In this paper, we introduce a formal notion of partial compliance, called Attack-resistance, of a computer program running together with a defense mechanism w.r.t a non-exploitability specification. In our setting, a program may contain exploitable vulnerabilities, such as buffer overflows, but appropriate defense mechanisms built into the program or the operating system render such vulnerabilities hard to exploit by certain attackers, usually relying on the strength of the randomness of a probabilistic transformation of the environment or the program and some knowledge on the attacker's goals and attack strategy. We are motivated by the reality that most large-scale programs have vulnerabilities despite our best efforts to get rid of them. Security researchers have responded to this state of affairs by coming up with ingenious defense mechanisms such as address space layout randomization (ASLR) or instruction set randomization (ISR) that provide some protection against exploitation. However, implementations of such mechanism have been often shown to be insecure, even against the attacks they were designed to prevent. By formalizing this notion of attack-resistance we pave the way towards addressing the questions: "How do we formally analyze defense mechanisms? Is there a mathematical way of distinguishing effective defense mechanisms from ineffective ones? Can we quantify and show that these defense mechanisms provide formal security guarantees, albeit partial, even in the presence of exploitable vulnerabilities?". To illustrate our approach we discuss under which circumstances ISR implementations comply with the Attack-resistance definition.
Hardware IP protection has been one of the most critical areas of research in the past years. Recently, attacks on hardware IPs (such as reverse engineering or cloning) have evolved as attackers have developed sophisticated techniques. Therefore, hardware obfuscation has been introduced as a powerful tool to protect IPs against piracy attacks. However, many recent attempts to break existing obfuscation methods have been successful in unlocking the IP and restoring its functionality. In this paper, we propose SARO, a Scalable Attack-Resistant Obfuscation that provides a robust functional and st…
Hash-based message authentication codes are an extremely simple yet hugely effective construction for producing keyed message digests using shared secrets. HMACs have seen widespread use as ad-hoc digital signatures in many Internet applications. While messages signed with an HMAC are secure against sender impersonation and tampering in transit, if used alone they are susceptible to replay attacks. We propose a construction that extends HMACs to produce a keyed message digest that has a finite validity period. We then propose a message signature scheme that uses this time-dependent MAC along w…
In mobile ad hoc networks, by attacking the corresponding routing protocol, an attacker can easily disturb the operations of the network. For ad hoc networks, till now many secured routing protocols have been proposed which contains some disadvantages. Therefore security in ad hoc networks is a controversial area till now. In this paper, we proposed a Lightweight and Attack Resistant Authenticated Routing Protocol (LARARP) for mobile ad hoc networks. For the route discovery attacks in MANET routing protocols, our protocol gives an effective security. It supports the node to drop the invalid pa…
Nodes in route-restricted overlays have an immutable set of neighbors, explicitly specified by their users. Popular examples include payment networks such as the Lightning network as well as social overlays such as the Dark Freenet. Routing algorithms are central to such overlays as they enable communication between nodes that are not directly connected. Recent results show that algorithms based on spanning trees are the most promising provably efficient choice. However, all suggested solutions fail to address how distributed spanning tree algorithms can deal with active denial of service atta…
Side-channel attacks are efficient attacks against cryptographic devices. They use only quantities observable from outside, such as the duration and the power consumption. Attacks against synchronous devices using electric observations are facilitated by the fact that all transitions occur simultaneously with some global clock signal. Asynchronous control remove this synchronization and therefore makes it more difficult for the attacker to insulate \emph{interesting intervals}. In addition the coding of data in an asynchronous circuit is inherently more difficult to attack. This article descri…
In this paper we describe our flexible ECDSA design for elliptic curve over binary extended fields GF(2l). We investigated its resistance against Horizontal Collision Correlation Attacks (HCCA). Due to the fact that our design is based on the Montgomery kP algorithm using Lopez-Dahab projective coordinates the scalar k cannot be successful revealed using HCCA, but this kind of attacks can be helpful to divide the measured traces into parts that correspond to processing of a single bit of the scalar k. The most important contribution of this paper is that our flexible field multiplier is resist…
