Reactive defense mechanisms, such as intrusion detection systems, have made significant efforts to secure a system or network for the last several decades. However, the nature of reactive security ...mechanisms has limitations because potential attackers cannot be prevented in advance. We are facing a reality with the proliferation of persistent, advanced, intelligent attacks while defenders are often way behind attackers in taking appropriate actions to thwart potential attackers. The concept of moving target defense (MTD) has emerged as a proactive defense mechanism aiming to prevent attacks. In this work, we conducted a comprehensive, in-depth survey to discuss the following aspects of MTD: key roles, design principles, classifications, common attacks, key methodologies, important algorithms, metrics, evaluation methods, and application domains. We discuss the pros and cons of all aspects of MTD surveyed in this work. Lastly, we highlight insights and lessons learned from this study and suggest future work directions. The aim of this paper is to provide the overall trends of MTD research in terms of critical aspects of defense systems for researchers who seek to develop proactive, adaptive MTD mechanisms.
The concept of trust and/or trust management has received considerable attention in engineering research communities as trust is perceived as the basis for decision making in many contexts and the ...motivation for maintaining long-term relationships based on cooperation and collaboration. Even if substantial research effort has been dedicated to addressing trust-based mechanisms or trust metrics (or computation) in diverse contexts, prior work has not clearly solved the issue of how to model and quantify trust with sufficient detail and context-based adequateness. The issue of trust quantification has become more complicated as we have the need to derive trust from complex, composite networks that may involve four distinct layers of communication protocols, information exchange, social interactions, and cognitive motivations. In addition, the diverse application domains require different aspects of trust for decision making such as emotional, logical, and relational trust. This survey aims to outline the foundations of trust models for applications in these contexts in terms of the concept of trust, trust assessment, trust constructs, trust scales, trust properties, trust formulation, and applications of trust. We discuss how different components of trust can be mapped to different layers of a complex, composite network; applicability of trust metrics and models; research challenges; and future work directions.
Achieving an improved understanding of catalyst properties, with ability to predict new catalytic materials, is key to overcoming the inherent limitations of metal oxide based gas sensors associated ...with rather low sensitivity and selectivity, particularly under highly humid conditions. This study introduces newly designed bimetallic nanoparticles (NPs) employing bimetallic Pt‐based NPs (PtM, where M = Pd, Rh, and Ni) via a protein encapsulating route supported on mesoporous WO3 nanofibers. These structures demonstrate unprecedented sensing performance for detecting target biomarkers (even at p.p.b. levels) in highly humid exhaled breath. Sensor arrays are further employed to enable pattern recognition capable of discriminating between simulated biomarkers and controlled breath. The results provide a new class of multicomponent catalytic materials, demonstrating potential for achieving reliable breath analysis sensing.
Effective strategy to readily synthesize highly dispersed Pt‐based bimetallic (PtM, where M = Pd, Rh, and Ni) NPs as a new class of active catalysts is successfully developed on the highly porous architecture of 1D WO3 nanofibers via a protein template, i.e., apoferritin, in combination with the electrospinning method for superior exhaled‐breath sensors.
Many systems or applications have been developed for distributed environments with the goal of attaining multiple objectives in the face of environmental challenges such as high dynamics/hostility or ...severe resource constraints (e.g., energy or communications bandwidth). Often the multiple objectives are conflicting with each other, requiring optimal tradeoff analyses between the objectives. This paper is mainly concerned with how to model multiple objectives of a system and how to optimize their performance. We first conduct a comprehensive survey of the state-of-the-art modeling and solution techniques to solve multi-objective optimization problems. In addition, we discuss pros and cons of each modeling and optimization technique for in-depth understanding. Further, we classify existing approaches based on the types of objectives and investigate main problem domains, critical tradeoffs, and key techniques used in each class. We discuss the overall trends of the existing techniques in terms of application domains, objectives, and techniques. Further, we discuss challenging issues based on the inherent nature of multi-objective optimization problems. Finally, we suggest future work directions in terms of what critical design factors should be considered to design and analyze a system with multiple objectives.
