Find drawbacks of recent research on intrusion response

In modeling system response to security threats, researchers have made extensive use of state-space models. Like the one we mentioned before, RRE: A game theoretic intrusion response and recovery engine, this paper uses the partially observable stochastic game model and extended attack tree called attack-response tree. I think the main drawback for this kind of discrete-time state space model is that they may suffer from state-space explosion.

IDEA1: we may extend some other combinatorial methods for modeling and analyzing cyber attacks and countermeasures to solve this state explosion problem.

Second, by using game theory to find the best defense from a pool of defense mechanisms, it is not a so good way actually. Complicated and consume lots of time and resource.

IDEA2: We could extend some other suitable algorithms which is less expensive compared to this kind of state-space based approach.

Another team has done a great work on this area. Dr. Kishor Trivedi

Summary: Case study (experiments) related to intrusion response, security analysis

Here is my problem on doing such research:

As most of existing work did before, they developed a tool/package/system aiming at specific environment or they have data set with intrusions injected inside already. At least, they are doing security measurement, analysis or security modeling at some kind of specific physical system or research object. If they do how to response, they will have their intrusion alerts from some kind of intrusion detection system (e.g.bro, snort) as their input, or simply use some trace. It cannot come from nowhere. It has to base on some kind of actual real system or results from other tools. Maybe I myself still stuck with engineering thought, not academic thought. Correct me here, please. Thanks.

Below is a list of most representive examples:

William H Sanders from UIUC

RRE: A Game Theoretic Intrusion Response and Recovery Engine

cited by 12, Dependable System and Networks (DSN 2009)

This paper develop a Response and Recovery Engine (RRE) uses alert notifications from Snort, and then choose an optimal response actions by solving a partially observable competitive Markov decision process. They made process control network for a power grid and SCADA as their case study. In order to investigate how such RRE works in reality, they implemented RRE on top of Snort, running on Ubuntu system.

ADEPTS: adapative intrusion response using attack graphs in an e-commerce environment

Saurabh Bagchi from Purdue

cited by 29, DSN 2005

This paper develop ADEPTS to monitor and track intrusions in real-time and deploy responses to contain and restrict the spread of attacks in the system. It also has a testbed for experiments on ADEPTS. The author setup a payload system to mimic an e-commerce webstore, with web servers running applications. Different from RRE, it uses multiple detectors which communicate with ADEPTS, such as Snort and Libsafe. Three experiments were set to demonstrate this ADEPTS 1) for survivabilitity 2) ability to deploy response as the speed of attack varies, 3) adaptation in ADEPTS in choosing responses. Attack graph is used in this paper to show attack goals, since it could provide a possible path of spread of the intrusion.

Intrusion Response as a resource allocation problem

Michael Bloem, Tansu Alpcan, Tamer Basar from uiuc, information trust institute

This paper develop an algorithm for optimal allocation of the systm administrator's time available for responding to attacks, by modeling the interaction between malicious attackers and the intrusion detection system as a noncooperactive non-zero sum game. For the experiment part, this paper implement an IDS prototype in MATLAB and demonstrate its operation under various scenarios with and without such algorithm. One common thing is that it studies intrusion response in an access control systems (PR-BAC), developed by the Boeing company.

other works like Feedback control applied to survivability: A host-based autonomic defense system, which describes the design of a prototype host-based ADS intended to protect a Linux-based web server from automated Internet worm attacks; Using alert verification to identify successful intrusion attempts, presents tool that performs real-time verification of attacks detected by an intrusion detection system. It is not a response, but to verify the alert produced by IDS.

Weekly Summary

This week I have been doing two things basically.

One is to quantitatively measure the performability and security of the system, that is to quantify the amount of security provided by a system-level method. It needs first to specify the security policy, describe the vulnerabilities of the target system, and then quantitatively evaluation based on some model, like privilege graph model. One crucial factor is to define "cost" for them, such as intrusion damage cost, response cost. I was considering relate this cost to their performance.

Second is that I'm trying to build a intrusion response system based on our cps. First I have to get some intrusion alerts as the input to this IRS from some kind of intrusion detection system. Right now I'm doing with Bro developed by a researcher in UCB. It may need at least one week to get familiar with such system.

some existing intrusion response system

Bro: http://www.bro-ids.org/

Developed by Vern Paxon, a research at UC Berkely, it is a network-based, misuse intrusion detection system. Packets are passively captured from the network and processed into an event stream. The event stream is then compared against a policy script interpreter to detect intrusions. Reports are generated in the form of connection summaries and real-time alerts. Approximately 40 Mb of connection summaries and 20 real-time notifications occur each day. While automatic intrusion response beyond reporting and alerts is discussed as future research, it is currently not implemented.

