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Experiences with Specification-Based Intrusion Detection Prem Uppuluri and R. Sekar Department of Computer Science SUNY at Stony Brook, NY Present by:

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Presentation on theme: "Experiences with Specification-Based Intrusion Detection Prem Uppuluri and R. Sekar Department of Computer Science SUNY at Stony Brook, NY Present by:"— Presentation transcript:

1 Experiences with Specification-Based Intrusion Detection Prem Uppuluri and R. Sekar Department of Computer Science SUNY at Stony Brook, NY Present by: Mike Hsiao, 2007/11/30 Lecture Notes In Computer Science (LNCS), Vol. 2212, Proceedings of the 4th International Symposium on Recent Advances in Intrusion Detection (RAID)

2 2/29 Outline Introduction and Background What is specification-based? Behavioral Modeling Specification Language and Example Specification development 5 steps for developing specification Experiential Results On DARPA/Lincoln and DARPA/AFRL 1999 Discussions and Conclusions 20% false negative rate with zero false negative

3 3/29 Three Intrusion Detection Techniques Misuse Detection It can accurately detect known attacks Its drawback is the inability to detect previously unseen attacks Anomaly Detection It is capable of detecting novel attacks, but suffers from a high rate of false alarms Specification-based Detection a promising alternative that combine the strengths of misuse and anomaly detection

4 4/29 Specification-based Detection Manually developed specifications are used to characterize legitimate program behaviors. It does not generate false alarms when unusual (but legitimate) program behaviors are encountered. Its false positive rate can be comparable to misuse detection. Since it detects attacks as deviations from legitimate behaviors, it has the potential to detect previously unknown attack.

5 5/29 Questions about realization How much effort is require to develop program behavioral specification? compare with efforts required for training anomaly detection systems How effective is the approach in detecting novel attacks? Are there classes of attacks that can be detected by specification-based techniques that cannot be detected by anomaly detection or vice-versa? Can it achieve false alarm rates that are comparable to misuse detection?

6 6/29 General Experiences of Specification-based Detection Of the order of tens of hours and modest specification development efforts, an effective IDS can be developed. for many security-critical programs on Solaris These efforts need to be undertaken just once for each operating system. further customization on the basis of individual hosts or installations seems to be unnecessary anomaly detection systems typically need training/tuning for each host/system installation.

7 7/29 Behavioral Monitoring Specification Language (BMSL) BMSL enables concise specifications of event based security-relevant properties These properties can capture either normal behavior of programs and systems, or misuse behaviors associated with known exploitations. BMSL specifications are based on the packet contents, log file entries, and for system calls (and the values of system call arguments.) In this paper, only system calls are considered.

8 8/29 BMSL (cont’d) BMSL support a rich set of language constructs that allow reasoning about not only singular event, but also temporally related event sequences. For a given event stream (system calls), an interceptor component placed in the stream provides efficient interception of raw events. The interceptors deliver raw event streams to a runtime environment associated with each stream. A single detection engine monitors each defended process.

9 9/29 pat -> action pat is a pattern on event sequences, otherwise known as histories. action specifies the response to be launched when the observed history satisfies pat. We typically initiate responses when abnormal behaviors are witnessed thus, components of rules usually correspond to negations of properties of normal event histories.

10 10/29 Two System Call Events The first event for a system call corresponds to the system call invocation it has the same name as the system call with the arguments that are exactly the same as the system call The second event corresponds to the return from the system call its name is obtained by suffixing _exit to the name of the system call The arguments includes all of the arguments to the system call, plus another argument that captures the return value from the system call.

11 11/29 The pattern language: Regular Expressions over Events REE extends the concepts from sequences of characters to events with arguments. occurrence of single event: e(x 1, …, x n )|cond is satisfied if cond evaluates to true ( x are arguments) occurrence of one of many events: E 1 ||E 2 || … ||E n, where E i captures an occurrence of a single event event non-occurrence: !(E 1 ||E 2 || … || E n ) Temporal operators sequencing: pat 1 ;pat 2 alternation: pat 1 || pat 2 repetition: pat*

12 12/29 The pattern language (cont’d) pattern: e1(x);e2(x) e1(a);e2(b) -> not satisfied e1(a);e2(a) -> satisfied an event history H matching a pattern p H matches p if any suffix of H matches p. anchor i.e., constrain the match to occur from the beginning of the history H a special event begin is introduced at the beginning of the pattern.

13 13/29 Example Specifications restrict a process from making a certain set of system calls execve||connect||chmod||chown||creat||sendto||mk dir -> term() if arguments are not used else where, we can omitted them. term() is an external function provided in runtime environment. restrict the files that a process may access or reading or writing admFiles = {"/etc/utmp", "/etc/passwd"} open(f,mode)|(realpath(f)≠admFiles||mode≠O_RD ONLY)->term()

14 14/29 Example Specifications (cont’d) assert that a program never opens and closes a file without reading or write into it. openExit(fd)::=open_exit(..., fd)|| creat_exit(..., fd) rwOp(fd)::=read(fd)||readdir(fd)|| write(fd) openExit(fd);(!rwOp(fd))*;close(fd)

15 15/29 Specification development 1.Developing generic specifications parameterize the system calls and arguments 2.Securing program groups class programs that have similar security implications (e.g., setuid, daemons) 3.Developing application-specific specifications 4.Customizing specifications for an operating system/site 5.Adding misuse specifications the detection of some attacks requires knowledge about attack behavior.