Microarchitectural Data Sampling (MDS) is a set of hardware vulnerabilities in Intel CPUs that allows an attacker to leak bytes of data from memory loads and stores across various security boundaries. On affected CPUs, some of these vulnerabilities were patched via microcode updates. Additionally, Intel announced that the newest microarchitectures, namely Cascade Lake and Ice Lake, were not affected by MDS. While Cascade Lake turned out to be vulnerable to the ZombieLoad v2 MDS attack (also known as TAA), Ice Lake was not affected by this attack. In this technical report, we show a variant of …
Mobile devices store a diverse set of private user data and have gradually become a hub to control users' other personal Internet-of-Things devices. Access control on mobile devices is therefore highly important. The widely accepted solution is to protect access by asking for a password. However, password authentication is tedious, e.g., a user needs to input a password every time she wants to use the device. Moreover, existing biometrics such as face, fingerprint, and touch behaviors are vulnerable to forgery attacks. We propose a new touch-based biometric authentication system that is passiv…
Meltdown and Spectre exploit microarchitectural changes the CPU makes during transient out-of-order execution. Using side-channel techniques, these attacks enable leaking arbitrary data from memory. As state-of-the-art software mitigations for Meltdown may incur significant performance overheads, they are only seen as a temporary solution. Thus, software mitigations are disabled on more recent processors, which are not susceptible to Meltdown anymore. In this paper, we show that Meltdown-like attacks are still possible on recent CPUs which are not vulnerable to the original Meltdown attack. We…
Lattice based encryption schemes and linear code based encryption schemes have received extensive attention in recent years since they have been considered as post-quantum candidate encryption schemes. Though LLL reduction algorithm has been one of the major cryptanalysis techniques for lattice based cryptographic systems, key recovery cryptanalysis techniques for linear code based cryptographic systems are generally scheme specific. In recent years, several important techniques such as Sidelnikov-Shestakov attack, filtration attacks, and algebraic attacks have been developed to crypt-analyze …
In this article, we describe a methodology that aims at either breaking or proving the security of CRT-RSA implementations against fault injection attacks. In the specific case-study of the BellCoRe attack, our work bridges a gap between formal proofs and implementation-level attacks. We apply our results to three implementations of CRT-RSA, namely the unprotected one, that of Shamir, and that of Aumüller et al. Our findings are that many attacks are possible on both the unprotected and the Shamir implementations, while the implementation of Aumüller et al. is resistant to all single-fault att…
Global Positioning System (GPS) is used ubiquitously in a wide variety of applications ranging from navigation and tracking to modern smart grids and communication networks. However, it has been demonstrated that modern GPS receivers are vulnerable to signal spoofing attacks. For example, today it is possible to change the course of a ship or force a drone to land in an hostile area by simply spoofing GPS signals. Several countermeasures have been proposed in the past to detect GPS spoofing attacks. These countermeasures offer protection only against naive attackers. They are incapable of dete…
Physical-layer based key generation schemes exploit the channel reciprocity for secret key extraction, which can achieve information-theoretic secrecy against eavesdroppers. Such methods, although practical, have been shown to be vulnerable against man-in-the-middle (MitM) attacks, where an active adversary, Mallory, can influence and infer part of the secret key generated between Alice and Bob by injecting her own packet upon observing highly correlated channel/RSS measurements from Alice and Bob. As all the channels remain stable within the channel coherence time, Mallory's injected packets …
We address the problem of shoulder-surfing attacks on authentication schemes by proposing IllusionPIN (IPIN), a PIN-based authentication method that operates on touchscreen devices. IPIN uses the technique of hybrid images to blend two keypads with different digit orderings in such a way, that the user who is close to the device is seeing one keypad to enter her PIN, while the attacker who is looking at the device from a bigger distance is seeing only the other keypad. The user's keypad is shuffled in every authentication attempt since the attacker may memorize the spatial arrangement of the p…
Logic locking is used to protect integrated circuits (ICs) from piracy and counterfeiting. An encrypted IC implements the correct function only when the right key is input. Many existing logic-locking methods are subject to the powerful satisfiability (SAT)-based attack. Recently, an Anti-SAT scheme has been developed. By adopting two complementary logic blocks that consist of AND/NAND trees, it makes the number of iterations needed by the SAT attack exponential to the number of input bits. Nevertheless, the Anti-SAT scheme is vulnerable to the later AppSAT and removal attacks. This paper prop…
Proof-of-work (PoW) is an algorithmic tool used to secure networks by imposing a computational cost on participating devices. Unfortunately, traditional PoW schemes require that correct devices perform computational work perpetually, even when the system is not under attack. We address this issue by designing a general PoW protocol that ensures two properties. First, the network stays secure. In particular, the fraction of identities in the system that are controlled by an attacker is always less than 1/2. Second, our protocol's computational cost is commensurate with the cost of an attacker. …
