Context: Diversification and obfuscation are promising techniques for securing software and protecting computers from harmful malware. The goal of these techniques is not removing the security holes, but making it difficult for the attacker to exploit security vulnerabilities and perform successful attacks. Objective: There is an increasing body of research on the use of diversification and obfuscation techniques for improving software security; however, the overall view is scattered and the terminology is unstructured. Therefore, a coherent review gives a clear statement of state-of-the-art, normalizes the ongoing discussion and provides baselines for future research. Method: In this paper, systematic literature review is used as the method of the study to select the studies that discuss diversification/obfuscation techniques for improving software security. We present the process of data collection, analysis of data, and report the results. Results: As the result of the systematic search, we collected 357 articles relevant to the topic of our interest, published between the years 1993 and 2017. We studied the collected articles, analyzed the extracted data from them, presented classification of the data, and enlightened the research gaps. Conclusion: The two techniques have been extensively used for various security purposes and impeding various types of security attacks. There exist many different techniques to obfuscate/diversify programs, each of which targets different parts of the programs and is applied at different phases of software development life-cycle. Moreover, we pinpoint the research gaps in this field, for instance that there are still various execution environments that could benefit from these two techniques, including cloud computing, Internet of Things (IoT), and trusted computing. We also present some potential ideas on applying the techniques on the discussed environments.

Diversification and Obfuscation Techniques for Software Security: a Systematic Literature Review

Modern missions of government and private organizations rely on computer networks to operate. As evidenced by several well-publicized cyber breaches, these missions are under attack. Several cyber defensive measures have been proposed to mitigate this threat, some are meant to protect individual hosts on the network, and others are designed to protect the network at large. From a qualitative perspective, these mitigations seem to improve security, but there is no quantitative assessment of their effectiveness with respect to a complete network system and a cyber-supported mission for which the network exists. The purpose of this paper is to examine network-level cyber defensive mitigations and quantify their impact on network security and mission performance. Testing such mitigations in an live network environment is generally not possible due to the expense, and thus a modeling and simulation approach is utilized. Our approach employs a modularized hierarchical simulation framework to model a complete cy...

Quantifying the mission impact of network-level cyber defensive mitigations:

Quantitative security analysis of a dynamic network system under lateral movement-based attacks

The purpose of this chapter is to introduce cyber security researchers to key concepts in modern control and game theory that are relevant to Moving Target Defenses and Adaptive Cyber Defense. We begin by observing that there are fundamental differences between control models and game models that are important for security practitioners to understand. Those differences will be illustrated through simple but realistic cyber operations scenarios, especially with respect to the types and amounts of data require for modeling. In addition to modeling differences, there are a variety of ways to think about what constitutes a “solution.” Moreover, there are significant differences in the computational and information requirements to compute solutions for various types of Adaptive Cyber Defense problems. This material is presented in the context of the advances documented in this book, the various chapters of which describe advances made in the 2012 ARO ACD MURI.

Overview of Control and Game Theory in Adaptive Cyber Defenses

Network devices and user accounts often provide an initial entry point for attackers who wish to gain a foothold on a network, pivot to other hosts, and ultimately disrupt an organizational mission and/or steal valuable network resources. Several host-level cyber defensive measures have been proposed to mitigate this threat. Although these mitigations are intuitively appealing from a security perspective, there is a lack of quantitative analysis addressing their effectiveness with respect to the network as a whole and the mission that the network supports. Testing these mitigations in an operational setting is prohibitively expensive, and thus modeling and simulation approaches are sought, due to their relative low cost. Our goal is to investigate the network-scale effects of various host-level defensive mitigations both from the standpoint of cyber security and mission impact. Our approach utilizes a hierarchical framework to model a complex cyber system at multiple, appropriate scales. Experiments serve to provide quantitative assessment of host-level mitigations from a complete network system perspective.

Quantitative analysis of the mission impact for host-level cyber defensive mitigations

Moving target (MT) technologies are a class of cyber security defensive techniques that seek to protect computer networks by making them less homogenous, less static, and less deterministic in order to increase the complexity required for a successful cyber attack. MT techniques are associated with performance costs, and thus their effectiveness and overhead must be evaluated before deployment in a live setting. However, testing the effectiveness and usage costs of a newly-developed MT technique on a live computer network is a costly process. This paper presents an agent-based approach for simulating an operational network and measuring the impact of security policies that incorporate MT technologies. The proposed agent-based simulation system (ABS) is intended to evaluate candidate MT techniques and provide important and cost-effective support for the overall MT technology development and testing process. We demonstrate the ABS model via a case study that evaluates a particular MT technology and discuss how this evaluation via simulation can be used to support the larger process of MT technology development and testing.

Agent-based simulation in support of moving target cyber defense technology development and evaluation

Periodic randomization of a computer programâs binary code is an attractive technique for defending against several classes of advanced threats. In this paper we describe a model of attacker-defender interaction in which the defender employs such a technique against an attacker who is actively constructing an exploit using Return Oriented Programming (ROP). In order to successfully build a working exploit, the attacker must guess the locations of several small chunks of program code (i.e., gadgets) in the defended programâs memory space. As the attacker continually guesses, the defender periodically rotates to a newly randomized variant of the program, effectively negating any gains the attacker made since the last rotation. Although randomization makes the attackerâs task more difficult, it also incurs a cost to the defender. As such, the defenderâs goal is to find an acceptable balance between utility degradation (cost) and security (benefit). One way to measure these two competing factors is the total task latency introduced by both the attacker and any defensive measures taken to thwart him. We simulated a number of diversity strategies under various threat scenarios and present the measured impact on the defenderâs task.

Simulation based Evaluation of a Code Diversification Strategy

Periodic randomization of a computer program’s binary code is an attractive technique for defending against several classes of advanced threats. In this paper we describe a model of attacker-defender interaction in which the defender employs such a technique against an attacker who is actively constructing an exploit using Return Oriented Programming (ROP). In order to successfully build a working exploit, the attacker must guess the locations of several small chunks of program code, known as gadgets, in the defended program’s memory space. The defender thwarts the attacker’s efforts by periodically re-randomizing his code. Randomization incurs some performance cost, therefore an ideal strategy strikes an acceptable balance between utility degradation (cost) and security (benefit). We present risk aware and risk agnostic policy recommendations that were generated using simulation techniques. We found that policies that create low volatility environments are ideal for risk sensitive actors while policies that favor high system performance are more suitable for higher risk appetites.

Simulation Driven Policy Recommendations for Code Diversity

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Agent-based simulation in support of moving target cyber defense technology development and evaluation

Quantitative analysis of the mission impact for host-level cyber defensive mitigations

Simulation based Evaluation of a Code Diversification Strategy

Simulation Driven Policy Recommendations for Code Diversity