Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Security-focused operating system wikipedia , lookup
Wireless security wikipedia , lookup
Unix security wikipedia , lookup
Computer security wikipedia , lookup
Mobile security wikipedia , lookup
Cyberattack wikipedia , lookup
Network tap wikipedia , lookup
Secure multi-party computation wikipedia , lookup
Computer and network surveillance wikipedia , lookup
Distributed firewall wikipedia , lookup
Deep packet inspection wikipedia , lookup
Network Security and Intrusion Detection Survey of the Art and Practice Dr. Michah Lerner AT&T Labs 15-August-2000 15-August-2000 AT&T Outline Model Principles Assumptions Methods Products No silver bullets Published sources only Note: this talk describes some attack models. If you’d like “try them out”, don’t! 15-August-2000 AT&T Intrusion Detection Systems, IDS Identified by Dorothy Denning in 1987 IEEE Software Engineering • Protect systems and networks from threats, vulnerabilities, and intrusions Art includes: • “Bro: A System for Detecting Network Intruders in Real • Time” (Vern Paxon) JiNao – Protect link state routing – Felix Wu Rule-based expert system, statistical analysis, protocol analysis, OSPF MIB, distributed programming interface (DPI) Vendors include: • • Amazon.com lists 171 security products Axent (NetProwler, and Tivoli modules), ISS, Network Associates, Cisco 15-August-2000 AT&T A Story … Jane the Dandelion wine merchant • Running SSL to protect her eCommerce site Coalition against Dandelion Wine • Quietly launches a chosen ciphertext attack • against her SSL server (Daniel Bleichenbacher, LNCS 1462, 1998) Exploit weakness in SSL V.3.0 Generate many authentication requests SSL reports which ones were incorrectly formatted The Coalition obtained her master secret! • They tested about one million chosen ciphertexts – on her server! • She just thought that SSL was slow! • IDS would have found incomplete SSL handshakes, and probably foiled the intruder 15-August-2000 AT&T Assumptions Assumptions … • RFC 1636 – encryption essential to security Open networks violate this assumption Encryption should protect control information, as well as contents See section 7.3 of the RFC • In attack from Vi net Vj assume only one of Vi, Vj is the attacker DDOS violates this assumption Assumptions are “sometimes” wrong • Replay attack can masquerade with encrypted data • Distributed attacks can leverage multiple attackers • Encryption can be broken 15-August-2000 AT&T Concept – Collection & Analysis CERN European Laboratory for Particle Physics Birth Place of “The Web Browser” – http://www.cern.ch Every time something suspicious is detected, the session’s security weight is increased When the security weight gets higher than a given threshold, detailed monitoring starts Encryption was, until recently, not allowed by the French law Not much used for first break-in discovery, but invaluable for security incident analysis and follow-up: it Security answers typical questions like: officer When did the first break-in happen? Which other systems may have Filter been attacked? Which other services on the attacked system may have been compromised? Reports Suspicious behavior Network Analyzer 15-August-2000 AT&T Data base Intrusion – Examples Denial of Service Hijacking of session or router Theft • Resources – bandwidth theft or blockage • Identity • Information 15-August-2000 AT&T Intrusion at any layer or slice Difficult and Complex Problem Application Static & dynamic page Quality of Service Media Transport Content Media MPEG etc. HTTP H.323 SIP RTSP RSVP RTCP Transport RTP TCP Physical Link Network UDP IPv4, IPv6 PPP SONET 15-August-2000 AAL3/4 AAL5 ATM PPP Ethernet AT&T V.34 Mobsters101 – How to Intrude Resources • Exhaust, overload or consume Control Functions • Undermine direct control protocols 1 For discussion purposes only Assert authentication or authorization contrary to policy Block authentication or authorization Subvert timing or other policing methods 1 • Undermine indirect control Transport Functions Transmit forged content Modify, Read or Block content “Many attackers use tools like COPS or SATAN, which automate the process of checking for known bugs in remote network systems. These freely available tools, as well as commercial tools such as ISS’s Internet