Metal oxide nanosheets having high mesoporosity, grain size distribution of 5–10 nm, and ultrathin thickness have attracted much attention due to their intriguing properties such as high ...surface‐to‐volume ratio and superior chemical activities. However, 2D nanostructures tend to restack, inducing a decrease in accessible surface area and a number of pores. To solve this problem, herein, a unique synthetic method of crumpled metal oxide nanosheets using spray pyrolysis of metal ion–coated graphene oxide, followed by heat treatment, is reported. This method is applicable not only to single‐component metal oxides but also to heterogeneous multicomponent metal oxides in which composition can be controlled. Crumpled SnO2, ZnO, and Co3O4 as well as SnO2/ZnO and SnO2/Co3O4 nanosheets with heterogeneous interfaces are successfully synthesized and used as superior gas sensing layers. Because of the abundant reaction sites, well‐developed porosity for high gas accessibility, the formation of heterojunctions, the crumpled SnO2/ZnO and SnO2/Co3O4 nanosheets exhibit outstanding sensing performance (Rair/Rgas = 20.25 toward 5 ppm formaldehyde, and Rair/Rgas = 14.13 toward 5 ppm acetone, respectively). This study can contribute to the realization of a family of heterogeneous crumpled metal oxide nanosheets that can be applied to various research fields.
A general synthetic platform of hierarchically structured holey metal oxide nanosheets is achieved via a graphene oxide templating route and spray pyrolysis technique. The crumpled heterogeneous 2D metal oxide (crumpled H_2D MO) as a sensing layer exhibits improved sensing performance of formaldehyde (crumpled 2D SnO2/ZnO) and acetone (crumpled 2D SnO2/Co3O4) molecules due to the high porosity, surface area, and heterojunction effect.
A Survey on Systems Security Metrics Pendleton, Marcus; Garcia-Lebron, Richard; Cho, Jin-Hee ...
ACM computing surveys,
02/2017, Letnik:
49, Številka:
4
Journal Article
Recenzirano
Odprti dostop
Security metrics have received significant attention. However, they have not been systematically explored based on the understanding of attack-defense interactions, which are affected by various ...factors, including the degree of system vulnerabilities, the power of system defense mechanisms, attack (or threat) severity, and situations a system at risk faces. This survey particularly focuses on how a system security state can evolve as an outcome of cyber attack-defense interactions. This survey concerns how to measure system-level security by proposing a security metrics framework based on the following four sub-metrics: (1) metrics of system vulnerabilities, (2) metrics of defense power, (3) metrics of attack or threat severity, and (4) metrics of situations. To investigate the relationships among these four sub-metrics, we propose a hierarchical ontology with four sub-ontologies corresponding to the four sub-metrics and discuss how they are related to each other. Using the four sub-metrics, we discuss the state-of-art existing security metrics and their advantages and disadvantages (or limitations) to obtain lessons and insight in order to achieve an ideal goal in developing security metrics. Finally, we discuss open research questions in the security metrics research domain and we suggest key factors to enhance security metrics from a system security perspective.
The Cancer Genome Atlas (TCGA) project recently uncovered four molecular subtypes of gastric cancer: Epstein-Barr virus (EBV), microsatellite instability (MSI), genomically stable (GS), and ...chromosomal instability (CIN). However, their clinical significances are currently unknown. We aimed to investigate the relationship between subtypes and prognosis of patients with gastric cancer.
Gene expression data from a TCGA cohort (
= 262) were used to develop a subtype prediction model, and the association of each subtype with survival and benefit from adjuvant chemotherapy was tested in 2 other cohorts (
= 267 and 432). An integrated risk assessment model (TCGA risk score) was also developed.
