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Smart Log Data Analytics: Techniques for Advanced Security Analysis

為了解決Incident event的問題，作者Skopik, Florian,Wurzenberger, Markus,Landauer, Max 這樣論述：

Florian Skopik is Head of the Cyber Security Research Program at the Austrian Institute of Technology (AIT) with a team comprising around 30 people. He spent 10+ years in cyber security research, before, and partly in parallel, another 15 years in software development. Nowadays, he coordinates natio

nal and large-scale international research projects, as well as the overall research direction of the team. His main interests are centered on critical infrastructure protection, smart grid security and national cyber security and defense. Since 2018, Florian further works as ISO 27001 Lead Auditor.

Before joining AIT in 2011, Florian was with the Distributed Systems Group at the Vienna University of Technology as a research assistant and post-doctoral research scientist from 2007 to 2011, where he was involved in a number of international research projects dealing with cross-organizational co

llaboration over the Web. In context of these projects, he also finished his PhD studies. Florian further spent a sabbatical at IBM Research India in Bangalore for several months. He published more than 125 scientific conference papers and journal articles and holds more than 50 industry recognized

security certifications, including CISSP, CISM, CISA, CRISC, and CCNP Security. In 2017 he finished a professional degree in Advanced Computer Security at the Stanford University, USA. Florian is member of various conference program committees and editorial boards and standardization groups, such as

ETSI TC Cyber and OASIS CTI. He frequently serves as reviewer for numerous high-profile journals, including Elsevier’s Computers & Security. He is registered subject matter expert of ENISA in the areas of new ICTs and emerging application areas as well as Critical Information Infrastructure Protect

ion (CIIP) and CSIRTs cooperation. In his career, he gave several keynote speeches, organized scientific panel discussions at flagship conferences, such as a smart grid security panel at the IEEE Innovative Smart Grid Technologies (ISGT) conference in Washington D.C., and acted as co-moderator of th

e National Austrian Cyber Security Challenge 2017, and as jury member of the United Nations Cyber Security Challenge 2019. Florian is IEEE Senior Member, Senior Member of the Association for Computing Machinery (ACM), Member of (ISC)2, Member of ISACA and Member of the International Society of Autom

ation (ISA).Markus Wurzenberger is a scientist and project manager at the Austrian Institute of Technology (AIT), located in Vienna, Austria. His main research interests are log data analysis with focus on anomaly detection and cyber threat intelligence (CTI). This includes the development of (i) no

vel machine learning that allow online processing of large amounts of log data to enable attack detection in real time, and (ii) artificial intelligence (AI) methods and concepts for extracting threat information from anomalies to automatically generate actionable and shareable CTI. Besides the invo

lvement in several national and international research projects, Markus is one of the key researchers working on AIT’s anomaly detection project AECID (Automatic Event Correlation for Incident Detection). Among the most prominent solutions developed within this project, Markus and his team created A

Miner, a software component for log analysis, which implements several anomaly detection algorithms and is included as package in the official Debian distribution. In 2016, Markus enrolled for his PhD studies in computer science at the Vienna University of Technology, with focus on anomaly detection

in computer log data. The subject of his PhD aligns with several national and international research projects AIT is involved in. In 2015 Markus obtained his Master’s Degree in Technical Mathematics at the Vienna University of Technology. Since 2014 he is a full-time researcher at AIT in the area o

f cyber security. Max Landauer finished his Bachelor’s Degree in Business Informatics at the Vienna University of Technology in 2016. In 2017, he joined the Austrian Institute of Technology (AIT), where he carried out his Master’s Thesis on clustering and time-series analysis of system log data. He

started his PhD studies as a cooperative project between the Vienna University of Technology and the Austrian Institute of Technology in 2018. For his dissertation, Max is working on an automatic threat intelligence mining approach that extracts actionable CTI from raw log data. The goal of this res

earch is to transform threat information shared by different organizations into abstract alert patterns that allow detection and classification of similar attacks. Moreover, Max is a maintainer of the logdata-anomaly-miner (AMiner), an Open-Source agent for parsing and analyzing all kinds of system

logs, that is developed at AIT and available in the Debian distribution. He is also contributing to multiple other tools that are part of AECID (Automatic Event Correlation for Incident Detection), a framework for all kinds of efficient and scalable log data analysis techniques such as parser genera

tion and log clustering. Max has multiple years of experience with nationally and internationally funded projects in numerous areas, including machine learning, artificial intelligence, cyber-physical systems, and digital service chains. He is currently employed as a Junior Scientist in the center f

or Digital Safety and Security at the Austrian Institute of Technology. His main research interests are log data analysis, anomaly detection, and cyber threat intelligence.

