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Register a new userSuperstring-Based Sequence Obfuscation to Thwart Pattern Matching Attacks
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Added by
Bo Guan
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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User privacy can be compromised by matching user data traces to records of their previous behavior. The matching of the statistical characteristics of traces to prior user behavior has been widely studied. However, an adversary can also identify a user deterministically by searching data traces for a pattern that is unique to that user. Our goal is to thwart such an adversary by applying small artificial distortions to data traces such that each potentially identifying pattern is shared by a large number of users. Importantly, in contrast to statistical approaches, we develop data-independent algorithms that require no assumptions on the model by which the traces are generated. By relating the problem to a set of combinatorial questions on sequence construction, we are able to provide provable guarantees for our proposed constructions. We also introduce data-dependent approaches for the same problem. The algorithms are evaluated on synthetic data traces and on the Reality Mining Dataset to demonstrate their utility.
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Deep Neural Networks (DNNs) are well-known to be vulnerable to Adversarial Examples (AEs). A large amount of efforts have been spent to launch and heat the arms race between the attackers and defenders. Recently, advanced gradient-based attack techniques were proposed (e.g., BPDA and EOT), which have defeated a considerable number of existing defense methods. Up to today, there are still no satisfactory solutions that can effectively and efficiently defend against those attacks. In this paper, we make a steady step towards mitigating those advanced gradient-based attacks with two major contributions. First, we perform an in-depth analysis about the root causes of those attacks, and propose four properties that can break the fundamental assumptions of those attacks. Second, we identify a set of operations that can meet those properties. By integrating these operations, we design two preprocessing functions that can invalidate these powerful attacks. Extensive evaluations indicate that our solutions can effectively mitigate all existing standard and advanced attack techniques, and beat 11 state-of-the-art defense solutions published in top-tier conferences over the past 2 years. The defender can employ our solutions to constrain the attack success rate below 7% for the strongest attacks even the adversary has spent dozens of GPU hours.
We consider a key encapsulation mechanism (KEM) based on Module-LWE where reconciliation is performed on the 8-dimensional lattice $E_8$, which admits a fast CVP algorithm. Our scheme generates 256 bits of key and requires 3 or 4 bits of reconciliation per dimension. We show that it can outperform Kyber in terms of the modulus q with comparable error probability. We prove that our protocol is IND-CPA secure and improves the security level of Kyber by 7.3%.
As a research field of stream ciphers, the pursuit of a balance of security and practicality is the focus. The conditions for security usually have to satisfy at least high period and high linear complexity. Because the feedforward clock-controlled structure can provide quite a high period and utility, many sequence ciphers are constructed based on this structure. However, the past study of its linear complexity only works when the controlled sequence is an m-sequence. Using the theory of matrix over the ring and block matrix in this paper, we construct a more helpful method. It can estimate the lower bound of the linear complexity of the feedforward clock-controlled sequence. Even the controlled sequence has great linear complexity.
In this paper we introduce a variant of the Syndrome Decoding Problem (SDP), that we call Restricted SDP (R-SDP), in which the entries of the searched vector are defined over a subset of the underlying finite field. We prove the NP-completeness of R-SDP, via a reduction from the classical SDP, and describe algorithms which solve such new problem. We study the properties of random codes under this new decoding perspective, in the fashion of traditional coding theory results, and assess the complexity of solving a random R-SDP instance. As a concrete application, we describe how Zero-Knowledge Identification (ZK-ID) schemes based on SDP can be tweaked to rely on R-SDP, and show that this leads to compact public keys as well as significantly reduced communication costs. Thus, these schemes offer an improved basis for the construction of code-based digital signature schemes derived from identification schemes through the well-know Fiat-Shamir transformation.
Known for its decentralized and tamper-aware properties, blockchain is attractive to enhance the infrastructure of systems that have been constrained by traditionally centralized and vendor-locked environments. Although blockchain has commonly been used as the operational model behind cryptocurrency, it has far more foreseeable utilities in domains like healthcare, where efficient data flow is highly demanded. Particularly, blockchain and related technologies have been touted as foundational technologies for addressing healthcare interoperability challenges, such as promoting effective communications and securing data exchanges across various healthcare systems. Despite the increasing interests in leveraging blockchain technology to improve healthcare infrastructures, a major gap in literature is the lack of available recommendations for concrete architectural styles and design considerations for creating blockchain-based apps and systems with a healthcare focus. This research provides two contributions to bridge the gap in existing research. First, we introduce a pattern sequence for designing blockchain-based healthcare systems focused on secure and at-scale data exchange. Our approach adapts traditional software patterns and proposes novel patterns that take into account both the technical requirements specific to healthcare systems and the implications of these requirements on naive blockchain-based solutions. Second, we provide a pattern-oriented reference architecture using an example application of the pattern sequence for guiding software developers to design interoperable (on the technical level) healthcare IT systems atop blockchain-based infrastructures. The reference architecture focuses on minimizing storage requirements on-chain, preserving the privacy of sensitive information, facilitating scalable communications, and maximizing evolvability of the system.
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