Measuring the Impact of Spectre and Meltdown

The Spectre and Meltdown flaws in modern microprocessors represent a new class of attacks that have been difficult to mitigate. The mitigations that have been proposed have known performance impacts. The reported magnitude of these impacts varies depending on the industry sector and expected workload characteristics. In this paper, we measure the performance impact on several workloads relevant to HPC systems. We show that the impact can be significant on both synthetic and realistic workloads. We also show that the performance penalties are difficult to avoid even in dedicated systems where security is a lesser concern

The medical science DMZ: a network design pattern for data-intensive medical science

Abstract: Objective We describe a detailed solution for maintaining high-capacity, data-intensive network flows (eg, 10, 40, 100 Gbps+) in a scientific, medical context while still adhering to security and privacy laws and regulations. Materials and Methods High-end networking, packet-filter firewalls, network intrusion-detection systems. Results We describe a “Medical Science DMZ” concept as an option for secure, high-volume transport of large, sensitive datasets between research institutions over national research networks, and give 3 detailed descriptions of implemented Medical Science DMZs. Discussion The exponentially increasing amounts of “omics” data, high-quality imaging, and other rapidly growing clinical datasets have resulted in the rise of biomedical research “Big Data.” The storage, analysis, and network resources required to process these data and integrate them into patient diagnoses and treatments have grown to scales that strain the capabilities of academic health centers. Some data are not generated locally and cannot be sustained locally, and shared data repositories such as those provided by the National Library of Medicine, the National Cancer Institute, and international partners such as the European Bioinformatics Institute are rapidly growing. The ability to store and compute using these data must therefore be addressed by a combination of local, national, and industry resources that exchange large datasets. Maintaining data-intensive flows that comply with the Health Insurance Portability and Accountability Act (HIPAA) and other regulations presents a new challenge for biomedical research. We describe a strategy that marries performance and security by borrowing from and redefining the concept of a Science DMZ, a framework that is used in physical sciences and engineering research to manage high-capacity data flows. Conclusion By implementing a Medical Science DMZ architecture, biomedical researchers can leverage the scale provided by high-performance computer and cloud storage facilities and national high-speed research networks while preserving privacy and meeting regulatory requirements

Studying Security Issues in HPC (Super Computer) Environment

HPC has evolved from being a buzzword to becoming one of the most exciting areas in the field of Information Technology & Computer Science. Organizations are increasingly looking to HPC to improve operational efficiency, reduce expenditure over time and improve the computational power. Using Super Computers hosted on a particular location and connected with the Internet can reduce the installation of computational power and making it centralise. However, centralise system has some advantages and disadvantages over the distributed system, but we avoid discussing those issues and focusing more on the HPC systems. HPC can also be used to build web and file server and for applications of cloud computing. Due to cluster type architecture and high processing speed, we have experienced that it works far better and handles the loads in much more efficient manner then series of desktop with normal configuration connected together for application of cloud computing and network applications. In this paper we have discussed on issues re lated to security of data and information on the context of HPC. Data and information are vanurable to security and safety. It is the purpose of this paper to present some practical security issues related to High Performance Computing Environment. Based on our observation on security requirements of HPC we have discuss some existing security technologies used in HPC. When observed to various literatures, we found that the existing techniques are not enough. We have discussed, some of the key issues relating to this context. Lastly, we have made an approach to find an appropriate solution using Blowfish encryption and decryption algorithm. We hope that, with our proposed concepts, HPC applications to perform better and in safer way. At the end, we have proposed a modified blow fish algorithmic technique by attaching random number generator algorithm to make the encryption decryption technique more appropriate for our own HPC environment

Infrastructure as a service: exploring network access control challenges

Cloud Computing Infrastructure as a Service (IaaS) is a great model for outsourcing IT infrastructure. It is built to offer fascinating features to support business development, such as elasticity, multi-tenancy, configurability and dynamicity. However, IaaS faces security challenges on account of its flexible nature. For this article, we studied the IaaS characteristics and investigated their related security challenges. We then elaborated these security challenges by exploring the security threats on live virtual machine migration as it is one of the main IaaS operations. We found that proper access control techniques and models are a critical element in enhancing IaaS and mitigating the identified security threats. Therefore, we investigated and contrasted the implemented and the proposed firewall architectures in IaaS as a firewall is a basic security appliance that enforces access control. We also explored and contrasted the proposed access control models in the IaaS. It was found that the traditional firewalls and access control models were not sufficient for IaaS. Therefore, there is a need to develop a proper access control model and enforcement techniques to mitigate IaaS security threats. Based on the security research trend and the results obtained in this articles exploration, we endorse an IaaS access control system built on a computational intelligent approach

