MAIS: MOBILE AGENT INTEGRITY SYSTEM

A Security System to IDS based on Autonomous Agents

Rafael Páez, Joan Tomàs, Jordi Forné and Miquel Soriano

Telematics Engineering, Technical University of Catalonia, Jordi Girona 1-3, Barcelona, Spain

Keywords: Multiagent systems, mobile agents, Software Watermarking, Intrusion Detection Systems.

Abstract: Intrusion Detection Systems based on autonomous agents are a promising technology due to their

scalability, resilience to failures, independence and reduction of network traffic. However, when used to

protect critical systems, the IDS by itself can be the target of malicious attacks. In this paper we propose a

security system to verify the integrity of the IDS agents during their execution time, by using software

watermarking techniques.

1 INTRODUCTION

The security of software systems has become an

important topic because they provide the

functionality of critical systems controlling

important infrastructures like centres for disasters

prevention, intelligent buildings, planes’ functions

automation, etc. So, many human lives and

important amounts of money strongly depend on the

confidentiality, integrity and availability of software

systems which must be protected to warranty the

required level of security. There are several tools

that are used to provide this security, such as

firewalls, honeynets, honeypots, and Intrusion

Detection Systems (IDS). However, since the

reliability of the whole system relies on the proper

function of them, the tools their selves become

objectives susceptible to be attacked and therefore

they also need to be protected.

Intrusion Detection Systems detect suspicious

activities and possible intrusions in a system or

private network at the moment at which these

happen. The different entities that compose the IDS

need to communicate among them, therefore is

important to keep in mind security communication

services such as integrity of the information,

authentication and access control.

One of the important characteristics of security

systems and particularly of IDS, is the cooperation

among its components in order to achieve their

global objective and to reduce central processing. By

this reason, an agent-based technology has been

proposed to be integrated with IDSs, since they carry

out the processing in-situ and they can

autonomously communicate to each other.

The main security limitations that affect the

deployment of mobile agents are multiplied in IDS

based on autonomous agents, since IDS by itself are

one of the main objectives to be attacked by

malicious users. In this article we focus our attention

in Autonomous Agents for Intrusion Detection,

identifying a particular threat for these systems and

then proposing a solution to increase the security

against this potential attack. Our proposal is based

on an IDS system architecture based on autonomous

agents named Autonomous Agents For Intrusion

Detection (AAFID). In the AAFID system there are

three types of entities: monitors, transceivers and

agents, hierarchically organised in a tree

infrastructure.

Our objective is to analyze a risk scene and to

propose a possible solution. In section 2, we

introduce the related background, including software

agents, watermarking techniques and IDS based on

agents and its security. In the section 3, we present a

risk scene. In section 4 we present a system named

MAIS, its architecture and the operation protocol.

Finally section 5 concludes.

2 STATE OF THE ART

In this section we overview the related background

necessary to understand the solution that we present

here. Likewise, we analyze the security problems

Páez R., Tomàs J., Forné J. and Soriano M. (2007).

MAIS: MOBILE AGENT INTEGRITY SYSTEM - A Security System to IDS based on Autonomous Agents.

In Proceedings of the Second International Conference on Security and Cryptography, pages 41-47

DOI: 10.5220/0002120500410047

 SciTePress

and some solutions that have been presented in the

literature. More specifically, we introduce Intrusion

Detections Systems, agents, software watermarking

techniques and the main existing proposals about

IDS based on autonomous agents, including a

security analysis.

2.1 Intrusion Detection Systems

An Intrusion Detection System tries to detect and to

alert about suspicious activities and possible

intrusions in a system or particular network. An

intrusion is an unauthorized or non wished activity

that attacks confidentiality, integrity and/or

availability of the information or computer

resources. To reach its goal an IDS monitors the

traffic in the network or gets information from

another source such as log files. The IDS analyzes

this information and sends an alarm to the system

administrator. The system administrator decides to

avoid, to correct or to prevent the intrusion.

Basically an IDS has an events generator, an

analyzer or sensor and a response module. The event

generator sends the packets to the events collection

module that communicates with the sensor. The

sensor filters the information and discards irrelevant

data. The response module decides whether to send

or not an alarm according to the policy held in its

database (

Goyal, Sitaraman, and Krishnamurthy 2003).

