SCALPEL: Exploring the Limits of Tag-enforced Compartmentalization

We present Secure Compartments Automatically Learned and Protected by Execution using Lightweight metadata (SCALPEL), a tool for automatically deriving compartmentalization policies and lowering them to a tagged architecture for hardware-accelerated enforcement. SCALPEL allows a designer to explore high-quality points in the privilege-reduction vs. performance overhead tradeoff space using analysis tools and a detailed knowledge of the target architecture to make best use of the available hardware. SCALPEL automatically implements hundreds of compartmentalization strategies across the privilege-performance tradeoff space, all without manual tagging or code restructuring. SCALPEL uses two novel optimizations for achieving highly performant policies: the first is an algorithm for packing policies into working sets of rules for favorable rule cache characteristics, and the second is a rule prefetching system that allows it to exploit the highly predictable nature of compartmentalization rules. To create policies, SCALPEL introduces a quantitative privilege metric (the Overprivilege Ratio) that is used to drive its algorithmic compartment generation. We implement SCALPEL on a FreeRTOS stack and target a tag-extended RISC-V core. Our results show that SCALPEL-created policies can reduce overprivilege by orders of magnitude with hundreds of logical compartments while imposing low overheads (<5%).

Machine Learning to Design an Auto-tuning System for the Best Compressed Format Detection for Parallel Sparse Computations

Many applications in scientific computing process very large sparse matrices on parallel architectures. The presented work in this paper is a part of a project where our general aim is to develop an auto-tuner system for the selection of the best matrix compression format in the context of high-performance computing. The target smart system can automatically select the best compression format for a given sparse matrix, a numerical method processing this matrix, a parallel programming model and a target architecture. Hence, this paper describes the design and implementation of the proposed concept. We consider a case study consisting of a numerical method reduced to the sparse matrix vector product (SpMV), some compression formats, the data parallel as a programming model and, a distributed multi-core platform as a target architecture. This study allows extracting a set of important novel metrics and parameters which are relative to the considered programming model. Our metrics are used as input to a machine-learning algorithm to predict the best matrix compression format. An experimental study targeting a distributed multi-core platform and processing random and real-world matrices shows that our system can improve in average up to 7% the accuracy of the machine learning.

A Transformation-Based Quantum Physical Synthesis Approach for Nearest-Neighbor Architectures

The physical synthesis concept for quantum circuits, the interaction between synthesis and physical design processes, was first introduced in our previous work. This concept inspires us to propose some techniques that can minimize the number of extra inserted SWAP operations required to run a circuit on a nearest-neighbor architecture. Minimizing the number of SWAP operations potentially decreases the latency and error probability of a quantum circuit. Focusing on this concept, we present a physical synthesis technique based on transformation rules to decrease the number of SWAP operations in nearest-neighbor architectures. After the qubits of a circuit are mapped onto the physical qubits provided by the target architecture, our procedure is fed by this mapping information. Our method uses the obtained placement and scheduling information to apply some transformation rules to the original netlist to decrease the number of extra SWAP gates required for running the circuit on the architecture. We follow two policies in applying a transformation rule, greedy and simulated-annealing-based policies. Simulation results show that the proposed technique decreases the average number of extra SWAP operations by about 20.6% and 24.1% based on greedy and simulated-annealing-based policies, respectively, compared with the best in the literature.

Development of an Enterprise Architecture for Healthcare using TOGAF ADM

Hospital is one of the most complex organization with highly intensive interaction between stakeholders (patients, nurses, doctors, staff, etc.). In the operation of a hospital, the use of Information technology has been proven to improve effectiveness and efficiency. However, in the majority of cases, the processes to achieve the Strategic Objectives through implementation of Information Technology are full of challenges. Based on the case study in Dharmais Cancer Hospital, there are many symptoms that are identified by this study and lead to 4 issues, namely: lack of ownership from Business users, lack of alignment between business strategy and IT strategy, lack of awareness to use IT as a tool for competitive advantage, and low quality of IT operation performances. In order to solve the issues and support the achievement of Strategic Business Objective through IT, an Enterprise Architecture approach can be used to develop baseline architecture, identify the target architecture, finding the gap, and use the gap as recommendation to solve those issues. The methodology chosen is TOGAF ADM, based on its focus on processes and its flexibility to combine artifacts and approaches that are most suitable for the case. This study develops 7 recommendations to Strengthen Business area of organization, 5 recommendations to Align IT plan with Business Strategy, 16 recommendations to Implement several IT solutions as Competitive Advantage for organization, and 8 recommendations to provide higher performances by enabling Service Management approach for IT Operation. This study also shows how TOGAF ADM can improve the awareness of the business users to the business itself. Doi: 10.28991/esj-2021-01278 Full Text: PDF

Polyoxazolines with a Vicinally Double-Bioactivated Terminus for Biomacromolecular Affinity Assessment

Interactions between proteins and carbohydrates with larger biomacromolecules, e.g., lectins, are usually examined using self-assembled monolayers on target gold surfaces as a simplified model measuring setup. However, most of those measuring setups are either limited to a single substrate or do not allow for control over ligand distance and spacing. Here, we develop a synthetic strategy, consisting of a cascade of a thioesterification, native chemical ligation (NCL) and thiol-ene reaction, in order to create three-component polymer conjugates with a defined double bioactivation at the chain end. The target architecture is the vicinal attachment of two biomolecule residues to the α telechelic end point of a polymer and a thioether group at the ω chain end for fixating the conjugate to a gold sensor chip surface. As proof-of-principle studies for affinity measurements, we demonstrate the interaction between covalently bound mannose and ConA in surface acoustic wave (SAW) and surface plasmon resonance (SPR) experiments.

Sustainable Government Enterprise Architecture Framework

The suitable utility of driving the enterprise architecture exercise is to utilize the enterprise architecture framework as the fundamental guidance. But there are some challenges of applying those frameworks for government and their agencies because most of the frameworks have concentrated focus for the private sector which some fundamentally requirement of government would be specifically different. This paper aims to propose that the sustainable government enterprise architecture framework specifically applies for the national strategic planning in the optimum exercise process and clarity guidance for the information technology organization being able to transform and improve their services for an achievable adaptation efficiency, simplification, cost management, collaboration, shareability, and standardization which accommodate the rapidly changing service usability on digitalization known as “e-Government.” The fundamental design idea of this proposed framework has identified five keys principles, which are (1) legislation support, (2) top-down target architecture, (3) architecture governance, (4) shared services, and (5) cross-organization collaboration that would be considered as the key critical success factors for achieving the exercise. The overall response of the specific expert survey of this proposed framework has demonstrated the consensus responded at 90 percentage agreeable, which would strongly consider this framework applicable for groups of developing countries as the baseline framework for their digitalized transformation.

Automation of Network Services for the Future Internet

Internet service providers are shifting to an open, modern, software-based architecture that enables both new operating and business models. The target architecture is loosely coupled, cloud-native, data and artificial intelligence-driven, and relies on traffic engineering-related protocols to get the full potential of the network capabilities. The components need to use standard interfaces to be easily procured and deployed without the need for customization. Achieving these goals will require a significant change in how the network resources are architected, built, procured, licensed, and maintained. Some levers to drive this transformation rely on adopting open protocols such as NETCONF/RESTCONF or gNMI to operate the network and use standard data models to interact with the network more programmatically. This chapter presents such architecture, including service provider experiences.