Rational Multiparty Computation

The field of rational cryptography considers the design of cryptographic protocols in the presence of rational agents seeking to maximize local utility functions. This departs from the standard secure multiparty computation setting, where players are assumed to be either honest or malicious. ^ We detail the construction of both a two-party and a multiparty game theoretic framework for constructing rational cryptographic protocols. Our framework specifies the utility function assumptions necessary to realize the privacy, correctness, and fairness guarantees for protocols. We demonstrate that our framework correctly models cryptographic protocols, such as rational secret sharing, where existing work considers equilibrium concepts that yield unreasonable equilibria. Similarly, we demonstrate that cryptography may be applied to the game theoretic domain, constructing an auction market not realizable in the original formulation. Additionally, we demonstrate that modeling players as rational agents allows us to design a protocol that destabilizes coalitions. Thus, we establish a mutual benefit from combining the two fields, while demonstrating the applicability of our framework to real-world market environments.^ We also give an application of game theory to adversarial interactions where cryptography is not necessary. Specifically, we consider adversarial machine learning, where the adversary is rational and reacts to the presence of a data miner. We give a general extension to classification algorithms that returns greater expected utility for the data miner than existing classification methods

Cyber-security Risk Assessment

Cyber-security domain is inherently dynamic. Not only does system configuration changes frequently (with new releases and patches), but also new attacks and vulnerabilities are regularly discovered. The threat in cyber-security is human, and hence intelligent in nature. The attacker adapts to the situation, target environment, and countermeasures. Attack actions are also driven by attacker's exploratory nature, thought process, motivation, strategy, and preferences. Current security risk assessment is driven by cyber-security expert's theories about this attacker behavior. The goal of this dissertation is to automatically generate the cyber-security risk scenarios by: * Capturing diverse and dispersed cyber-security knowledge * Assuming that there are unknowns in the cyber-security domain, and new knowledge is available frequently * Emulating the attacker's exploratory nature, thought process, motivation, strategy, preferences and his/her interaction with the target environment * Using the cyber-security expert's theories about attacker behavior The proposed framework is designed by using the unique cyber-security domain requirements identified in this dissertation and by overcoming the limitations of current risk scenario generation frameworks. The proposed framework automates the risk scenario generation by using the knowledge as it becomes available (or changes). It supports observing, encoding, validating, and calibrating cyber-security expert's theories. It can also be used for assisting the red-teaming process. The proposed framework generates ranked attack trees and encodes the attacker behavior theories. These can be used for prioritizing vulnerability remediation. The proposed framework is currently being extended for developing an automated threat response framework that can be used to analyze and recommend countermeasures. This framework contains behavior driven countermeasures that uses the attacker behavior theories to lead the attacker away from the system to be protected

Simulated penetration testing and mitigation analysis

Da Unternehmensnetzwerke und Internetdienste stetig komplexer werden, wird es immer schwieriger, installierte Programme, Schwachstellen und Sicherheitsprotokolle zu überblicken. Die Idee hinter simuliertem Penetrationstesten ist es, Informationen über ein Netzwerk in ein formales Modell zu transferiern und darin einen Angreifer zu simulieren. Diesem Modell fügen wir einen Verteidiger hinzu, der mittels eigener Aktionen versucht, die Fähigkeiten des Angreifers zu minimieren. Dieses zwei-Spieler Handlungsplanungsproblem nennen wir Stackelberg planning. Ziel ist es, Administratoren, Penetrationstestern und der Führungsebene dabei zu helfen, die Schwachstellen großer Netzwerke zu identifizieren und kosteneffiziente Gegenmaßnahmen vorzuschlagen. Wir schaffen in dieser Dissertation erstens die formalen und algorithmischen Grundlagen von Stackelberg planning. Indem wir dabei auf klassischen Planungsproblemen aufbauen, können wir von gut erforschten Heuristiken und anderen Techniken zur Analysebeschleunigung, z.B. symbolischer Suche, profitieren. Zweitens entwerfen wir einen Formalismus für Privilegien-Eskalation und demonstrieren die Anwendbarkeit unserer Simulation auf lokale Computernetzwerke. Drittens wenden wir unsere Simulation auf internetweite Szenarien an und untersuchen die Robustheit sowohl der E-Mail-Infrastruktur als auch von Webseiten. Viertens ermöglichen wir mittels webbasierter Benutzeroberflächen den leichten Zugang zu unseren Tools und Analyseergebnissen.As corporate networks and Internet services are becoming increasingly more complex, it is hard to keep an overview over all deployed software, their potential vulnerabilities, and all existing security protocols. Simulated penetration testing was proposed to extend regular penetration testing by transferring gathered information about a network into a formal model and simulate an attacker in this model. Having a formal model of a network enables us to add a defender trying to mitigate the capabilities of the attacker with their own actions. We name this two-player planning task Stackelberg planning. The goal behind this is to help administrators, penetration testing consultants, and the management level at finding weak spots of large computer infrastructure and suggesting cost-effective mitigations to lower the security risk. In this thesis, we first lay the formal and algorithmic foundations for Stackelberg planning tasks. By building it in a classical planning framework, we can benefit from well-studied heuristics, pruning techniques, and other approaches to speed up the search, for example symbolic search. Second, we design a theory for privilege escalation and demonstrate the applicability of our framework to local computer networks. Third, we apply our framework to Internet-wide scenarios by investigating the robustness of both the email infrastructure and the web. Fourth, we make our findings and our toolchain easily accessible via web-based user interfaces

