The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

Silver nanoparticles (AgNPs) can be synthesized from a variety of techniques including physical, chemical and biological routes. They have been widely used as nanomaterials for manufacturing cosmetic and healthcare products, antimicrobial textiles, wound dressings, antitumor drug carriers, etc. due to their excellent antimicrobial properties. Accordingly, AgNPs have gained access into our daily life, and the inevitable human exposure to these nanoparticles has raised concerns about their potential hazards to the environment, health, and safety in recent years. From in vitro cell cultivation tests, AgNPs have been reported to be toxic to several human cell lines including human bronchial epithelial cells, human umbilical vein endothelial cells, red blood cells, human peripheral blood mononuclear cells, immortal human keratinocytes, liver cells, etc. AgNPs induce a dose-, size- and time-dependent cytotoxicity, particularly for those with sizes ≤10 nm. Furthermore, AgNPs can cross the brain blood barrier of mice through the circulation system on the basis of in vivo animal tests. AgNPs tend to accumulate in mice organs such as liver, spleen, kidney and brain following intravenous, intraperitoneal, and intratracheal routes of administration. In this respect, AgNPs are considered a double-edged sword that can eliminate microorganisms but induce cytotoxicity in mammalian cells. This article provides a state-of-the-art review on the synthesis of AgNPs, and their applications in antimicrobial textile fabrics, food packaging films, and wound dressings. Particular attention is paid to the bactericidal activity and cytotoxic effect in mammalian cells.

Bactericidal and Cytotoxic Properties of Silver Nanoparticles.

Solid composite electrolytes (SCEs) that combine the advantages of solid polymer electrolytes (SPEs) and inorganic ceramic electrolytes (ICEs) present acceptable ionic conductivity, high mechanical strength, and favorable interfacial contact with electrodes, which greatly improve the electrochemical performance of all-solid-state batteries compared to single SPEs and ICEs. However, there are many challenges to overcome before the practical application of SCEs, including the low ionic conductivity less than 10-3 S cm-1 at ambient temperature, poor interfacial stability, and high interfacial resistance, which greatly restrict the room temperature performance. Herein, the advances of SCEs applied in all-solid-state lithium batteries are presented, including the Li ion migration mechanism of SCEs, the strategies to enhance the ionic conductivity of SCEs by various morphologies of ICEs, and construction methods of the low resistance and stable interfaces of SCEs with both cathode and anode. Finally, some typical applications of SCEs in lithium batteries are summarized and future development directions are prospected. This work presents how it is quite significant to further enhance the ionic conductivity of SCEs by developing the novel SPEs with the special morphology of ICEs for advanced all-solid-state lithium batteries.

https://onlinelibrary.wiley.com/doi/epdf/10.1002/advs.201903088

Progress and Perspective of Ceramic/Polymer Composite Solid Electrolytes for Lithium Batteries

Safety is the most important requirement for autonomous vehicles; hence, the ultimate challenge of designing an edge computing ecosystem for autonomous vehicles is to deliver enough computing power, redundancy, and security so as to guarantee the safety of autonomous vehicles. Specifically, autonomous driving systems are extremely complex; they tightly integrate many technologies, including sensing, localization, perception, decision making, as well as the smooth interactions with cloud platforms for high-definition (HD) map generation and data storage. These complexities impose numerous challenges for the design of autonomous driving edge computing systems. First, edge computing systems for autonomous driving need to process an enormous amount of data in real time, and often the incoming data from different sensors are highly heterogeneous. Since autonomous driving edge computing systems are mobile, they often have very strict energy consumption restrictions. Thus, it is imperative to deliver sufficient computing power with reasonable energy consumption, to guarantee the safety of autonomous vehicles, even at high speed. Second, in addition to the edge system design, vehicle-to-everything (V2X) provides redundancy for autonomous driving workloads and alleviates stringent performance and energy constraints on the edge side. With V2X, more research is required to define how vehicles cooperate with each other and the infrastructure. Last, safety cannot be guaranteed when security is compromised. Thus, protecting autonomous driving edge computing systems against attacks at different layers of the sensing and computing stack is of paramount concern. In this paper, we review state-of-the-art approaches in these areas as well as explore potential solutions to address these challenges.

Edge Computing for Autonomous Driving: Opportunities and Challenges

Hydrogen atom makes graphene magnetic Graphene has many extraordinary mechanical and electronic properties, but it's not magnetic. To make it so, the simplest strategy is to modify its electronic structure to create unpaired electrons. Researchers can do that by, for example, removing individual carbon atoms or adsorbing hydrogen onto graphene. This has to be done in a very controlled way because of a peculiarity of the graphene's crystal lattice, which consists of two sublattices. Gonzales-Herrero et al. deposited a single hydrogen atom on top of graphene and used scanning tunneling microscopy to detect magnetism on the sublattice lacking the deposited atom (see the Perspective by Hollen and Gupta). Science, this issue p. 437; see also p. 415 Scanning tunneling microscopy shows that a hydrogen atom deposited on graphene makes the complementary sublattice magnetic. [Also see Perspective by Hollen and Gupta] Isolated hydrogen atoms absorbed on graphene are predicted to induce magnetic moments. Here we demonstrate that the adsorption of a single hydrogen atom on graphene induces a magnetic moment characterized by a ~20–millielectron volt spin-split state at the Fermi energy. Our scanning tunneling microscopy (STM) experiments, complemented by first-principles calculations, show that such a spin-polarized state is essentially localized on the carbon sublattice opposite to the one where the hydrogen atom is chemisorbed. This atomically modulated spin texture, which extends several nanometers away from the hydrogen atom, drives the direct coupling between the magnetic moments at unusually long distances. By using the STM tip to manipulate hydrogen atoms with atomic precision, it is possible to tailor the magnetism of selected graphene regions.

