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A Study on Analysis of Malicious Code Behavior Information for Predicting Security Threats in New Environments.

1. Introduction

The development of ICT technology is changing our lives. Especially, due to the advanced technology of IoT (Internet of Things), which is a technology in which all the objects around are connected with each other through networks, various services and various types of ICT environments are emerging [1][2]. ICT technology has come to coexist near us in residential, work and living spaces such as Smart home, smart factory, and smart city environments [3][4]. In addition, ICT technology is being applied to transportation that has a big impact on our lives, such as the next-generation intelligent transportation system called C-ITS (Cooperative-Intelligent Transport System) [5].

However, the development of ICT does not always bring us the benefit. Malicious code is evolving as fast as the development of ICT technologies. According to the report released in McAfee lab in September 2018, the total number of malicious codes is about 80 million in Q2 of 2018[6]. In particular, mobile malware that infects and spreads through mobile devices accounts for about 27 million cases [6].

As such, the development of ICT technology and the evolution of malicious code are closely related. In particular, devices and ICT technologies that are popular around the world are being used as a good infection route and attack target for malicious code. Especially, the rapid improvements of smartphone technology have resulted in the evolution of mobile botnets [7]. The most representative case is the Mirai Botnet incident in October 2016 [8]. In case of ransomware, it is designed to encrypt system user's files and documents, but it can do more than that depending on which family of ransomwares it belongs to [9]. Recently, ransomware which locks the screen of a smartphone instead of file encryption is also emerging.

Through this, we have found that malicious code is scalable to adapt quickly to various environments and it is using success cases in existing environment. At the time when various malicious apps appeared for smartphones, there were some malicious apps with DDoS (Distributed Denial of Service) attack function, but they did not achieve great results. However, IoT devices have emerged to replace smartphones and IoT devices have received worldwide attention. Like the Mirai Botnet described above, DDoS attacks using IoT devices reappeared and achieved great results. We analyze the evolution of these malicious codes and try to predict how malicious codes will appear in the new environment.

Therefore, in this paper, we propose a method to predict security threats that can occur in new environment based on malicious behavior information that can be acquired through malicious code analysis.

The contents of this paper are as follows. Chapter 2 presents threat statistical related to malicious code. Chapter 3 presents structure of malicious code behavior information and its sections and subsections. Chapter 4 presents predicting security threats in new environments method. The last chapter presents the conclusion and describes future research.

2. Related Work

2.1 Threats Statistics

As ICT technology evolves, malicious code is also becoming more intelligent and automated, posing a significant threat to users of ICT technologies. Recently, malicious codes are getting out of the level of taking information of users. It also implemented a large number of DDoS attacks using a large number of zombie devices by inserting automation functions into malicious code. In addition, a variety of new malicious codes are being generated, including Ransomware, which encrypts important data for individuals and corporate storage and devices and requires money. As a result, malicious codes are changed into various forms and malicious codes of variants are being generated.

In S eptember of 2018, McAfee Labs provides McAfee Labs Threats Reports to provide insights into recent security threats [6]. Fig. 1 shows the statistics of total malware that occurred until 2018 Q2.

The total malware shown in the above statistics includes new malware and variant malware. The statistics of new malware are shown in Fig. 2 below.

Fig. 1 and Fig. 2 show that the ratio of new malware among total malware does not exceed 10%. As a result, we can see that the ratio of variant malware that reuse known malicious codes is higher than new malware.

In addition, the report also shows that mobile malware targeting mobile devices is steadily increasing. Also, Android lockscreen malware with Ransomware has also been growing rapidly since 2017[6].

Therefore, we analyze the fact that most malicious codes are reusing already generated malicious codes, and that there are many malicious codes in the environment (mobile, IoT, etc.) that can be called the latest trend.

3. Malicious Code Behavior Information

3.1 Definition

In this paper, Malicious Code Behavior Information refers to information such as infection route, attack target and attack behavior that can be obtained by analyzing malicious code. That is, it refers to all information related to malicious activity as well as internal information contained in malicious code. It is used to predict security threats that can occur in new environment by classifying them in detail. In this paper, MCBI refers to Malicious Code Behavior Information.

