skip to main content


Title: Session-level Adversary Intent-Driven Cyberattack Simulator
Recognizing the need for proactive analysis of cyber adversary behavior, this paper presents a new event-driven simulation model and implementation to reveal the efforts needed by attackers who have various entry points into a network. Unlike previous models which focus on the impact of attackers’ actions on the defender’s infrastructure, this work focuses on the attackers’ strategies and actions. By operating on a request-response session level, our model provides an abstraction of how the network infrastructure reacts to access credentials the adversary might have obtained through a variety of strategies. We present the current capabilities of the simulator by showing three variants of Bronze Butler APT on a network with different user access levels.  more » « less
Award ID(s):
1742789
NSF-PAR ID:
10190267
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
Proceedings of IEEE/ACM DS-RT 2020
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. The increasing penetration of cyber systems into smart grids has resulted in these grids being more vulnerable to cyber physical attacks. The central challenge of higher order cyber-physical contingency analysis is the exponential blow-up of the attack surface due to a large number of attack vectors. This gives rise to computational challenges in devising efficient attack mitigation strategies. However, a system operator can leverage private information about the underlying network to maintain a strategic advantage over an adversary equipped with superior computational capability and situational awareness. In this work, we examine the following scenario: A malicious entity intrudes the cyber-layer of a power network and trips the transmission lines. The objective of the system operator is to deploy security measures in the cyber-layer to minimize the impact of such attacks. Due to budget constraints, the attacker and the system operator have limits on the maximum number of transmission lines they can attack or defend. We model this adversarial interaction as a resource-constrained attacker-defender game. The computational intractability of solving large security games is well known. However, we exploit the approximately modular behavior of an impact metric known as the disturbance value to arrive at a linear-time algorithm for computing an optimal defense strategy. We validate the efficacy of the proposed strategy against attackers of various capabilities and provide an algorithm for a real-time implementation. 
    more » « less
  2. null (Ed.)
    Recent years have seen an increased interest towards strong security primitives for encrypted databases (such as oblivious protocols) that hide the access patterns of query execution and reveal only the volume of results. However recent work has shown that even volume leakage can enable the reconstruction of entire columns in the database. Yet existing attacks rely on a set of assumptions that are unrealistic in practice for example they (i) require a large number of queries to be issued by the user or (ii) assume certain distributions on the queries or underlying data (e.g. that the queries are distributed uniformly at random or that the database does not contain missing values). In this work we present new attacks for recovering the content of individual user queries assuming no leakage from the system except the number of results and avoiding the limiting assumptions above. Unlike prior attacks our attacks require only a single query to be issued by the user for recovering the keyword. Furthermore our attacks make no assumptions about the distribution of issued queries or the underlying data. Instead our key insight is to exploit the behavior of real-world applications. We start by surveying 11 applications to identify two key characteristics that can be exploited by attackers-(l) file injection and (ii) automatic query replay. We present attacks that leverage these two properties in concert with volume leakage independent of the details of any encrypted database system. Subsequently we perform an attack on the real Gmail web client by simulating a server-side adversary. Our attack on Gmail completes within a matter of minutes demonstrating the feasibility of our techniques. We also present three ancillary attacks for situations when certain mitigation strategies are employed. 
    more » « less
  3. The security of Internet-of-Things (IoT) devices in the residential environment is important due to their widespread presence in homes and their sensing and actuation capabilities. However, securing IoT devices is challenging due to their varied designs, deployment longevity, multiple manufacturers, and potentially limited availability of long-term firmware updates. Attackers have exploited this complexity by specifically targeting IoT devices, with some recent high-profile cases affecting millions of devices. In this work, we explore access control mechanisms that tightly constrain access to devices at the residential router, with the goal of precluding access that is inconsistent with legitimate users' goals. Since many residential IoT devices are controlled via applications on smartphones, we combine application sensors on phones with sensors at residential routers to analyze workflows. We construct stateful filters at residential routers that can require user actions within a registered smartphone to enable network access to an IoT device. In doing so, we constrain network packets only to those that are consistent with the user's actions. In our experiments, we successfully identified 100% of malicious traffic while correctly allowing more than 98% of legitimate network traffic. The approach works across device types and manufacturers with straightforward API and state machine construction for each new device workflow. 