Scanner, are designed to help systems administrators audit their own networks, but are equally useful to an attacker.” [Wallach99] See http://www.cert.org/advisories 15-August-2000 AT&T Intrusion – Definition Intrusion • Violation of the network policy, even where the policy is not completely stated Policy • Allocation, usage and return of resources Possibly multiple policies active on a network Varied requirements of business, administration or trust Resources • Finite • Independent • Layered • Protocol-driven 15-August-2000 Protocols • Efficient, not perfect • IP spoofing – packets are not uniquely attributable to the origin • Costly to stop AT&T Prevention – Policies & Assurances Violations of policy may define intrusion Except: • Seldom have such a precise policy in IP • The policy could be buggy • New applications could violate the policy • Cost is prohibitive for many applications • Can plug anything into the Internet – not just “safe” applications. IEEE 802.3 (Ethernet) is ubiquitous An alternative to formal policy is assurances • General policy, but less rigorous Availability – connections, bandwidth, low delay Integrity – privacy, reliability, and low error-rate 15-August-2000 AT&T Detection Assurances are threatened by: • Misuse – specific attack behavior Based on expert knowledge of patterns associated with attack Patterns of misuse defined by experts, or by machine learning – should not occur Examples: – Mismatched SYN/ACK – Same authenticated user from multiple locations? – Multiple failed authentications? From different address?? • Problem: only recognizes anticipated threats (but can combine several threats that might otherwise be missed) Anomalous use – possible attack Recognize increased risk to network Compare actual with expected behavior Load rising atypically? 15-August-2000 AT&T How to Protect the Assurances? Redundancy • Makes it harder to corrupt • Make it easier to identify corruption • May make it easier to locate the corruption Explicit redundancy: add to network or data • Tags and attributes • Input/output validation Implicit redundancy: already in the network • Anonymous – timing • Private – network attributes • Content – privacy and easily evaded • Per-protocol or general properties State-machine compliance? Frame-format? 15-August-2000 AT&T Two Keys to Protection Prevention Define multiple layers • Define behavior of each • • layer, including resources Enforce each behavior Prohibit actions that may compromise the behavior Examples • IP DDOS does not affect • • • • ATM integrity Replay of short-lifetime HTTP cookies is traceable Link-layer marking Ingress/egress filtering End-to-end coordination 15-August-2000 Detection Identify correct behavior Reinforce or augment • Redundancy Format (protocol) Augmentation (tags) Validations Characterize activities Recognize anomalies • Unusual transit duration, • • • AT&T route, or augmentation Item – invalid packet header Aggregate – bad path or invalid protocol sequence Honeypot traces Explicit Redundancy – Protection Content transformation • SSL • Cookies Protocol hardening against adversarial “errors” • • IPSec Invalid session properties (i.e. stale keys, invalid context or content) may indicate attack Packet augmentation • Security labels • Properties inherited from ingress • Requirements incumbent upon egress • Min/max trust and validation of information flow1 Management at Ingress/Egress • Interaction with authentication and multiple domains 15-August-2000 AT&T Implicit Redundancy – Detection Packet • Well-formed packets (protocol-compliant) • Well-defined packets (service behavior) • Source, destination, format May validate endpoints and actions Traffic profile • Acquire by observation of usage Statistical model – “distinctive characteristics (packet size, timing) … not on connection contents” Resists encryption, and preserves privacy Database of representative samples Does the traffic profile fit the source/destination profiles? 