3.2 Structure of MCBI

The MCBI can be divided into an Infection & Propagation section and an attack section. First, the Infection and propagation section consists of the information that appears when malicious code infects an attacking target. The Attack section is also made up of information related to the attack target, executor and attack behavior of malicious code. Table 1 below shows the subsection of each main section of MCBI.

3.3 Infection & Propagation Section

All malicious codes use various paths to infect attack targets. There are also various types of malicious codes, such as downloading itself directly when the malicious code reaches an attack target or exploiting vulnerabilities of the system. User involvement may or may not be needed in the process of infecting and propagating malicious code. Therefore, this section classifies and defines the features that occur when malicious code propagates and infects. The section consists of infection & propagation route, infection type and user dependency subsection.

3.3.1 Infection & Propagation Route

Infection & propagation route classifies devices or services used as route of malicious code infection. This part can be added to new devices or services in consideration of the rapidly changing and evolving ICT environment, and can be deleted or included in other parts.

3.3.2 Infection & Propagation Type

Infection & propagation type subsection classifies the features used by malicious code to succeed in infecting and propagating to attack target.

3.3.3 User Dependency

User dependency subsection defines whether or not the system user intervention is necessary for malicious code to infect and propagate the attack target.

3.4 Attack Section

Malicious code has a specific or unspecified attack target, and after it reaches the attack target, it executes itself through any entities. In addition, when the malicious code is executed, malicious code performs ultimate aim. There are a variety of types that can be used to accomplish the end goal themselves, or to be used as a method for secondary infection and propagation, etc.

Therefore, the Attack section classifies and defines malicious code attack targets, malicious code executors, and attacking behavior. The section consists of attack target, executor and attack behavior.

3.4.1 Attack Target

The attack target subsection classifies and defines the target that malicious code wants to cause an attack.

3.4.2 Executor

The Executor subsection classifies and defines entities that actually execute malicious code.

3.4.3 Attack behavior

Malicious code performs malicious behavior as it can be understood by its name. In attack behavior subsection, malicious code classifies and defines entities that are mainly used to perform malicious actions.

3.5 MCBI Example

In this section, MCBI for representative malicious code is shown to help understanding of MCBI structure generation. Table 8 below shows the MCBI for the Mirai botnet code. Through the following results, contents information corresponding to Mirai botnet code can be utilized as tag information for type and grouping of malicious codes.

4. Predicting Security Threats in New Environments

4.1 MCBI Management

The MCBI proposed in this paper is a structure that can be continuously expanded and developed. In order to predict security threats in a new environment, such as the emergence of new ICT devices or new ICT technology, MCBI structure should be continuously developed through MCBI analysis for various malicious codes. Therefore, this section describes the process for continuous management of MCBI.

The process shown in Fig. 3 shows a mixture of regular operation process and event conditions with feedback and extension.

* Regular operation process

Step 1. Collect malicious code from various media and services.

Step 2. Perform MCBI analysis. (Phase 1 and Phase 2 are performed in sequence)

Step 3. Perform malicious code grouping and tagging based on the analysis result.

Regular operation process is aimed at gathering data on the recent behavior of malicious code by continuing to collect malicious code as possible and perform MCBI analysis. After analyzing the malicious code for MCBI, group similar malicious codes using MBCI contents.

* Feedback process

The feedback process is performed when it is difficult to define and classify a specific malicious code with the current MCBI structure. It is performed when a completely different type of malicious activity occurs although the ICT environment has not changed.

* Extension process

The process of extending the MCBI structure when a new technology or device emerged is called an extension process. New contents can be added to the infection & propagation route subsection when a new technology or device appears. Therefore, it is necessary to consider the process of expanding the MCBI structure.

4.2 Predicting Security Threats Process

Most of the security threats in the new environment are being reused from malicious code that has already occurred. Therefore, it is possible to predict the security threats that may occur in the new environment by performing the extension process of the MCBI structure proposed in this paper. When a new technology or device emerged with a new environment in the security ecosystem, the extension process of MCBI structure is performed through the following process and we predict security threats.