An SDN-based firewall shunt for data-intensive science applications

A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering, 2016Data-intensive research computing requires the capability to transfer les over long distances at high throughput. Stateful rewalls introduce su cient packet loss to prevent researchers from fully exploiting high bandwidth-delay network links [25]. To work around this challenge, the science DMZ design [19] trades o stateful packet ltering capability for loss-free forwarding via an ordinary Ethernet switch. We propose a novel extension to the science DMZ design, which uses an SDN-based rewall. This report introduces NFShunt, a rewall based on Linux's Net lter combined with OpenFlow switching. Implemented as an OpenFlow 1.0 controller coupled to Net lter's connection tracking, NFShunt allows the bypass-switching policy to be expressed as part of an iptables rewall rule-set. Our implementation is described in detail, and latency of the control-plane mechanism is reported. TCP throughput and packet loss is shown at various round-trip latencies, with comparisons to pure switching, as well as to a high-end Cisco rewall. Cost, as well as operations and maintenance aspects, are compared and analysed. The results support reported observations regarding rewall introduced packet-loss, and indicate that the SDN design of NFShunt is a technically viable and cost-e ective approach to enhancing a traditional rewall to meet the performance needs of data-intensive researchersGS201

Virtual Machine Image Management for Elastic Resource Usage in Grid Computing

Grid Computing has evolved from an academic concept to a powerful paradigm in the area of high performance computing (HPC). Over the last few years, powerful Grid computing solutions were developed that allow the execution of computational tasks on distributed computing resources. Grid computing has recently attracted many commercial customers. To enable commercial customers to be able to execute sensitive data in the Grid, strong security mechanisms must be put in place to secure the customers' data. In contrast, the development of Cloud Computing, which entered the scene in 2006, was driven by industry: it was designed with respect to security from the beginning. Virtualization technology is used to separate the users e.g., by putting the different users of a system inside a virtual machine, which prevents them from accessing other users' data. The use of virtualization in the context of Grid computing has been examined early and was found to be a promising approach to counter the security threats that have appeared with commercial customers. One main part of the work presented in this thesis is the Image Creation Station (ICS), a component which allows users to administer their virtual execution environments (virtual machines) themselves and which is responsible for managing and distributing the virtual machines in the entire system. In contrast to Cloud computing, which was designed to allow even inexperienced users to execute their computational tasks in the Cloud easily, Grid computing is much more complex to use. The ICS makes it easier to use the Grid by overcoming traditional limitations like installing needed software on the compute nodes that users use to execute the computational tasks. This allows users to bring commercial software to the Grid for the first time, without the need for local administrators to install the software to computing nodes that are accessible by all users. Moreover, the administrative burden is shifted from the local Grid site's administrator to the users or experienced software providers that allow the provision of individually tailored virtual machines to each user. But the ICS is not only responsible for enabling users to manage their virtual machines themselves, it also ensures that the virtual machines are available on every site that is part of the distributed Grid system. A second aspect of the presented solution focuses on the elasticity of the system by automatically acquiring free external resources depending on the system's current workload. In contrast to existing systems, the presented approach allows the system's administrator to add or remove resource sets during runtime without needing to restart the entire system. Moreover, the presented solution allows users to not only use existing Grid resources but allows them to scale out to Cloud resources and use these resources on-demand. By ensuring that unused resources are shut down as soon as possible, the computational costs of a given task are minimized. In addition, the presented solution allows each user to specify which resources can be used to execute a particular job. This is useful when a job processes sensitive data e.g., that is not allowed to leave the company. To obtain a comparable function in today's systems, a user must submit her computational task to a particular resource set, losing the ability to automatically schedule if more than one set of resources can be used. In addition, the proposed solution prioritizes each set of resources by taking different metrics into account (e.g. the level of trust or computational costs) and tries to schedule the job to resources with the highest priority first. It is notable that the priority often mimics the physical distance from the resources to the user: a locally available Cluster usually has a higher priority due to the high level of trust and the computational costs, that are usually lower than the costs of using Cloud resources. Therefore, this scheduling strategy minimizes the costs of job execution by improving security at the same time since data is not necessarily transferred to remote resources and the probability of attacks by malicious external users is minimized. Bringing both components together results in a system that adapts automatically to the current workload by using external (e.g., Cloud) resources together with existing locally available resources or Grid sites and provides individually tailored virtual execution environments to the system's users