/pdf/atomic-scale-control-of-graphene-magnetism-by-using-hydrogen-53d9rq6gri.pdf

Atomic-scale control of graphene magnetism by using hydrogen atoms

Obtaining detailed software execution information via hardware performance counters is a powerful analysis technique. The performance counters provide an effective method to monitor program behaviors; hence performance bottlenecks due to hardware architecture or software design and implementation can be identified, isolated and improved on. The granularity and overhead of the monitoring mechanism, however, are paramount to proper analysis. Many prior designs have been able to provide performance counter monitoring with inherited drawbacks such as intrusive code changes, a slow timer system, or the need for a kernel patch. In this paper, we present K-LEB (Kernel - Lineage of Event Behavior), a new monitoring mechanism that can produce precise, non-intrusive, low overhead, periodic performance counter data using a kernel module based design. Our proposed approach has been evaluated on three different case studies to demonstrate its effectiveness, correctness and efficiency. By moving the responsibility of timing to kernel space, K-LEB can gather periodic data at a 100μs rate, which is 100 times faster than other comparable performance counter monitoring approaches. At the same time, it reduces the monitoring overhead by at least 58.8%, and the difference between the recorded performance counter readings and those of other tools are less than 0.3%.

High Frequency Performance Monitoring via Architectural Event Measurement

Biometric applications become paramount across private sectors, industry, as well as government agencies. As large amount of data being collected from many different sources, managing such volumes of data and developing efficient and effective large-scale operational solutions are becoming a concern. For example, real-time identification of individuals with the purpose of allowing or denying their access to specific system or resource is challenging from the performance point of view. In addition, processing large amount of data would definitely consume a significant amount of energy. The Single-chip Cloud Computer (SCC) is an experimental processor created by Intel Labs. In this paper we employ SCC, which supports dynamic frequency and voltage scaling (DVFS), to investigate the power-aware computing and performance enhancement of an iris matching algorithm on such many-core architecture. This biometric application contains a large degree of parallelism that we can exploit by porting it onto the SCC. Results in terms of performance, power, energy, energy delay product (EDP), and power per speedup (PPS) metrics of executing the iris matching application under different number of cores, frequency, and voltage settings of the SCC platform are presented. We also analyze how the results for these metrics vary as we change these parameters.

/pdf/a-power-aware-study-of-iris-matching-algorithms-on-intel-s-1qwhcb7rdv.pdf

A Power-Aware Study of Iris Matching Algorithms on Intel's SCC

The Simultaneous Multithreading (SMT) architecture improves the resource efficiency via scheduling and executing concurrent threads in the same core. Moreover, fetch policies are proposed to assign priorities in the fetch stage to manage the shared resources. However, power consumption study is omitted in most fetch policies. On the other hand, the power management schemes nowadays are focused on multicore processors. Given the growing demands to manage the power consumption of processors and the fully shared system resources in SMT environment, it requires detailed research to develop the power management in an SMT processor. This paper proposes a power aware fetch policy PCOUNT, which evaluates the power consumption for two categories in SMT: computation resources and memory accessing resources. PCOUNT fetches from the thread with lowest evaluated power consumption in every CPU cycle, in order to reduce overall power consumption. Furthermore, this paper justifies studied fetch polices using power efficiency, which is calculated as evaluated power consumption per unit system throughput. As a result, PCOUNT improves power efficiency over ICOUNT by 26% and over DWarn by 31% on average. Meanwhile, PCOUNT is able to achieve better overall system throughput and average thread improvement than ICOUNT and DWarn.

/pdf/pcount-a-power-aware-fetch-policy-in-simultaneous-1ku3h06qh5.pdf

PCOUNT: A power aware fetch policy in Simultaneous Multithreading processors

In situ study on the thermal stability and interfaces properties of Er 2 O 3 /Al 2 O 3 /Si multi stacked films by X-ray photoelectron spectroscopy

Even though attaining high performance has been the user's pursuit traditionally, in the many-core era, the emphasis has shifted towards controlling the power and energy consumption, so as to maintain a satisfying performance while consuming an acceptable amount of energy. This paper describes an auto-tuning algorithm for the energy efficiency optimization of many-core platform, in this case, a Graphic Processing Unit (GPU). We employed gradient descent algorithm as the basis for this optimization. Metrics such as energy and energy delay product (EDP) are examined using programs representing different types of workloads such as sequential, parallel and hybrid. Based on the experimental results, our method achieves the level of savings over 15% in terms of energy consumption when compared with the default on-board governors that also adjust the voltage and frequency of the GPU. Our approach shows an advantage when optimizing towards EDP as well. This shows the effectiveness of our proposed approach.

Chen Liu

Papers

High Frequency Performance Monitoring via Architectural Event Measurement

A Power-Aware Study of Iris Matching Algorithms on Intel's SCC

PCOUNT: A power aware fetch policy in Simultaneous Multithreading processors

In situ study on the thermal stability and interfaces properties of Er 2 O 3 /Al 2 O 3 /Si multi stacked films by X-ray photoelectron spectroscopy

Energy-Aware Automatic Tuning of Many-Core Platform via Gradient Descent