Incident event進入發燒排行的影片

An Integrated Approach For Uncovering Novel DNA Methylation Biomarkers For Non-small Cell Lung Carcinoma

為了解決Incident event的問題，作者VAIBHAV KUMAR SUNKARIA 這樣論述：

Introduction - Lung cancer is one of primal and ubiquitous cause of cancer related fatalities in the world. Leading cause of these fatalities is non-small cell lung cancer (NSCLC) with a proportion of 85%. The major subtypes of NSCLC are Lung Adenocarcinoma (LUAD) and Lung Small Cell Carcinoma (LUS

C). Early-stage surgical detection and removal of tumor offers a favorable prognosis and better survival rates. However, a major portion of 75% subjects have stage III/IV at the time of diagnosis and despite advanced major developments in oncology survival rates remain poor. Carcinogens produce wide

spread DNA methylation changes within cells. These changes are characterized by globally hyper or hypo methylated regions around CpG islands, many of these changes occur early in tumorigenesis and are highly prevalent across a tumor type.Structure - This research work took advantage of publicly avai

lable methylation profiling resources and relevant comorbidities for lung cancer patients extracted from meta-analysis of scientific review and journal available at PubMed and CNKI search which were combined systematically to explore effective DNA methylation markers for NSCLC. We also tried to iden

tify common CpG loci between Caucasian, Black and Asian racial groups for identifying ubiquitous candidate genes thoroughly. Statistical analysis and GO ontology were also conducted to explore associated novel biomarkers. These novel findings could facilitate design of accurate diagnostic panel for

practical clinical relevance.Methodology - DNA methylation profiles were extracted from TCGA for 418 LUAD and 370 LUSC tissue samples from patients compared with 32 and 42 non-malignant ones respectively. Standard pipeline was conducted to discover significant differentially methylated sites as prim

ary biomarkers. Secondary biomarkers were extracted by incorporating genes associated with comorbidities from meta-analysis of research articles. Concordant candidates were utilized for NSCLC relevant biomarker candidates. Gene ontology annotations were used to calculate gene-pair distance matrix fo

r all candidate biomarkers. Clustering algorithms were utilized to categorize candidate genes into different functional groups using the gene distance matrix. There were 35 CpG loci identified by comparing TCGA training cohort with GEO testing cohort from these functional groups, and 4 gene-based pa

nel was devised after finding highly discriminatory diagnostic panel through combinatorial validation of each functional cluster.Results – To evaluate the gene panel for NSCLC, the methylation levels of SCT(Secritin), FOXD3(Forkhead Box D3), TRIM58(Tripartite Motif Containing 58) and TAC1(Tachikinin

1) were tested. Individually each gene showed significant methylation difference between LUAD and LUSC training cohort. Combined 4-gene panel AUC, sensitivity/specificity were evaluated with 0.9596, 90.43%/100% in LUAD; 0.949, 86.95%/98.21% in LUSC TCGA training cohort; 0.94, 85.92%/97.37 in GEO 66

836; 0.91,89.17%/100% in GEO 83842 smokers; 0.948, 91.67%/100% in GEO83842 non-smokers independent testing cohort. Our study validates SCT, FOXD3, TRIM58 and TAC1 based gene panel has great potential in early recognition of NSCLC undetermined lung nodules. The findings can yield universally accurate

and robust markers facilitating early diagnosis and rapid severity examination.

Xing Danwen: Captive of Love

為了解決Incident event的問題，作者El Fetouh, Tarek Abou/ Koonchung, Chan (CON)/ Butler, Judith (CO 這樣論述：

A monograph on one of China's most accomplished and daring artists, this volume follows the transformation of Xing Danwen's career from 1989 to the present.Since 1989, when she began photographing the lives of artists squatting on the fringes of Beijing, Xing Danwen has forged a significant identity

in the Chinese art world. The exhibition and its accompanying catalogue, Captive of Love, focus on Xing's relationship to Beijing and feature works from all of her major series - Wall House, Urban Fiction, Thread, Because I am in the mountain, disCONNEXION, A Personal Diary, Sleep Walking, and Scro

ll. Recalling several threads from Jean Genet's final book, Prisoner of Love, which provides a prism for considering Xing's artistic practice, this wide-ranging monograph reveals Xing has never stopped developing as an artist. In every image she creates, Xing reconstructs reality, as if driven by a

compulsive desire to be at the center of the incident, approaching her characters with a marked sensuality. Through photographs, installations, and videos, Xing positions herself inside the event as a subject, a model, or a critical eye, creating a visual language that is both subversive and poetic.

TAREK ABOU EL FETOUH is an independent curator. His projects include the 2009 Sharjah Biennale; ＂Home Works 6＂, Beirut, 2013; ＂Lest the Two Seas Meet＂, Museum of Modern Art Warsaw, 2015; and ＂The Time is Out of Joint＂, Sharjah and Gwangju, 2016. Born in Cairo, El Fetouh currently lives and works

in Brussels.

資訊安全事件管理平台的自動化聯合防護阻擋機制之研究

為了解決Incident event的問題，作者劉鍵毅 這樣論述：

隨著台灣資通安全意識提升，國內許多企業、法人或公務機關，逐漸重視資訊安全的防護，導入資訊安全事件管理平台，使網路活動及日誌可視化，並集中於同一平台上，讓資安管理人員能直接在SIEM平台上直接看見許多設備的日誌，平時除了能主動查找異常日誌外，也能被動地建立規則條件及門檻值（Threshold）使日誌被規則關聯。在有了告警功能後，管理者便可以一目了然的看見告警的原因，再經由人工判斷，判斷是否需要將該事件的IP新增到具有阻擋功能之設備進行阻擋，或向具阻擋功能之資安設備管理者申請阻擋。本研究將實作開發自動化聯防阻擋程式，並在資訊安全事件管理平台上建立相關規則，並利用模擬真實事件發生時的日誌，在資訊安

全事件管理平台上模擬出設備日誌，將資訊安全事件管理平台所觸發相關規則之事件IP，透過自動化阻擋程式，將IP送至入侵偵測防禦系統（Intrusion Prevention System, IPS）黑名單進行阻擋，以符合自動化阻擋機制，並將阻擋程式之日誌送至SIEM進行監控，最後將整體機制呈現於結果。