As shown in Fig. 4, the process of predicting possible security threats in a new environment consists of 4 steps.

* New environment

Initiate the MCBI's extension process to realize the emergence of new technologies or devices and to predict potential security threats in the upcoming new environment.

* Feature analysis

As a step of analyzing features for a new technology or device it analyzes not only computing ability, network function, storage function, but also connectivity with other media and data type that can be newly created and managed.

* Comparison with MCBI

This is the stage of comparing and analyzing with MCBI based on the analysis result of feature analysis step. If an entirely new technology or device emerges, new content can be added to the MCBI during this process. This process expands the MCBI to accommodate new environments.

* Search and analysis malicious code

The analysis of MCBI for new technologies and devices and malicious codes that have related MCBI tags are searched. Based on MCBI information of searched malicious codes, security threats that can occur in new environment are derived.

5. Conclusion & Future Research

Malicious code is evolving in line with the pace of ICT technology development. There may be some difficulties in predicting all possible security threats in a new environment that will be met by the emergence of new technologies and devices without special criteria. Malicious code that causes most security threats is evolving into a form that applies security threats that already existed in existing environments to new environments rather than entirely new forms. Therefore, in this paper, we classify and define not only internal information of malicious code that can be acquired from malicious code samples but also malicious behavior information such as infection process and attack process of malicious code. We refer to this information as Malicious Code Behavior Information (MCBI) and we propose a method to predict security threats in a new environment by continuously managing it and defining an extension process to apply it to new environment. We believe that it can help to predict and respond to repeated malicious code attacks in a rapidly changing ICT environment.

In the future, we will continue to manage and extend the MCBI information to predict the security threats to new technologies and devices. We also plan to provide effective and continuous operation of these processes.

Acknowledgment

This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. NRF-2017R1E1A1A01075110).

References

[1] Somia Sahraoui and Azeddine Bilami, "Asymmetric End-to-End Security for Human-to-Thing Communications in the Internet of Things," in Proc. of IoT'16 Proceedings of the 6th International Conference on the Internet of Things, pp.131-139, November 07-09, 2016. Article (CrossRef Link).

[2] Meesun Kim, Hyun Ahn and Kwanghoon Pio Kim, "Process-Aware Internet of Things: A Conceptual Extension of the Internet of Things Framework and Architecture," KSII Transactions on Internet and Information Systems, vol. 10, no. 8, August 31, 2016. Article (CrossRef Link).

[3] Vu-Anh-Quang Nguyen, "Study on realtime control system in IoT based smart factory: Interference awareness, architectural elements, and its application," in Proc. of Information Science and Technology (ICIST), 2017 Seventh International Conference on, April 16-19, 2017. Article (CrossRef Link).

[4] H. Arasteh, V. Hosseinnezhad, V. Loia, A. Tommasetti, O. Troisi, M. Shafie-khah and P. Siano, "Iot-based Smart Cities: A Survey," in Proc. of Environment and Electrical Engineering (EEEIC),

2016 IEEE 16th International Conference on, June 7-10, 2016. Article (CrossRef Link).

[5] Jorge Alfonso, Nuria Sanchez, Jose Manuel Menendez and Emilio Cacheiro, "Cooperative ITS communications architecture: the FOTsis project approach and beyond," IETIntelligent Transport System, vol. 9, issue. 6, pp.591-598, August 06, 2015. Article (CrossRef Link).

[6] McAfee Labs, McAfee Labs Threats Report September 2018, September, 2018. Article (CrossRef Link).

[7] Ahmad Karim, Syed Adeel Ali Shah, Rosli Bin Salleh, Muhammad Arif, Rafidah Md Noor and Shahaboddin Shamshirband, "Mobile Botnet Attacks - an Emerging Threat: Classification, Review and Open Issues," KSII Transactions on Internet and Information Systems, vol. 9, no.4, April 30, 2015. Article (CrossRef Link).