Cryptographic Analysis of Secure Messaging Protocols

Instant messaging applications promise their users a secure and private way to communicate. The validity of these promises rests on the design of the underlying protocol, the cryptographic primitives used and the quality of the implementation. Though secure messaging designs exist in the literature, for various reasons developers of messaging applications often opt to design their own protocols, creating a gap between cryptography as understood by academic research and cryptography as implemented in practice. This thesis contributes to bridging this gap by approaching it from both sides: by looking for flaws in the protocols underlying real-world messaging applications, as well as by performing a rigorous analysis of their security guarantees in a provable security model.Secure messaging can provide a host of different, sometimes conflicting, security and privacy guarantees. It is thus important to judge applications based on the concrete security expectations of their users. This is particularly significant for higher-risk users such as activists or civil rights protesters. To position our work, we first studied the security practices of protesters in the context of the 2019 Anti-ELAB protests in Hong Kong using in-depth, semi-structured interviews with participants of these protests. We report how they organised on different chat platforms based on their perceived security, and how they developed tactics and strategies to enable pseudonymity and detect compromise.Then, we analysed two messaging applications relevant in the protest context: Bridgefy and Telegram. Bridgefy is a mobile mesh messaging application, allowing users in relative proximity to communicate without the Internet. It was being promoted as a secure communication tool for use in areas experiencing large-scale protests. We showed that Bridgefy permitted its users to be tracked, offered no authenticity, no effective confidentiality protections and lacked resilience against adversarially crafted messages. We verified these vulnerabilities by demonstrating a series of practical attacks.Telegram is a messaging platform with over 500 million users, yet prior to this work its bespoke protocol, MTProto, had received little attention from the cryptographic community. We provided the first comprehensive study of the MTProto symmetric channel as implemented in cloud chats. We gave both positive and negative results. First, we found two attacks on the existing protocol, and two attacks on its implementation in official clients which exploit timing side channels and uncover a vulnerability in the key exchange protocol. Second, we proved that a fixed version of the symmetric MTProto protocol achieves security in a suitable bidirectional secure channel model, albeit under unstudied assumptions. Our model itself advances the state-of-the-art for secure channels