An IDS can be classified according to its location, it

can be Network based IDS (NIDS) or Host based

IDS (HIDS); according to the detection mechanisms,

it can be misuse detection or anomaly detection; and

according to its nature it can be passive or reactive.

2.2 Agents

There are different definitions of agents

(

Balasubramaniyan et al, 1998), (Nwana, 1996), (Jansen

et al, 2000)

. In general, an agent is a software entity

that works autonomous and continuously gathering

data to accomplish an action on behalf of a person or

another agent. Autonomously means that it can work

without direct intervention of a human or other

system and has the control of its internal state and its

actions.

2.3 Software Watermarking

Watermarking techniques have been basically used

to ensure the protection of digital contents. With

these techniques, some information (usually called

mark), is embedded into a digital content like video,

audio, software, (Figure 1). The main objective is to

keep this information imperceptible in all copies of

the content that we protect in such a way that we can

later demand the authorship rights over these copies.

In software watermarking, the mark must not

interfere with the software functionalities. The mark

can be: static, when it is introduced in the source

code, or dynamic, when it is stored in the program

execution states.

Figure 1: Software Watermarking.

There are three basic aspects to consider when a

watermarking technique is designed: the required

data rate, the type of source to mark (native binary

code, bytecode, etc.) and the expected threat model

(translation, optimization, obfuscation of code, etc.).

To retrieve the watermark we need a recognizer.

Recognizers are designed to extract the watermark

from the program execution with a specific input.

Recognizers can be defined from trivial (does not

assure that the watermark can be retrieved) to strong

or ideal (resistant against all kind of

transformations). And according their operation,

recognizers can classified from static, when only the

source code is analyzed, to pure dynamic, when

only program execution state is examined.

2.4 IDS based on Autonomous Agents

According to (Jansen et al, 2000), (Lange et al, 1998)

and (

Dorothy et al, 1987), there are several advantages

of mobile agents that make them appropriate to IDS:

scalability, resilience to failures, independence,

reduction of network traffic, when another agent is

generated it is not necessary to restart the system,

solution to complex tasks, etc.

The architecture for IDS based on autonomous

agents has the following components: monitors,

transceivers, agents and filters. Definition of each

component and further information can be found in

(

Balasubramaniyan, 2003). The AAFID system

(Balasubramaniyan et al, 1998) includes a user

interface and several components of its architecture.

User interfaces use APIs that the monitor exports, to

ask for information and to provide instructions. In

the AAFID system there are three types of static

entities: monitors, transceivers and agents,

hierarchically organised with a tree infrastructure.

Watermar-

king

DATA

Watermar-

king Encoder

Application

running

MARKED

DATA

DISTRI-

BUTION

Watermar-

king

Encoder

SECRYPT 2007 - International Conference on Security and Cryptography

2.5 IDS based on Autonomous Agents

Security

To protect the entities of the IDS, it is necessary to

protect both the platform and the agents. Mobile

agents offer many functional advantages, but there

are new threats due to their mobile nature. The more

common threats are: agent against platform,

platform against agent, agent against other agents

and other entities against the agent system. Several

solutions have been proposed to reduce these risks

(Table 1) but particularly the threats of platform

against agents are the most difficult to avoid.

Table 1: Countermeasures for attacks of platforms against

agents.

CONTERMEASURES

Partial results encapsulation (Yee, 1997)

Mutual itinerary recording (Roth, 1998)

Itinerary recording with replication and voting

(Schneider, 1997)

Execution tracing (Vigna, 1997)

Environmental key generation (Riordan, 1998)

Computing with encrypted functions (Sander et al,

1998)

Obfuscated code (Hohl, 1998)

Cooperative agents (Roth, 1998)

Limiting the execution time (Esparza et al, 2003)

2.6 Protecting Agents Against

Malicious Hosts

Particularly, the attack carried out by a platform

against an agent is very difficult to avoid, because

the platform has total access to data, code and results

of the agent. So, if a host is malicious, it can easily

isolate the agent and extract information to corrupt it

or modify its code or its state. Other extreme

measures that a malicious host could perform are to

analyze the operation of the agent or to apply inverse

engineering to introduce subtle changes and to force

the agent to be malicious, reporting false results.