Big Data and Large-scale Data Analytics: Efficiency of Sustainable Scalability and Security of Centralized Clouds and Edge Deployment Architectures

One of the significant shifts of the next-generation computing technologies will certainly be in the development of Big Data (BD) deployment architectures. Apache Hadoop, the BD landmark, evolved as a widely deployed BD operating system. Its new features include federation structure and many associated frameworks, which provide Hadoop 3.x with the maturity to serve different markets. This dissertation addresses two leading issues involved in exploiting BD and large-scale data analytics realm using the Hadoop platform. Namely, (i)Scalability that directly affects the system performance and overall throughput using portable Docker containers. (ii) Security that spread the adoption of data protection practices among practitioners using access controls. An Enhanced Mapreduce Environment (EME), OPportunistic and Elastic Resource Allocation (OPERA) scheduler, BD Federation Access Broker (BDFAB), and a Secure Intelligent Transportation System (SITS) of multi-tiers architecture for data streaming to the cloud computing are the main contribution of this thesis study

AUTOMATED NETWORK SECURITY WITH EXCEPTIONS USING SDN

Campus networks have recently experienced a proliferation of devices ranging from personal use devices (e.g. smartphones, laptops, tablets), to special-purpose network equipment (e.g. firewalls, network address translation boxes, network caches, load balancers, virtual private network servers, and authentication servers), as well as special-purpose systems (badge readers, IP phones, cameras, location trackers, etc.). To establish directives and regulations regarding the ways in which these heterogeneous systems are allowed to interact with each other and the network infrastructure, organizations typically appoint policy writing committees (PWCs) to create acceptable use policy (AUP) documents describing the rules and behavioral guidelines that all campus network interactions must abide by. While users are the audience for AUP documents produced by an organization\u27s PWC, network administrators are the responsible party enforcing the contents of such policies using low-level CLI instructions and configuration files that are typically difficult to understand and are almost impossible to show that they do, in fact, enforce the AUPs. In other words, mapping the contents of imprecise unstructured sentences into technical configurations is a challenging task that relies on the interpretation and expertise of the network operator carrying out the policy enforcement. Moreover, there are multiple places where policy enforcement can take place. For example, policies governing servers (e.g., web, mail, and file servers) are often encoded into the server\u27s configuration files. However, from a security perspective, conflating policy enforcement with server configuration is a dangerous practice because minor server misconfigurations could open up avenues for security exploits. On the other hand, policies that are enforced in the network tend to rarely change over time and are often based on one-size-fits-all policies that can severely limit the fast-paced dynamics of emerging research workflows found in campus networks. This dissertation addresses the above problems by leveraging recent advances in Software-Defined Networking (SDN) to support systems that enable novel in-network approaches developed to support an organization\u27s network security policies. Namely, we introduce PoLanCO, a human-readable yet technically-precise policy language that serves as a middle-ground between the imprecise statements found in AUPs and the technical low-level mechanisms used to implement them. Real-world examples show that PoLanCO is capable of implementing a wide range of policies found in campus networks. In addition, we also present the concept of Network Security Caps, an enforcement layer that separates server/device functionality from policy enforcement. A Network Security Cap intercepts packets coming from, and going to, servers and ensures policy compliance before allowing network devices to process packets using the traditional forwarding mechanisms. Lastly, we propose the on-demand security exceptions model to cope with the dynamics of emerging research workflows that are not suited for a one-size-fits-all security approach. In the proposed model, network users and providers establish trust relationships that can be used to temporarily bypass the policy compliance checks applied to general-purpose traffic -- typically by network appliances that perform Deep Packet Inspection, thereby creating network bottlenecks. We describe the components of a prototype exception system as well as experiments showing that through short-lived exceptions researchers can realize significant improvements for their special-purpose traffic