Module Introduction

SiCAP-Data Analysis, based on dat山和a, scenario-oriented and al分少gorithm-supported, condu家船cts comprehensive inte答森lligent analysis of IT as做錯set configuration, monito民遠ring, operation, logs, 笑麗processes and oth志商er data based on big data, machine l視看earning, deep learning and o兒體ther technologies, including landing sc科河enarios in multiple technological作理 directions such as anomalous ris場請k analysis, multi-dimen唱個sional primary cause, root caus道還e analysis, intelligent a也鄉uditing, intell森從igent operation, intellig睡小ent prediction, and intelligent近事 robotic assistants, wh近女ich improves the overall risk perc短都eption and security dynamic pr水體otection.

Feature Introduction

• Unusual Risk Analysis

  Key Inclusions:Log anom技輛aly detection: based on log clu自我stering, pattern recognition and o器要ther machine learning techniqu朋鄉es and algorithms to disc門錢over abnormal logs and p路跳otential risks.
  Abnormal Behavior師線 Analysis: Establish a b他北ehavioral baseline, correlate有吃 user and asset 麗年behaviors, and use machine learni呢下ng and other algorithms to iden花時tify suspicious abnormal behaviors他廠 that seriously deviate from the bas鄉相eline.
  Threat Attack Monit我視oring: Based on networ去為k traffic, apply artificial intell做銀igence technologies and algor看醫ithms such as machine 我機learning, deep learning, e業動tc. to backtrack and ana了行lyze abnormal network behaviors,黑笑 and discover potential security thr化自eats and unknown network attacks b白了y matching them with訊作 threat intelligence and behavi用很oral models.
• Multidimensional Principal Cause A們個nalysis

  It is mainly a multi-dimen開答sional principal cause analys妹人is of traffic eve站電nts that can identify the main dime子飛nsions that generate traffic a綠拿nomalies.
• Root Cause Analysis女話

  For alarms or anomalo爸子us events, combined with net樹年work topology, ass金一et and service correlation relationship習事s, and fault transmissi空高on relationships, intelligent al站放gorithms such as decision tre樹她es and correlation analysis are appli化影ed to locate the root cause of the鄉是 problem and effectively用可 shorten the fault r這數esolution time.
• Intelligent Audit

  Apply big data and machine learnin頻月g algorithms to operation ses一如sions and historical audit records報用, form a rule base by analyzing農機 character commands 兒多and user behaviors, audit火理 operation comman森是ds and behaviors to s但關ee if they are nor用和mal by matching the rule bas妹海e, carry out intell子們igent auditing o愛土f operation sessions, provide intellige我女nt scoring and health level, assist au媽從dit administrators in their d內算aily audit work, and dynami業輛cally update the rule 些們base based on the final aud線熱it results.
• Intelligent Operation

  Key Inclusions：①　Operation A說拍uthorization Re件西commendation: Apply intell市內igent algorithms to recom行一mend authorization for new users ba林頻sed on historical authoriz用些ation, user roles, attributes, and a請技sset information for quic女快k authorization.。
  Rapid Dispatch Recomm樹物endation: When an asset malfunc分又tion or abnormality occurs, based on呢和 intelligent algorithms and aut哥錢omated scripts to col司能lect malfunction cha愛低racteristics, analyze t做很he cause of the malfunction, form海長 malfunction characteris資輛tics, and generate work order reco短友mmendation information based on thes都知e malfunction characteristi報用cs and historical 服劇operation behavi為視ors, which facilitates the rapid fo關匠rmation of special operation wo從媽rk orders for operation processing.
  運③　Operation Failure Solut請冷ion Recommendation: B筆女y analyzing historical opera了雪tion information and c個綠ombining the know靜劇ledge of operation solutions provid唱少ed by users to form an operation k術事nowledge base, we小我 recommend solutions 和什based on failure characteristics and 白日related historical operation inf又子ormation to assist users in quickly山計 resolving failures.。
• Intelligent Pred鐘農iction

  Relying on big data analysis and machin木讀e learning capabilities, it 要畫establishes a failu兵花re prediction model fo一相r business scenarios, and con數西ducts correlation analy吧物sis and deep lea快快rning based on the correlation of藍技 historical alarms. Meanwhil她我e, it is combined with the data acquir門市ed by the monitoring s海的ystem in real time to perform trend也會 analysis and prediction 好老of IT failures, capacity, etc.,黑自 to provide early warning of pos如兵sible future failures and realize i鄉長ntelligent prediction of f場來ailures.
• Intelligent Assistants

  It builds a bridge between informati村相on producers and information consumer訊愛s, adopts a high-performance computi年舞ng framework, organizes da事爸ta such as the collectio睡關n of users' his美船torical behaviors an舊人d functional correlations, establish老長es a user portrait 花花system based on m新南achine learning, data mining 國農and other technologies, integrates 資答a variety of algorithmic models, and m哥我akes all-round, multi-dimensional海相 and accurate predictions a理術nd recommendations of the離南 functions or contents req的船uired by users,時線 so as to reduce users' 白水operating costs.