Secure authentication and key agreement via abstract multi-agent interaction

Authentication and key agreement are the foundation for secure communication over the Internet. Authenticated Key Exchange (AKE) protocols provide methods for communicating parties to authenticate each other, and establish a shared session key by which they can encrypt messages in the session. Within the category of AKE protocols, symmetric AKE protocols rely on pre-shared master keys for both services. These master keys can be transformed after each session in a key-evolving scheme to provide the property of forward secrecy, whereby the compromise of master keys does not allow for the compromise of past session keys. This thesis contributes a symmetric AKE protocol named AMI (Authentication via Multi-Agent Interaction). The AMI protocol is a novel formulation of authentication and key agreement as a multi-agent system, where communicating parties are treated as autonomous agents whose behavior within the protocol is governed by private agent models used as the master keys. Parties interact repeatedly using their behavioral models for authentication and for agreeing upon a unique session key per communication session. These models are evolved after each session to provide forward secrecy. The security of the multi-agent interaction process rests upon the difficulty of modeling an agent's decisions from limited observations about its behavior, a long-standing problem in AI research known as opponent modeling. We conjecture that it is difficult to efficiently solve even by a quantum computer, since the problem is fundamentally one of missing information rather than computational hardness. We show empirically that the AMI protocol achieves high accuracy in correctly identifying legitimate agents while rejecting different adversarial strategies from the security literature. We demonstrate the protocol's resistance to adversarial agents which utilize random, replay, and maximum-likelihood estimation (MLE) strategies to bypass the authentication test. The random strategy chooses actions randomly without attempting to mimic a legitimate agent. The replay strategy replays actions previously observed by a legitimate client. The MLE strategy estimates a legitimate agent model using previously observed interactions, as an attempt to solve the opponent modeling problem. This thesis also introduces a reinforcement learning approach for efficient multi-agent interaction and authentication. This method trains an authenticating server agent's decision model to take effective probing actions which decrease the number of interactions in a single session required to successfully reject adversarial agents. We empirically evaluate the number of interactions required for a trained server agent to reject an adversarial agent, and show that using the optimized server leads to a much more sample-efficient interaction process than a server agent selecting actions by a uniform-random behavioral policy. Towards further research on and adoption of the AMI protocol for authenticated key-exchange, this thesis also contributes an open-source application written in Python, PyAMI. PyAMI consists of a multi-agent system where agents run on separate virtual machines, and communicate over low-level network sockets using TCP. The application supports extending the basic client-server setting to a larger multi-agent system for group authentication and key agreement, providing two such architectures for different deployment scenarios

An Explanatory Model of Motivation for Cyber-Attacks Drawn from Criminological Theories

A new influence model for Cyber Security is presented that deals with security attacks and implementation of security measures from an attacker's perspective. The underlying hypothesis of this model is that Criminological theories of Rational Choice, Desire for Control, and Low Self-Control are relevant to cybercrime and thereby aid in the understanding its basic Motivation. The model includes the roles of Consequences, Moral Beliefs such as Shame and Embarrassment together with Formal Sanctions in deterring cybercrime, as well as role of Defense Posture to limit the Opportunity to attack and increase the likelihood that an attacker will be detected and exposed. One of the motivations of the study was the observation that few attempts have been made to understand cybercrime, in the context of typical crime because: (a) an attacker may consider his actions as victimless due to remoteness of the victim; (b) ease to commit cybercrimes due to opportunities afforded by the Internet and its accessibility, and readily available tools and knowledge for an attack; and (c) vagueness of cybercrime laws that makes prosecution difficult. In developing the model, information from studies in classical crime was related to Cybercrime allowing for analysis of past cyber-attacks, and subsequently preventing future IS attacks, or mitigating their effects. The influence model's applicability is demonstrated by applying it to case studies of actual information attacks which were prosecuted through the United States Courts, and whose judges' opinions are used for statements of facts. Additional, demonstration of the use and face validity of the model is through the mapping of the model to major annual surveys' and reports' results of computer crime. The model is useful in qualitatively explaining "best practices" in protecting information assets and in suggesting emphasis on security practices based on similar results in general criminology

Algorithm-Substitution Attacks on Cryptographic Puzzles

In this work, we study and formalize security notions for algorithm substitution attacks (ASAs) on em cryptographic puzzles. Puzzles are difficult problems that require an investment of computation, memory, or some other related resource. They are heavily used as a building block for the consensus networks used by cryptocurrencies. These include primitives such as proof-of-work, proof-of-space, and verifiable delay functions (VDFs). Due to economies of scale, these networks increasingly rely on a small number of companies to construct opaque hardware or software (e.g., GPU or FPGA images): this dependency raises concerns about cryptographic subversion. Unlike the algorithms considered by previous ASAs, cryptographic puzzles do not rely on secret keys and thus enable a very different set of attacks. We first explore the threat model for these systems and then propose concrete attacks that (1) selectively reduce a victim\u27s solving capability ( e.g., hashrate) and (2) exfiltrate puzzle solutions to an attacker. We then propose defenses, several of which can be applied to existing cryptocurrency hardware with minimal changes. We also find that mining devices for many major proof-of-work cryptocurrencies already demonstrate errors exactly how a potentially subverted device would. Given that these attacks are relevant to all proof of work cryptocurrencies that have a combined market capitalization of around a few hundred billion dollars (2022), we recommend that all vulnerable mining protocols consider making the suggested adaptations today