Besides, I have saw a good paper <Cyber-Critical Infrastructure Protection Using Real-time Payload-based Anomaly Detection> written by Patrick. It uses the transport layer packets captured by Bro and then extract features from those TCP payload.

I am thinking if you want to do intrusion response, you may have to get some output/alerts from some kind of intrusion detection system. Right now I am getting myself familiar with this great tool.

Snort: http://www.snort.org/

It is also a famous network misuse intrusion detection system consists of three components: a packet decoder, a rule-based detection system, and an alert system. Intrusion response is limited to reports and alarms. Little of the work is based on such detection system.

The ultimate goal:

Expand all these network tools to cyber-physical system and come up with my own detection and response system. Theoretical part would be how to define abnormal behavior, build a model to quantitatively denote or rate the security level.

an idea on intrusion response

Intrusion response, as it said, it is kind of a reaction to some attacks happening (ongoing) in the system already. It effects after the adversary successfully attacked the system. The goal for such research is to bring an insecure network (CPS) under ongoing attacks to its normal operational mode with the minimum possible cost.

For example, if our CPS is under light DoS attack, controller and plant could still talk with each other, but there is large delay on the network caused by DoS attack. The UAV plant may not track the signal well. This is the cost, if we could define it formally, it would be much better. Then how could we response/react to this insecure network to make the possible cost minimum, which strategy should we choose to response/react based on which kind of selection algorithm.

But if we do so, that will make this problem as mitigating the attack.

Intrusion response and recovery

RRE: A Game Theoretic Intrusion Response and Recovery Engine (good paper)

--Saman Zonouz, Himanshu Khurana

This paper has implemented RRE on top of Snort, which is an open-source signature based IDS. RRE employs a game-theoretic response strategy against adversaries modeled as opponents in a two-player Stackelberg stochastic game. An important term used here is Attack-Response Trees (ARTs) to analyze undesired security events. By solving a partially observable competitive Markov decision process that is derived from attack-response trees, RRE will choose an optimal response actions. Basically, it depends the detection of Snort (alerts from here), using its alert to figure out respective response.

RRE is based on automated cost-sensitive model. What's great in this paper is that it modeled the security maintenance of computer networks as a two-player game in which the attacker and response engine try to maximize their own benefits by taking optimal adversary and response actions, respectively. Using ART, RRE explicitly takes inherent uncertainties into account along with alerts from Snort.

It is good method for small network (LAN) IDs.

Automated Response Using System-Call Delays

--Anil somayaji

This paper developed a system called pH (for process homeostasis), which can detect and stop intrusions before the target system is compromised. It monitors every executing process on a computer at the system-call level, and responds to anomalies by either delaying (slowing down) or aborting system calls. Normal behavior is determined by the currently running binary program.

pH is implemented as a patch for the Linux 2.2 kernel. They modified the system call dispatcher so that it calls a pH function prior to dispatching the system call. Basically, the author insert a independent process into Linux to monitor the entire process and detect the abnormal process.

It is good for single-host IDs.

Cooperating Security Managers: A Peer-Based Intrusion Detection System

--Maj. Gregory B. White, Eric A. Fisch

This paper designed and implemented CSM, which could perform a larger network IDS. Individual CSM works on each individual hosts. There is a security manager working to cooperatively and autonomously communicate with them and determine the current state of a system.

The prototype of CSM was developed using a Sun SPARC-station LX running SunOS v5.3. Basically, CSM is a package patched in OS to detect intrusive activities. Applied to a network, CSM is designed to perform intrusion detection and reporting functions in a distributed environment without requiring a designated central site or server to perform the analysis of network audit data.

Toward Cost-Sensitive Modeling for Intrusion Detection and Response (good paper)

--Wenke Lee@gatech

This paper builds a cost-sensitive intrusion detection model, including development cost, operational cost, damage cost and the cost of manual and automated response to intrusions. this kind of cost-sensitive machine learning techniques can produce detection models that are optimized for user-defined cost metrics.

The experiment uses the data from a military network with a wide variety of intrusions injected into the network over a period of 7 weeks. The data was divided into two parts: training set and test set.

The main objective in applying such a model is to compare intrusion damage and response cost to

Here is what I thought:

As we have seen above, almost all the previous work has developed a tool/package/system aiming at specific environment or they have data set with intrusions injected already. Since we don't have such kind of data set/trace, we could try to take advantage of the unique environment --- our cps simulation environment to develop a similar detection and response engine, as a goal. One problem is that this may not be easily ported to other internetworked environment. But one good thing is that it could be used to test different kinds of response strategy used to pick out a best response against the adversaries.