3 RISK SCENE

In an IDS based on autonomous agents, a monitor

controls a network segment and it sends a

transceiver to each host. Likewise, various agents

are generated by a transceiver in order to monitor a

determined type of traffic and they send alerts of

suspicious activities to the transceiver on which they

depend within the tree structure. One of the existing

threats in these systems is when an intruder attempts

to replace any IDS entity by another with similar

characteristics but subtly modified in order to avoid

a particular suspicious activity. So, if an agent or

transceiver is modified or replaced, they will not

report their correct results to their correspondent

monitor and likewise, if a monitor is replaced it will

not avoid or prevent the forthcoming attack.

Security solutions in IDS based on agents are the

same that are offered for any environment that use

agents. However, all the requirements are not

covered; in particular, the threats against the IDS, its

components and communications are not faced. So,

in this paper we propose to detect attacks against any

IDS entity with a new security scheme named

MAIS.

4 MAIS (MOBILE AGENT

INTEGRITY SYSTEM)

We propose a new system to verify not only the

integrity of transceivers located in different hosts of

the IDS architecture, but the correct execution of the

transceivers during its operation. The MAIS system

architecture is similar to AAFID system, but the

transceivers and monitors behave like mobile agents

and their mobility is limited, they only can displace

to their corresponding trusted entity, that is to say,

the upper level entity from which they depend. The

data collection agents are static and they conserve

the same characteristics of the AAFID system

agents.

4.1 MAIS Architecture

The MAIS architecture has three essential

components: monitors, transceivers and data

collection agents. The monitors are agents that are

located in the high levels of the infrastructure, they

carry out correlation of information of high level and

they control a network segment. There is a root

monitor located in the higher level. It has the ability

to communicate with an administrator interface and

it also can provide the access point for the whole

MAIS system. The administrator interface is

independent of the IDS entities, in order to permit

different implementations. The monitors can also

control other monitors and besides they are in charge

of emitting and to control another type of agents

called transceivers.

In MAIS, the monitors are also Trusted Parties,

which are in charge of identifying the entities that

MAIS: MOBILE AGENT INTEGRITY SYSTEM - A Security System to IDS based on Autonomous Agents

Figure 2: MAIS system architecture.

they control and to carry out the process of

watermarking recognition. The watermark allows us

to verify not only the transceiver’s or monitor’s

integrity but also their correct execution (a wrong

execution generates a wrong watermark).

Transceivers carry out correlation functions and

they send the information to the monitor which they

depend from. Transceivers have information about

the host where they reside and also control the

underlying agents. The main differences between an

AAFID transceiver and a MAIS transceiver are the

mobility and the mark.

The data collection agents inside the MAIS

infrastructure are in charge of monitoring a host and

its behaviour. The agents and their transceivers are

located in the same host.

In the MAIS system, the transceivers and monitors

must be mobile because they have to displace from

its host to their TTP. This TTP is the immediately

superior entity in the infrastructure, which will be

able to do the mark verification; therefore, it is

necessary to establish new characteristics for the

system. The first one is that all the monitors and

transceivers of the IDS must be mobile. The second

one is that an entity which controls to another

entities must behave as a trusted party when thus be

required and to perform the mark verification. The

third one is that each host must have at least two

transceivers being able to carry out the same

function, so when an agent is sent to the TTP to

verify the integrity of its code and of its execution,

another agent replaces its functionality.

The transceivers depend on monitors and

monitors likewise can depend on other monitors

(Figure 2), but the transceivers can only control their

underlying static agents (data collection agents). So,

the monitors are required to be trusted parties and

they control the marking and verification processes

to its underlying entities. The monitors have an

overview of a network segment and the transceivers

have an overview of a host

4.2 MAIS System Operation

The system operation protocol is as follows:

Network se

ment

Network segment

Host 2

Host 1

Interface

Administrator

T1 T2

Monitor (TTP)

Transceiver

Agent

T3 T4

Host n

T3 T4

SECRYPT 2007 - International Conference on Security and Cryptography

1. A monitor generates an entity and its

corresponding support entity.

2. Subsequently it performs the watermarking

process on each entity and sends them to the

destination host conserving its timestamp.

3. The entity moves to its destination host to carry

out its function.

4. The agents periodically move to their generating

entity according the established time

(timestamp). While an entity goes to verify the

integrity of its code and of its execution, the

support entity continues carrying out their work.

5. When an agent arrives to verify its integrity, the

issuing entity performs functions of third trust

party verifying the mark of the agent. If the

agent has been compromised, the TTP

eliminates it and isolate the host in which was

residing, considering it malicious.

