《CS259D:数据挖掘与网络安全》笔记说明

作者:Leo

本笔记是对课程CS 259D中涉及的论文和讲义的扩展,建议阅读原始论文和讲义。

Github: CS259D_Notes_HW_cn GitBook: CS259D Notes cn

  • 课程笔记
    • 介绍
    • 僵尸网络
    • 内部威胁
    • 生物行为特征
    • 网络安全
    • 网络钓鱼检测
    • 自动警报关联
    • 多分类器系统,入侵检测系统(IDS)
    • 深度包检测
    • 多态性
    • 在安全领域使用机器学习
    • 机器学习的敌人
    • 工业界做客讲座报告
  • 作业
    • 作业1
    • 作业2
    • 作业3
    • 作业4

课程笔记

介绍

  • 信息安全概述,当前的安全形势,安全领域数据挖掘案例

僵尸网络

  • 僵尸网络拓扑结构, 使用 NetFlow 检测僵尸网络
    • Lecture 2
    • BotMiner: Clustering Analysis of Network Traffic for Protocol- and Structure- Independent Botnet Detection
    • BotFinder: Finding Bots in Network Traffic Without Deep Packet Inspection
  • 使用 DNS 检测僵尸网络
    • Lecture 3
    • EXPOSURE: Finding Malicious Domains Using Passive DNS Analysis (2011)

内部威胁

  • 内部威胁简介,伪装检测策略
    • Lecture 3
    • One-class Training for Masquerade Detection (2003)

生物行为特征

  • 基于行为和认知生物特征的主动认证
    • Lecture 4
    • An examination of user behavior for re-authentication (M. Pusara’s PhD thesis,2007)
  • 基于鼠标动态信息分析的主动认证
    • Lecture 5
    • Continuous authentication for mouse dynamics: A pattern-growth approach (Shen C, Cai Z, Guan X. 2012)
    • Lecture 7
    • An Efficient User Verification System via Mouse Movements, 2011
  • 基于触摸和滑动模式分析的移动端主动认证
    • Lecture 7
    • Touchalytics: On the Applicability of Touchscreen Input as a Behavioral Biometric for Continuous Authentication, 2013

网络安全

  • 基于Web服务器日志分析的Web威胁检测
    • Lecture 8
    • A multi-model approach to the detection of web-based attacks, 2005
  • 网络安全警报聚类
    • Lecture 12
    • Using Generalization and Characterization Techniques in the Anomaly-based Detection of Web Attacks, Robertson et al., 2006

网络钓鱼检测

  • 钓鱼邮件和钓鱼网站检测
    • Lecture 16
    • Learning to Detect Phishing Emails, Fette et al, 2007
    • Cantina: A content-based approach to detecting phishing websites, Zhang et al, 2007

自动警报关联

  • Building attack scenarios from individual alerts correlation
    • Lecture 20
    • A Comprehensive Approach to Intrusion Detection Alert Correlation, Valeur et al, 2004

多分类器系统,入侵检测系统(IDS)

  • 多分类系统(MCS)概述,MCS在安全分析中的优势
    • Lecture 10
    • Adaptive Intrusion Detection System via Online Learning, 2012

深度包检测

  • 基于数据包载荷建模的网络入侵检测
    • Lecture 12
    • PAYL: Anomalous payload-based network intrusion detection, Wang-Stolfo 2004
  • 把多个 One-class 分类器用于数据包有效载荷建模和网络检测
    • Lecture 15
    • McPAD : A Multiple Classifier System for Accurate Payload-based Anomaly Detection, Perdisci et al, 2009

多态性

  • 多态混合攻击,无法为多态攻击建模
    • Lecture 14
    • Polymorphic Blending Attacks, Fogla et al, 2006
    • On the Infeasibility of Modeling Polymorphic Shellcode, Song et al, 2007

在安全领域使用机器学习

  • 在安全领域使用机器学习的挑战与实践指导
    • Lecture 13
    • Outside the closed world: On using machine learning for network intrusion detection, Sommer-Paxson, 2010
    • Challenging the Anomaly Detection Paradigm: A Provocative Discussion, Gates-Taylor, 2007
    • The Base-Rate Fallacy and Its Implications for the Difficulty of Intrusion Detection, Axelsson, 1999

机器学习的敌人

  • 机器学习的安全问题
    • Lecture 10
    • The security of machine learning, 2010

工业界做客讲座报告

  • Wells Fargo
    • Lecture 6
    • Guest speaker Avi Avivi, VP Enterprise Information Security Architecture at Wells Fargo
  • Union Bank
    • Lecture 9
    • Guest speaker Gary Lorenz, Chief Information Security Officer (CISO) and Managing Director at MUFG Union Bank
  • 安全数据挖掘在Google(流传较广的报告)
    • Lecture 11
    • Guest speaker Massimiliano Poletto, head of Google Security Monitoring Tools group
  • Industry Perspectives
    • Q&A with guest speaker Michael Fey, EVP and CTO of Intel Security Group (aka McAfee)

作业

作业1

  • 作业 1. 僵尸网络
  • 作业 2. Anomaly Detection via “Eigenface” of Command History
  • 作业 3. Continuous Authentication via Biometric Behavior

作业2

  • 作业 1. 测验
  • 作业 2. 触摸信息识别
  • 作业 3. 熵在攻击检测/诊断中的使用

作业3

  • 电子邮件抓包分析

作业4

  • 测验

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