16 16/29 1. Developing generic specifications group system calls of similar functionality allow us to consider a smaller number of system call groups (few tens) while writing specifications, rather than a few hundred system calls also helps in developing portable specifications The authors identified 23 groups, further organized into 9 categories. File Access Operations WriteOperations: open, create ReadOperations FileAttributeChangeOps: chgrp, chmod

17 17/29 1. Developing generic specifications (cont’d) Process Operations ProcessCreations: fork, execve ProcessInterference: kill Network Calls ConnectCalls AcceptCallls Setting resource attributes such as scheduling algorithm and parameters Privileged Calls mount, reboot

18 18/29 2. Securing program groups restrict setuid program (e.g., passwd) with bounded size of input argument execve(path,argv,envp | checkSize(path,argv,envp,max) -> term() failed login attempts (e.g., Telnet, FTP) execve(prog) | prog = "telnetd" && tooManyAttempts() -> log("too many failed logins") (setuid || setreuid) -> resetAttempt()

19 19/29 3. Developing application- specific specification The author identified the principal security- related system calls made by ftpd and plausible sequence orders for their execution. (!setreuid)*;setreuid(r,e) -> loggedUser := e (!setreuid())*;ftpInitBadCall() -> term() setreuid();any()*;ftpAccessBadCall() -> term() connect(s, sa)|((getIPAddress(sa) != clientIP) && (getPort(sa) ≠ ftpAccessedSvcs)) -> term()

20 20/29 4. Customizing specifications for an OS/site system calls and files may different from different OS/site. e.g., password file, private directories site specific security policies e.g., anonymous ftp

21 21/29 5. Adding Misuse rules to specification Certain attacks can be detected only based on knowledge about specific attack behavior. E.g., a small number of login failures using the user name guest usually indicates an attack. But small number of failures are not that unusual with other user names, as users frequently mistype or forget their passwords. This knowledge pertains to attacker behavior, rather than the behavior of the program itself.

22 22/29 Experimental Data Data 1999 DARPA/Lincoln Lab offline evaluation an audit log data is used to corresponding system call (name, time, args, and return value, process is, userid, guid, IPs, and ports) 1999 DARPA/AFRL online evaluation Specifiation for program in.ftpd, in.telnetd, eject, ffbconfig, fdformat, ps, cat, cp, su, netstat, mail, crontab and login

23 23/29 Experimental Results Attack Name # of instances % instances detected before misuseafter misuse fdformat 3100% ffbconfig 1100% eject 1100% secret 4100% ps 4100% ftpwrite 2100% warez master 1100% warez client 2100% guess telnet 3100% http tunnel 70%100% guest 20%100% total 3082%100%

24 24/29 Development Effort The author claim that general specifications seem to be sufficient for detecting a majority of the attack. Many attacks produce violations of multiple rules. attacks may be detectable with even less effort in specification development. For ftpd, the authors develop 14 rules which were 18 lines of codes in BMSL. setuid to root programs required 6 man hour to refine and customize the specification.

25 25/29 Development Effort (comparing with training anomaly detection systems) Production of training data (by a human) for anomaly detection systems is resource intensive. It is very important to ensure that the training data encompasses almost all legitimate behaviors, which is difficult, and typically requires manual intervention on a program by program basis. Trained data is usually specific to a particular installation of an operating system.

26 26/29 Novel attacks and false positive rate Over 80% of the attacks could be detected without encoding any attack-specific information into the specifications. Viewed differently, all of these attacks are “unknown” to our system. In the online evaluation, the authors did not encode any misuse rules all detections were based on normal behavior specifications. In this context, the system detected all of the three attacks launched during this evaluation, once again with zero false alarms.

27 27/29 Novel attacks and false positive rate (comparing with anomaly detection systems) A specification is aimed at capturing a superset of possible behaviors of a program. As such, there is no inherent reason to have false positives, except due to specification errors. There may be some behaviors that are outside of the legitimate behaviors of a program, but within the superset captured by a specification. Exploits that involve such behaviors will be missed by a specification-based approach, while they can be captured by a learning based approach.

28 28/29 Novel attacks and false positive rate (anomaly detection can’t) Learning-based approach essentially learns that execution of a security-relevant error is normal. Viewed alternatively, exploitation of the error to inflict intrusion does not lead to any change in the behavior of the program containing the error. Existing anomaly detection approaches based on system calls generally ignore system call argument values. Anomaly detectors typically need to be trained/tuned for each host/site.

29 29/29 Comments Unusual v.s. Legitimate Focus on the program behavior, not attack behavior. Using system calls as a basis may not be a good solution for network-based system. But system call is a good basis. (It is the basis of all programs.) Classification is a smart approach. Using regular expression is a flexible design.

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