15-August-2000 AT&T General Technique Collect traffic and audit information • Protocol analysis • Various sensors Content-independent sensors may work even on encrypted data State-based sensors evaluate the trustworthiness of connection path State-free sensors operate without change to firewall or network-element Compute patterns of misuse or abuse Recognize patterns of a possible attack Previously observed or predicted attack patterns Uncharacteristic changes in predicted performance 15-August-2000 AT&T Information to Collect Audit information • • Management information bases (MIBS) and logs After-the-fact analysis of traffic artifacts Historical information • • Recognition of previously used contents, such as serial numbers, someone else’s password, etc. Strength of evidence follows the strength of the content source Distributed • Exchange data on suspected intrusions (IETF IDWG) • Information from IP authentication systems 15-August-2000 AT&T Information to Compute Attack signatures • Hard problem – needs attack models to organize data • Attacks are often distributed – requires coordination • ISS publishes about 350 Real Secure Signatures at http://www.iss.net Backdoors Denial of Service Distributed Denial of Service OS Sensor Suspicious Activity Unauthorized Access Attempts • Only three detect RIP attacks on routing • None of the published signatures mention streaming, VoIP, MPEG, Quality of Service, or attacks on OSPF 15-August-2000 AT&T Detailed Taxonomy Knowledge-based • Expert systems; Signature analysis • Petri nets; State-transition analysis Behavior-based • Statistics; Expert systems • Neural networks; “User Intention” model Source: IBM RZ 3176 (# 93222) 10/25/99 Computer Science/Mathematics (23 pages). A ReviseTaxonomy for Intrusion-Detection Systems by Hervé Debar, Marc Dacier, Andreas Wespi 15-August-2000 AT&T Information Collection Tools Tcpdump Bro NetMon Snort All can use rules 15-August-2000 AT&T Protocol Monitoring Validate Appropriate Traffic Flows: • Multiple granularities of description • Recognize change from the behavior Activation/deactivation of connections Correlation/evaluation of connection attributes How • Protocol scrubbing [InfoComm 2000] State machines for correct protocol flow Error states for erroneous traffic • • Pattern recognition Simulation/validation of expected behaviors Does the expected response follow, or something else? 15-August-2000 AT&T ASAX and Russel (RUle-baSed Sequence Evaluation Language) State full event detection Correlation of events across multiple hosts • consolidate intrusion evidence from several scattered sources and correlate them intelligently at a central location. automata Declarative Language Russel Rules FW-1 Router Internet ISP FUNDP Univ. Sniffer ASAX 15-August-2000 AT&T • SYN-Flood • IP spoof • Port Scan • Host Scan • etc. Source: Aziz Mounji [email protected] Russell -- ASX Automatic Actions Evt1 • Disable account • Log to file • SNMP traps • Email Sec-Ad • Exec any command • Send event to manager Evt2 Interface with C Event Stream Evtn time Rule1(uid) Rule1(uid) Rulek(x,y) 15-August-2000 State full Detection Rule1(uid) Rulek(uid) Rulek(uid) AT&T What if Alert? Block offending traffic sources Terminate suspicious processes Coordinate with multiple domains • Intruder Detection and Isolation Protocol (IDIP) Trace Report Directive 15-August-2000 (discovery coordinator) AT&T Products (Names changing all the time) Boundary controllers • NAI Gauntlet, ARGuE, MPOG, etc. • Secure Computing Sidewinder Detectors • Axent, Cisco • SRI Emerald expert-system • NAI CyberCop • ISS RealSecure • NFR www.nfr.net • Event-based traffic analysis, pattern matching, aggregation and adaptation SUNY, BRO, CIDF, IDIAN, DPF packet filter compiler … 15-August-2000 AT&T Vendors and Products – Tivoli Compatibility Source: RZ 3253 (# 93299) 06/26/00; Computer Science 45 pages Integration of Host-based Intrusion Detection Systems into the Tivoli Enterprise Console, Christian Gigandet (IBM Research; Zurich Research Laboratory) 15-August-2000 AT&T Cisco Intrusion Detection System • NetSonar (Scanner) • NetRanger (Monitor) 15-August-2000 AT&T The Cisco Secure IDS includes two components: Sensor (renamed NetSonar) and Director (renamed NetRanger). Cisco Secure IDS Sensors, which are high-speed network "appliances," analyze the content and context of individual packets to determine if traffic is authorized. 