[8] James A. Jerkins, "Motivating a market or regulatory solution to IoT insecurity with the Mirai botnet code," in Proc. of Computing and Communication Workshop and Conference (CCWC),

2017 IEEE 7th Annual, January 09-11, 2017. Article (CrossRef Link).

[9] Ahmed El-Kosairy and Marianne A. Azer, "Intrusion and ransomware detection system," in Proc. of 2018 1st International Conference on Computer Applications & Information Security (ICCAIS), September 27, 2018. Article (CrossRef Link).

[10] Taejin Lee and Jin Kwak, "Effective and Reliable Malware Group Classification for a Massive Malware Environment," International Journal of Distributed Sensor Networks, Hindawi Publishing Corporation, Volume 2016, 2016. Article (CrossRef Link).

[11] Taejin Lee, Bomin Choi, Youngsang Shin and Jin Kwak, "Automatic malware mutant detection and group classification based on the n-gram and clustering coefficient," The Journal of Supercomputing, Springer, 18 December, 2015. Article (CrossRef Link).

[12] Zhang Fuyong and Zhao Tiezhu, "Malware Detection and Classification Based on ngrams Attribute Similarity," in Proc. of 2017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC), 21 July, 2017. Article (CrossRef Link).

[13] Arzu Gorgulu Kakisim, Mert Nar, Necmettin Carkaci and Ibrahim Sogukpinar, "Analysis and Evaluation of Dynamic Feature-Based Malware Detection Methods," Innovative Security Solutions for Information Technology and Communications (SECITC 2018), pp 247-258, Feb, 2019. Article (CrossRef Link).

Seul-Ki Choi received Korea B.S. and M.S degrees in Department of Information Security Engineering from Soonchunhyang University. He is currently pursuing the Ph.D. degree in Department of Computer Engineering with Ajou University, Korea. His research interests include IoT Security, Vulnerability & Malware analysis and Cryptographic protocols.

Tae-Jin Lee is a professor at Dept. Of Information Security in Hoseo University, Korea. He received the Ph.D. degree from Ajou University, Korea. Professor Lee's current research interests focus on System security, Malware Analysis.

Jin Kwak is a professor at Dept. Of Cyber Security in Ajou University, Korea. He received the Ph.D. degree from SKKU, Korea. His research interests include Cryptographic protocols, Applied security mechanisms for Cloud and Big Data system and so on.

Seul-Ki Choi (1), Taejin Lee (2) and Jin Kwak (3*)

(1) ISAA Lab., Department of Computer Engineering, Ajou University, Republic of Korea

[e-mail: skchoi.isaa@gmail.com]

(2) Department of Computer Engineering, Hoseo University, Republic of Korea

[e-mail: kinjecs0@gmail.com]

(3) Department of Cyber Security, Ajou University, Republic of Korea

[e-mail: security@ajou.ac.kr]

(*) Corresponding author: Jin Kwak

Received October 2, 2018; revised January 8, 2019; accepted February 28, 2019; published March 31 2019

A preliminary version of this paper was presented at APIC-IST 2018, and was selected by the conference review process.

http://doi.org/10.3837/tiis.2019.03.028
Table 1. Subsection of MCBI

Section      Subsection         Description

             Infection &        - Media or service used as a route of
             propagation route  infection and propagation of malicious
                                code
Infection &  Infection &        - Features classified in malware
Propagation  propagation type   infection and propagation process
                                (e.g., the method of transmitting
                                malicious code itself directly
                                to an attack target)
             User dependency    - User dependency in malicious
                                code infections and propagation.
             Attack target      - The target for malicious code to
                                perform attack behavior
Attack       Executor           - An entity that execute malicious code
                                that reaches the target system
             Attack behavior    - Actions caused by malicious code
                                to attack targets

Table 2. Contents of infection & propagation route

Subsection   Contents           Description

Infection &  Removable data     - A device for storing and moving data,
Propagation  storage            such as USB, CD, HDD, flash memory etc.
route                           - It is a malicious code infecting and
                                propagating means that occurs even in
                                an environment where security is
                                maintained by disconnecting from the
                                external network.
             Web/Cloud storage  - Storage that exists in a networked
                                space such as web and cloud
                                environment.
                                - It is used to use web service or to
                                store data.