    more » « less
  4. Sybil attacks present a significant threat to many Internet systems and applications, in which a single adversary inserts multiple colluding identities in the system to compromise its security and privacy. Recent work has advocated the use of social-network-based trust relationships to defend against Sybil attacks. However, most of the prior security analyses of such systems examine only the case of social networks at a single instant in time. In practice, social network connections change over time, and attackers can also cause limited changes to the networks. In this work, we focus on the temporal dynamics of a variety of social-network-based Sybil defenses. We describe and examine the effect of novel attacks based on: (a) the attacker's ability to modify Sybil-controlled parts of the social-network graph, (b) his ability to change the connections that his Sybil identities maintain to honest users, and (c) taking advantage of the regular dynamics of connections forming and breaking in the honest part of the social network. We find that against some defenses meant to be fully distributed, such as SybilLimit and Persea, the attacker can make dramatic gains over time and greatly undermine the security guarantees of the system. Even against centrally controlled Sybil defenses, the attacker can eventually evade detection (e.g. against SybilInfer and SybilRank) or create denial-of-service conditions (e.g. against Ostra and SumUp). After analysis and simulation of these attacks using both synthetic and real-world social network topologies, we describe possible defense strategies and the trade-offs that should be explored. It is clear from our findings that temporal dynamics need to be accounted for in Sybil defense or else the attacker will be able to undermine the system in unexpected and possibly dangerous ways. 
    more » « less
  5. The NTT (Nippon Telegraph and Telephone) Data Corporation report found that 80% of U.S. consumers are concerned about their smart home data security. The Internet of Things (IoT) technology brings many benefits to people's homes, and more people across the world are heavily dependent on the technology and its devices. However, many IoT devices are deployed without considering security, increasing the number of attack vectors available to attackers. Numerous Internet of Things devices lacking security features have been compromised by attackers, resulting in many security incidents. Attackers can infiltrate these smart home devices and control the home via turning off the lights, controlling the alarm systems, and unlocking the smart locks, to name a few. Attackers have also been able to access the smart home network, leading to data exfiltration. There are many threats that smart homes face, such as the Man-in-the-Middle (MIM) attacks, data and identity theft, and Denial of Service (DoS) attacks. The hardware vulnerabilities often targeted by attackers are SPI, UART, JTAG, USB, etc. Therefore, to enhance the security of the smart devices used in our daily lives, threat modeling should be implemented early on in developing any given system. This past Spring semester, Morgan State University launched a (senior) capstone project targeting undergraduate (electrical) engineering students who were thus allowed to research with the Cybersecurity Assurance and Policy (CAP) center for four months. The primary purpose of the capstone was to help students further develop both hardware and software skills while researching. For this project, the students mainly focused on the Arduino Mega Board. Some of the expected outcomes for this capstone project include: 1) understanding the physical board components, 2) learning how to attack the board through the STRIDE technique, 3) generating a Data Flow Diagram (DFD) of the system using the Microsoft threat modeling tool, 4) understanding the attack patterns, and 5) generating the threat based on the user's input. To prevent future threats and attacks from taking advantage of systems vulnerabilities, the practice of "threat modeling" is implemented. This method allows the analysis of potential attackers, including their goals and techniques, while also providing solutions and mitigation strategies. Although Threat modeling can be performed throughout the development of a system, implementing it during developmental stages will prevent further problems in the future. Threat Modeling is crucial because it will help identify any potential threat before it propagates in the system. Identifying threats and providing countermeasures will save both time and money while also keeping the consumers safe. As a result, students must grow to understand how essential detecting and preventing attacks are to protect consumer information systems and networks. At the end of this capstone project, students should take away hands-on skills in cyber defense. 
    more » « less