15-August-2000 AT&T ISS RealSecure • • Network engine resides on PC, monitors network transmissions for “signs of abuse and attack” About 350 attack signatures currently published 15-August-2000 AT&T Attack Recognition Platform Support Active Response Response Signature Definition Management Programming Data Acquisition ID module embedded in router/switch/firewall: • • • • Processor provides most of the analysis. Speed. Hardware assist with packet classification provides wire-speed intrusion detection. Security is painful. Shrink-wrap ID engine -- easy to install, easy to manage with relatively low cost. ID module as an ASIC: – – – • Evaluates all incoming and outgoing traffic for intrusions across all ports Switching. Monitors heavily routed or switched networks at the most heavily-trafficked network junctions. Speed. May also address speed issues by embedding ID in higher-performance hardware. ID module running on adapter card: – – – • APIs solve top 4 problems ID as a true design component. Installed on networking backplane, e.g. multi-gigabit switch, Probably only way to handle Switching. Embedded in high-performance network device allows access to all packets at single location. Speed. Wire-speed intrusion detection. ID module embedded in host protocol stack: – Attached to protocol stack above encryption layer. AT&T of encrypted traffic while still providing adequate value. – 15-August-2000 Encryption. Allows intrusion detection to exist in the presence CyberSafe Centrax 15-August-2000 AT&T Summary Maintain integrity: • Per layer • Per slice (protocol) Validate packets • Ingress/egress counters Squelch attack sources that do not comply with reasonable usage • • Test carefully to ensure not a new application Streaming media is not a UDP attack! Measure and understand “flow” properties • Recognize statistically significant variation from these path properties 15-August-2000 AT&T Backup Slides A bit more formality A glimpse at some academic research 15-August-2000 AT&T Assumptions Assumptions • RFC 1636 – encryption essential to security Open networks violate this assumption Encryption should protect control information, as well as contents • In attack from Vi net Vj assume only one of Vi, Vj is the attacker DDOS violates this assumption Assumptions are sometimes wrong • Replay attack can masquerade with encrypted data • Distributed attacks can leverage multiple attackers • Encryption can be broken 15-August-2000 AT&T General Network Model (circumscribes problem domain) G = (V, E) Path = {Vin, {Ej}, {Vj}, … {Ek}, {Vk}, {El}, {Vout}} Path consists of vertices and edges Edges E: • Propagate signal Vertices V: • Receive signal • Compute output • Emit signal 15-August-2000 AT&T Network Model Edges (links) • Signal propagation • Impairments due to random noise Redundancy manages noise, fade or analog error Detect and correct by protocols through algebraic redundancy Vertices (routers/switches) • Aggregate bits into packet • Classify and enqueue packet Packet-type and priority (UDP? TCP? ICMP? RSVP?) Loss due to load variation and queue size Detect and correct by redundant payload or retransmission • Dequeue packet Data packet: compute output as f(packet, control) Control packet: modify control as f(packet, control) 15-August-2000 AT&T Vertex Control function f(packet,control) Data packet: • Pure IP: f(packet, control) is nearly the identity function • modify TTL, next-hop, etc Proxy or active protocol: f(packet, control) not identity Augment packets in more complex “custom” ways Control packets: • Routing: static or dynamic • Resource: modify resources, i.e. queues, priorities • Behavior: modify function, i.e. classifier, marking, etc. 15-August-2000 AT&T Monitoring Entity Signatures Entity output descriptions • Compute usage signatures (local and complete) Entity to neighbors Entity to endpoints Entity input descriptions: • Receivers compute signature of received data Comparisons • Entities exchange signatures (or log centrally) Anomaly detected from signature mismatches 15-August-2000 AT&T JiNao – Protect Link-State Routing Routing Protocol OSPF Routing Protocol EIGRP RIB RIB RIB FIB Where should I forward this packet? Router/OS Kernel SNMPv3 Eng. Originator Routing Protocol BGP JiNao Decision Module Detection Module IDS MIB Info. Abst. Module Protocol Engine 15-August-2000 Statistical Analysis Protocol Analysis Prevention Module Interception Module Network AT&T Finite state machine with timing analysis, verifies Validity of OSPF actions, and guards against any intrusion – even one with “valid” security credentials