6. In case that an agent do not arrive on the

established time to perform the verification

process, the host is isolated and the agent

eliminated.

The issuing entity conserves the timestamp to

verify that each agent arrives on time to control its

integrity in determined periods of time. In each host

there will be at least two entities executing the same

function to provide service continuity while an entity

displaces to carry out the verification of its integrity

When the agent arrives to the verifier it verifies the

mark. Is important to note that an incorrect

transceiver's execution generates a wrong mark; so,

the system administrator can detect the anomalous

behaviour and perform the corresponding security

measures.

On the other hand, watermarking techniques are

used instead of digest techniques because the

transceivers are constantly being self modified to

incorporate the new collected information.

4.3 Watermarking Layer

The algorithm that we use to embed the mark is the

Dynamic Graph Watermarking (Collberg and

Thomborson, 1998) and (Collberg and Thomborson,

1999), but others watermarking algorithms may be

considered.

4.3.1 Watermarking Algorithm Overview

The main characteristic of the Dynamic Graph

Watermarking algorithm is that it offers protection

against distortive de-watermarking attacks as

obfuscation or optimization. The basic idea is to

embed the mark into a graph topology. This graph is

dynamically built during run time. As it is well

known, dynamic graph structures are hard to

analyze. On the other hand, semantic source code

modification does not affect these algorithm

performances because execution results must be the

same, in other words, the agent has to generate the

same graph structure of its watermark.

The mathematical hard problem used by this

algorithm is the same that is used by public key

cryptography: the prime number factorization. In

other words, if n is the product of two bigger prime

numbers p and q, calculate p and q from n is a hard

computational problem. Applied in this

environment, a system that is able to embed this

number n into a graph structure in an agent can be a

good option to prove the legal origin of one code.

That is to say, as the legal owner has the values that

factorize n and the method to retrieve the value of n,

he can prove his ownership. From this point of view,

the efforts to solve the watermarking problem will

be concentrated in mark embedding and extracting

methods.

4.3.2 Mark Embedding

Basically, there are two encoding techniques to

embed the mark into a graph topology: Radix-K and

Enumeration.

Figure 3: Radix-K encoding example.

Radix-K encoding consists in a graph with circular

linked list structure. This list has an extra pointer

field which encodes a base-K digit. A null pointer

encodes a 0, a self-pointer encodes a 1, a pointer to

the next node encodes a 2, etc. Figure 3 shows, as an

example, the codification for 61 * 73 = 4453 = 3*6

+2*6

+0*6

+ 4*6

+ 1*6

. On the other hand,

Enumeration Encoding is based in the work of F.

Harary and E. Palmer in (

Harary and Palmer, 1973).

4.3.3 Embedding Process

As shown in figure 4, the owner selects n as product

of two big prime numbers p and q. n is embedded in

the topology of a graph G. After that, a source code

W which builds G is constructed. W is embedded

into the original agent O and the watermarked agent

is obtained. When O

is run with I as input, the

MAIS: MOBILE AGENT INTEGRITY SYSTEM - A Security System to IDS based on Autonomous Agents

Figure 4: Embedding and Extraction process.

graph G will be built and the recognizer R is

constructed. The objective of R is identified G on the

heap of the agent execution. After that,

tamperproofing and obfuscation techniques can be

applied (see O

and O

). Finally, the recognizer is

extracted from the application and O

is sent to its

destination host. When a malicious agent O

moved to their generating entity, this entity can

identify if the execution of this agent has been

modified linking O

with R and executing them with

I as input. As result, the modified watermark n’ is

obtained and this entity can verify that the original

factors p and q can not factorize n’ and it allows to

detect the malicious agent. In other words, if n and

n’ does not match; the agent execution has been

modified.

4.3.4 Mark Extraction

As was commented before, the idea is to construct a

graph in memory which topology embeds the mark.

To recover this mark, an extraction process is

needed. One method can be to examine all reachable

heap objects but this can be a hard computational

problem. Instead of this, the input I is divided in

parts an every part builds a portion of the

watermark. As a result of the last part, the recognizer

returns the root node of the watermark.

4.3.5 Watermarking Justification

Digital signatures are widely used to guarantee the

code integrity and authenticity. The digital signature

can be used to verify, at a given moment, that a

software code is exactly as created. However, it

cannot assure that the code was properly executed

over a period of time.