             Local network      - path that infects or propagates
                                malicious code using internal
                                network protocols such as ARP spoofing.
             P2P                - Data sharing technique used to share
                                data between users without going
                                through the server.
             Mobile device      - Mobile devices are data terminal
                                with mobility and computing
                                capabilities, such as Smartphones,
                                IoT devices and wearable devices.
                                - These mobile devices have been
                                recently used in malicious
                                code infections and propagation routes
                                because they have appropriate
                                computing ability and various
                                functions to infect or propagate
                                malicious codes.
             Message service    - Specific message service available
                                for each device such as
                                SMS / MMS of smart phone.
                                - It is a malicious code infecting and
                                propagating method that is still used
                                today, such as providing a path to
                                access malicious code using social
                                engineering attack technique called
                                smishing.
             E-mail             - A method of exchanging messages
                                between people using electronic
                                devices without periodic access
                                - Although it is not widely used due
                                to the development of application
                                services provided by message service
                                and mobile device, it is still used as
                                a malicious code infecting and
                                propagating path because of its
                                advantage of sending messages without
                                mutual periodic access.
             Web board          - Community space where users can
                                upload / download information between
                                users.
                                - Malicious code can be spread to
                                infected and unspecified users, or
                                attacked to administrator by using
                                vulnerability of web board.
             Web application    - Applications that utilize Web
                                services, such as Web browsers
                                - Current web applications are used in
                                a mixture of different kinds of
                                applications to give users a visible
                                effect. An attacker can attempt to
                                propagate and infect malicious code to
                                users of the web application through
                                some of these vulnerable applications.
             TCP/UDP port       - TCP / UDP-based services
             service            - Various services are provided
                                through ports as well as well-known
                                ports.

Table 3. Contents of infection & propagation type

Subsection   Contents         Description

Infection &  Direct           - Infection and propagation through
Propagation                   direct access such as downloading
Type                          malicious code directly through network
                              service or copying directly.
             Indirect         - Indirectly infecting and propagating
                              by suggesting a method of accessing
                              malicious code (Access link included in
                              SMS/MMS etc.) through a social
                              engineering method
             Vulnerabilities  - There are various types such as
                              unauthorized access or elevation of
                              privilege by infecting and spreading
                              using security vulnerabilities.
             Weak setting     - Security related settings are not
                              properly set up such as using default
                              password, activating guest user etc.

Table 4. Contents of user dependency

Subsection  Contents     Description

User        Need         - System user involvement is essential to
Dependency               successful infection and propagation
                         - Since system user intervention is necessary,
                         social engineering attack is often used.
                         (e.g., malicious code download & execute,
                         permission agreement etc.)
            Unnecessary  - Malicious code can be infected and
                         propagated without the involvement of the
                         system user.
                         - Malicious code infections and propagation
                         methods using security vulnerabilities and
                         weak settings, such as unauthorized access
                         through privilege elevation

Table 5. Contents of attack target

Subsection  Contents     Description

Attack      User         - System user infected with malicious code is
Target                   the victim of malicious code.
                         - The user may be attacked to perform a
                         secondary security threat using the user's
                         identity. (e.g., disguised user, false
                         information leakage, access to other
                         user etc.)
            System       - Malicious code infected system itself is
                         the target of malicious code.
                         - If the infected system is an attack target,
                          the attacker targets the service running on
                          the system and the configuration information
                          of the system.
                         - In order to ensure the continuous operation
                         of malicious code, the boot process can be
                         attacked or the network service can be
                         attacked for the second intrusion.
                         - In order to utilize the resources of the
                         infected system, the operation policy of the
                         system can be targeted.
                         (e.g., crypto mining, DDoS botnet etc.)
            Information  - Information of the user/system stored and
                         managed inside the system is target of
                         malicious code.
                         - In order to sniff information such as OTP
                         and user password, input information can be
                         targeted for attack.
                         - Malicious code can target the stored data
                         to collect data related to the user or system.
                         - System information can be attacked for
                         continuous intrusion and attack.