EBV subtype was associated with the best prognosis, and GS subtype was associated with the worst prognosis. Patients with MSI and CIN subtypes had poorer overall survival than those with EBV subtype but better overall survival than those with GS subtype (
= 0.004 and 0.03 in two cohorts, respectively). In multivariate Cox regression analyses, TCGA risk score was an independent prognostic factor HR, 1.5; 95% confidence interval (CI), 1.2-1.9;
= 0.001. Patients with the CIN subtype experienced the greatest benefit from adjuvant chemotherapy (HR, 0.39; 95% CI, 0.16-0.94;
= 0.03) and those with the GS subtype had the least benefit from adjuvant chemotherapy (HR, 0.83; 95% CI, 0.36-1.89;
= 0.65).
Our prediction model successfully stratified patients by survival and adjuvant chemotherapy outcomes. Further development of the prediction model is warranted.
Managing trust in a distributed Mobile Ad Hoc Network (MANET) is challenging when collaboration or cooperation is critical to achieving mission and system goals such as reliability, availability, ...scalability, and reconfigurability. In defining and managing trust in a military MANET, we must consider the interactions between the composite cognitive, social, information and communication networks, and take into account the severe resource constraints (e.g., computing power, energy, bandwidth, time), and dynamics (e.g., topology changes, node mobility, node failure, propagation channel conditions). We seek to combine the notions of "social trust" derived from social networks with "quality-of-service (QoS) trust" derived from information and communication networks to obtain a composite trust metric. We discuss the concepts and properties of trust and derive some unique characteristics of trust in MANETs, drawing upon social notions of trust. We provide a survey of trust management schemes developed for MANETs and discuss generally accepted classifications, potential attacks, performance metrics, and trust metrics in MANETs. Finally, we discuss future research areas on trust management in MANETs based on the concept of social and cognitive networks.
The accurate measurement of security metrics is a critical research problem, because an improper or inaccurate measurement process can ruin the usefulness of the metrics. This is a highly challenging ...problem, particularly when the ground truth is unknown or noisy. In this paper, we measure five malware detection metrics in the absence of ground truth, which is a realistic setting that imposes many technical challenges. The ultimate goal is to develop principled, automated methods for measuring these metrics at the maximum accuracy possible. The problem naturally calls for investigations into statistical estimators by casting the measurement problem as a statistical estimation problem. We propose statistical estimators for these five malware detection metrics. By investigating the statistical properties of these estimators, we characterize when the estimators are accurate, and what adjustments can be made to improve them under what circumstances. We use synthetic data with known ground truth to validate these statistical estimators. Then, we employ these estimators to measure five metrics with respect to a large data set collected from VirusTotal.
Tumor recurrence following treatment is the major cause of mortality for glioblastoma multiforme (GBM) patients. Thus, insights on the evolutionary process at recurrence are critical for improved ...patient care. Here, we describe our genomic analyses of the initial and recurrent tumor specimens from each of 38 GBM patients. A substantial divergence in the landscape of driver alterations was associated with distant appearance of a recurrent tumor from the initial tumor, suggesting that the genomic profile of the initial tumor can mislead targeted therapies for the distally recurred tumor. In addition, in contrast to IDH1-mutated gliomas, IDH1-wild-type primary GBMs rarely developed hypermutation following temozolomide (TMZ) treatment, indicating low risk for TMZ-induced hypermutation for these tumors under the standard regimen.
Display omitted
•Distant recurrence predicts branched evolution of the paired tumors•Distant recurrence frequently involves divergence in key GBM driver alterations•Recurrent GBMs have more aberrations in core GBM driver pathways than initial GBMs•TMZ-induced hypermutation is rare in IDH1-wild-type primary GBMs
Kim et al. find that glioblastomas recurring at distant sites have driver genetic alterations very different from those of matched initial tumors. They also show that, in contrast to IDH1-mutated tumors, IDH1-wild-type primary glioblastomas rarely develop hypermutation following temozolomide treatment.
PDF