Static-Memory-Hard Functions, and Modeling the Cost of Space vs. Time

A series of recent research starting with (Alwen and Serbinenko, STOC 2015) has deepened our understanding of the notion of memory-hardness in cryptography — a useful property of hash functions for deterring large-scale password-cracking attacks — and has shown memory-hardness to have intricate connections with the theory of graph pebbling. Definitions of memory-hardness are not yet unified in the somewhat nascent field of memory-hardness, however, and the guarantees proven to date are with respect to a range of proposed definitions. In this paper, we observe two significant and practical considerations that are not analyzed by existing models of memory-hardness, and propose new models to capture them, accompanied by constructions based on new hard-to-pebble graphs. Our contribution is two-fold, as follows. First, existing measures of memory-hardness only account for dynamic memory usage (i.e., memory read/written at runtime), and do not consider static memory usage (e.g., memory on disk). Among other things, this means that memory requirements considered by prior models are inherently upper-bounded by a hash function’s runtime; in contrast, counting static memory would potentially allow quantification of much larger memory requirements, decoupled from runtime. We propose a new definition of static-memory-hard function (SHF) which takes static memory into account: we model static memory usage by oracle access to a large preprocessed string, which may be considered part of the hash function description. Static memory requirements are complementary to dynamic memory requirements: neither can replace the other, and to deter large-scale password-cracking attacks, a hash function will benefit from being both dynamic memory-hard and static-memory-hard. We give two SHF constructions based on pebbling. To prove static-memory-hardness, we define a new pebble game (“black-magic pebble game”), and new graph constructions with optimal complexity under our proposed measure. Moreover, we provide a prototype implementation of our first SHF construction (which is based on pebbling of a simple “cylinder” graph), providing an initial demonstration of practical feasibility for a limited range of parameter settings. Secondly, existing memory-hardness models implicitly assume that the cost of space and time are more or less on par: they consider only linear ratios between the costs of time and space. We propose a new model to capture nonlinear time-space trade-offs: e.g., how is the adversary impacted when space is quadratically more expensive than time? We prove that nonlinear tradeoffs can in fact cause adversaries to employ different strategies from linear tradeoffs. Finally, as an additional contribution of independent interest, we present an asymptotically tight graph construction that achieves the best possible space complexity up to log log n-factors for an existing memory-hardness measure called cumulative complexity in the sequential pebbling model

Overcoming Data Breaches and Human Factors in Minimizing Threats to Cyber-Security Ecosystems

This mixed-methods study focused on the internal human factors responsible for data breaches that could cause adverse impacts on organizations. Based on the Swiss cheese theory, the study was designed to examine preventative measures that managers could implement to minimize potential data breaches resulting from internal employees\u27 behaviors. The purpose of this study was to provide insight to managers about developing strategies that could prevent data breaches from cyber-threats by focusing on the specific internal human factors responsible for data breaches, the root causes, and the preventive measures that could minimize threats from internal employees. Data were collected from 10 managers and 12 employees from the business sector, and 5 government managers in Ivory Coast, Africa. The mixed methodology focused on the why and who using the phenomenological approach, consisting of a survey, face-to-face interviews using open-ended questions, and a questionnaire to extract the experiences and perceptions of the participants about preventing the adverse consequences from cyber-threats. The results indicated the importance of top managers to be committed to a coordinated, continuous effort throughout the organization to ensure cyber security awareness, training, and compliance of security policies and procedures, as well as implementing and upgrading software designed to detect and prevent data breaches both internally and externally. The findings of this study could contribute to social change by educating managers about preventing data breaches who in turn may implement information accessibility without retribution. Protecting confidential data is a major concern because one data breach could impact many people as well as jeopardize the viability of the entire organization