Table 6. Contents of Executor

Subsection  Contents     Description

Executor    User         - Users execute malicious code that reaches
                         the target system directly.
                         - If the executor of the malicious code is a
                         user, it is related to the user dependency
                         of the infection & propagation section.
            OS           - OS execute malicious code.
                         - There is a case where malicious code is
                         inserted into the scheduler of the operating
                         system.
                         - Malicious code can be executed by
                         modifying processes that run automatically
                         in the operating system.
            Application  - Malicious code execution through
                         applications with macros.
                         - Execute malicious code using vulnerable
                         applications.
                         - Execute malicious code through other
                         malicious code.
            BIOS         - The BIOS that manages booting the system
                         is directly related to the execution of the
                         malicious code.
                         - These malicious code are executed before
                         the operating system is loaded.
                         - By inserting malicious code into the
                         MBR(Master Boot Record), the malicious code
                         can be run before the operating system
                         is booted.

Table 7. Contents of attack behavior

Subsection  Contents    Description

Attack      System      - The attacking behavior of the malicious code
Behavior                is related to the operation of the infected
                        system.
                        - Malicious code exploits system privileges
                        to perform unwanted actions.
                        - It deliberately depletes system resources and
                        causes system failure.
                        - Network and security-related configuration
                        information is forcibly changed so that
                        malicious code can perform a attack.
            Process     - Malicious code attacks the process of infected
                        system.
                        - An attack that can control the execution and
                        termination of processes.
                        - Checking the status of the process and system
                        to check whether the anti-virus application is
                        running or not.
            Filesystem  - Malicious code attacks files stored and
                        managed by an infected system. (e.g., file
                        deletion, modulation, generation etc.)
            Network     - Malicious code performs network-based attack.
                        - To leak information about system and user or
                        stored data.
                        - When a remote attack is performed by
                        server-client communication between an attacker
                        and a victim, such as RAT(Remote Access Trojan).
                        - When it is related to an attack that uses
                        network traffic such as DDoS attack.
            Device      - Malicious code attacks device managed by an
                        infected system.
                        - It causes malfunction of input/output device
                        in PC environment.
                        - In the case of a recent IoT environment, when
                        attacking a server or a central control unit
                        managing a plurality of IoT devices.

Table 8. MCBI example for Mirai botnet code

Section      Subsection   Contents      Description

Infection &  Infection &  TCP/UDP       - irai botnet code uses the
Propagation  Propagation  port service  Telnet port(23) as the initial
             Route                      infection and penetration route.
             Infection &  Weak setting  - Mirai botnet code attempts to
             Propagation                infect IoT devices using the
             Type                       administrator default password.
             User         Unnecessary   - Mirai botnet code can be
             Dependency                 infected and propagated without
                                        the involvement of the system
                                        user.
Attack       Attack       System        - The Mirai botnet code targets
             Target                     the operating policy of the
                                        system in order to
                                        utilize the resources of the
                                        infected system.
            Executor     Application    - The Mirai botnet code performs
                                        a second malicious action by
                                        launching a malicious
                                        application that is nstalled
                                        after successful penetration
                                        into the IoT device.
             Attack       System        - The Mirai botnet code infects
             Behavior                   the system with additional
                                        command code to perform DDoS
                                        attacks on infected systems.
                                        - In order to keep the Mirai
                                        botnet code running, code is
                                        inserted to disable the reboot
                                        function.
                          Network       - The Mirai botnet code
                                        utilizes the network system
                                        resources of the infected IoT
                                        devices to perform DDoS attacks.
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Author:Choi, Seul-Ki; Lee, Taejin; Kwak, Jin
Publication:KSII Transactions on Internet and Information Systems
Article Type:Case study
Date:Mar 1, 2019
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