiated at Yale University. Among the results, the IBM team has used a 3D qubit [technical paper available] to extend the amount of time that the qubits retain their quantum states up to 100 microseconds. This value reaches just past the minimum threshold to enable effective error correction schemes and suggests that scientists can begin to focus on broader engineering aspects for scalability.
In separate experiments, the group at IBM also demonstrated a more traditional "two-dimensional" qubit (2D qubit) device and implemented a two-qubit logic operation – a controlled-NOT (CNOT) operation [technical paper available], which is a fundamental building block of a larger quantum computing system. Their operation showed a 95 percent success rate, enabled in part due to the long coherence time of nearly 10 microseconds. These numbers are on the cusp of effective error correction schemes and greatly facilitate future multi-qubit experiments.
IBM and Quantum Computing Leadership
The implementation of a practical quantum computer poses tremendous scientific and technological challenges, but all results taken together paint a very favorable picture for realizing the first practical quantum computer in the not too distant future.
Core device technology and performance metrics at IBM have undergone a series of amazing advancements by a factor of 100 to 1,000 times since the middle of 2009, culminating in the recent results that are very close to the minimum requirements for a full-scale quantum computing system as determined by the world-wide research community. In these advances, IBM stresses the importance and value of the ongoing exchange of information and learning with the quantum computing research community as well as direct university and industrial collaborations.
"The superconducting qubit research led by the IBM team has been progressing in a much focused way on the road to a reliable, scalable quantum computer. The device performance that they have now reported brings them nearly to the tipping point; we can now see the building blocks that will be used to prove that error correction can be effective, and that reliable logical qubits can be realized," observes David DiVincenzo, professor at the Institute of Quantum Information, Forschungszentrum Juelich.
Based on this progress, optimism about superconducting qubits and the possibilities for a future quantum computer are rapidly growing. While most of the work in the field to date has focused on improvements in device performance, efforts in the community now must now include systems integration aspects, such as assessing the classical information processing demands for error correction, I/O issues, feasibility, and costs with scaling.
IBM envisions a practical quantum computing system as including a classical system intimately connected to the quantum computing hardware. Expertise in communications and packaging technology will be essential at and beyond the level presently practiced in the development of today's most sophisticated digital computers.
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