In the IDS, given that the transceivers are

changing continuously because they are collecting

information, digital signatures techniques are

inappropriate. Moreover we want to provide not

only transceivers integrity but the correct execution

of the transceiver. Therefore, we propose to use a

watermarking technique which is suitable because

the mark is dynamically built during run time and if

the semantic source code is modified the agent has

to generate the same graph structure of its

watermark, otherwise it indicates that the agent

execution has been modified.

5 CONCLUSIONS

The attacks of malicious hosts against the agents are

considered one of the problems most difficult to

solve and there is not a form of protection that

eliminates them completely. To offer a determined

security level in an IDS based on agents is necessary

SECRYPT 2007 - International Conference on Security and Cryptography

to combine different techniques that permit to detect

an attack although it cannot be avoided. The

drawback to send an agent to a malicious host is that

this can be attacked, because of the host has total

access to the code and data, therefore, to carry out a

verification of its integrity, we propose the use of

trusted monitors using watermarking techniques to

verify the proper working of the IDS software

components..

REFERENCES

B. Goyal, S. Sitaraman, S. Krishnamurthy, 2003. Intrusion

Detection Systems: An overview. SANS Institute

2001, as part of the Information Security Reading

Room.

J.S Balasubramaniyan, J.O. Garcia-Fernandez, D. Isacoff,

E. Spafford, D. Zamboni, 1998. An Architecture for

Intrusion Detection using Autonomous Agents,

Proceedings., 14th Annual Computer Security

Applications Conference, pages 13 – 24

H.S. Nwana, 1996. Software Agents: An Overview,

Knowledge Engineering Review, 11(3), pages 1-40

W. Jansen, P. Mell, T. Karygiannis, D. Marks, 2000.

Mobile Agents in Intrusion Detection and Response,

Proc. 12th Annual Canadian Information Technology

Security Symposium, Ottawa.

D. Lange and M. Oshima, 1998. Programming and

deploying java mobile agents with agle, (Addison-

Wesley)

Dorothy E. Denning, 1987. An intrusion detection model,

IEEE Transactions on Software Engineering, 13(2),

pages 222-232.

W. A. Jansen. Countermeasures for mobile agent security,

2002. Computer communications, Special Issue on

Advanced Security Techniques for Network

Protection, 25(15), pages 1392-1401

B.S. Yee, 1997. A Sanctuary for Mobile Agents.

Technical Report CS97-537, University of California

in San Diego.

V. Roth, 1998. Secure Recording of Itineraries Through

Cooperating Agents, Proc. of the ECOOP Workshop

on Distributed Object Security and 4th Workshop on

Mobile Object Systems: Secure Internet Mobile

Computations, France, pages 147-154.

F.B. Schneider, 1997. Towards Fault-Tolerant and Secure

Agentry, Proc. 11th International Workshop on

Distributed Algorithms, Saarbucken, Germany, pages

1-14.

G. Vigna, 1997. Protecting Mobile Agents Through

Tracing, Proceedings of the 3rd ECOOP Workshop on

Mobile Object Systems, Jyvälskylä, Finland.

J. Riordan, B. Schneier, 1998. Environmental Key

Generation Towards Clueless Agents, Lecture Notes in

Computer Science, 1419, pages 14-24.

T. Sander, C. Tschudin, 1998. Protecting Mobile Agents

Against Malicious Hosts, Lecture Notes in Computer

Science, 1419, pages 44-60.

F. Hohl, 1998. Time Limited Blackbox Security:

Protecting Mobile Agents From Malicious Hosts,

Lecture Notes in Computer Science, 1419, pages 92-

113.

O. Esparza, M. Soriano, J. L. Muñoz, J. Forné, 2003. A

protocol for detecting malicious hosts based on

limiting the execution time of mobile agents, 8

IEEE

Symposium on Computers and Communications. 1,

pages 251-256.

Christian Collberg and Clark Thomborson. On the limits

of software watermarking.Technical Report 164,

August 1998.

Christian Collberg and Clark Thomborson. Software

watermarking: Models and dynamic embeddings. In

Principles of Programming Languages 1999,

POPL’99, San Antonio, TX, January 1999.

Frank Harary and E. Palmer. Graphical enumeration,

1973. Academic Press, New York

MAIS: MOBILE AGENT INTEGRITY SYSTEM - A Security System to IDS based on Autonomous Agents