In this paper, a new stream cipher is designed as a clock-controlled one, but with a new mechanism of altering steps based on system theory in such a way that the structures used in it are resistant to conventional attacks. Our proposed algorithm (PALS) uses the main key with the length of 256 bits and a 32-bit message key. The most important criteria considered in designing the PALS are resistance to known attacks, maximum period, high linear complexity, and good statistical properties. As a result, the output keystream is very similar to the perfectly random sequences and resistant to conven…
Memory corruption vulnerabilities are still a severe threat for software systems. To thwart the exploitation of such vulnerabilities, many different kinds of defenses have been proposed in the past. Most prominently, Control-Flow Integrity (CFI) has received a lot of attention recently. Several proposals were published that apply coarse-grained policies with a low performance overhead. However, their security remains questionable as recent attacks have shown. To ease the assessment of a given CFI implementation, we introduce a framework to discover code gadgets for code-reuse attacks that conf…
Since the development of semiconductor technologies, exascale computing and its associated applications have required increasing degrees of efficiency. Semiconductor-transistor-based circuits (STbCs) have struggled in increasing the GHz frequency. Emerging as an alternative to STbC, the superconducting electrons (SCE) technology promises higher-speed clock frequencies at ultra-low power consumption. The rapid single flux quantum (RSFQ) circuits have a theoretical potential for three orders of magnitude reduction in power while operating at clock frequencies higher than 100 GHz. Although the se…
Despite the potential of federated learning, it is known to be vulnerable to backdoor attacks. Many robust federated aggregation methods are proposed to reduce the potential backdoor risk. However, they are mainly validated in the CV field. In this paper, we find that NLP backdoors are hard to defend against than CV, and we provide a theoretical analysis that the malicious update detection error probabilities are determined by the relative backdoor strengths. NLP attacks tend to have small relative backdoor strengths, which may result in the failure of robust federated aggregation methods for …
Towards Deep Learning Models Resistant to Transfer-based Adversarial Attacks via Data-centric Robust Learning
School of Cyber Science and Engineering, Xi’an Jiaotong University（西安交通大学网络空间安全学院）；School of Cyber Science and Technology, Zhejiang University（浙江大学网络空间安全学院）
Adversarial attacks add perturbations to the input features with the intent of changing the classification produced by a machine learning system. Small perturbations can yield adversarial examples which are misclassified despite being virtually indistinguishable from the unperturbed input. Classifiers trained with standard neural network techniques are highly susceptible to adversarial examples, allowing an adversary to create misclassifications of their choice. We introduce a new type of network unit, called MWD (max of weighed distance) units that have a built-in resistant to adversarial att…
In this paper we introduce a unified field multiplier for the EC kP operation in two different types of Galois fields. The most important contributions of this paper are that the multiplier is based on the 4-segment Karatsuba multiplication method and that it is inherent resistant against selected horizontal attacks.
Recent advances in autoencoders and generative models have given rise to effective video forgery methods, used for generating so-called "deepfakes". Mitigation research is mostly focused on post-factum deepfake detection and not on prevention. We complement these efforts by introducing a novel class of adversarial attacks---training-resistant attacks---which can disrupt face-swapping autoencoders whether or not its adversarial images have been included in the training set of said autoencoders. We propose the Oscillating GAN (OGAN) attack, a novel attack optimized to be training-resistant, whic…
Federated Edge Learning (FEL) allows edge nodes to train a global deep learning model collaboratively for edge computing in the Industrial Internet of Things (IIoT), which significantly promotes the development of Industrial 4.0. However, FEL faces two critical challenges: communication overhead and data privacy. FEL suffers from expensive communication overhead when training large-scale multi-node models. Furthermore, due to the vulnerability of FEL to gradient leakage and label-flipping attacks, the training process of the global model is easily compromised by adversaries. To address these c…
Orthogonal blinding based schemes for wireless physical layer security aim to achieve secure communication by injecting noise into channels orthogonal to the main channel and corrupting the eavesdropper's signal reception. These methods, albeit practical, have been proven vulnerable against multi-antenna eavesdroppers who can filter the message from the noise. The vulnerability is rooted in the fact that the main channel state remains static in spite of the noise injection, which allows an eavesdropper to estimate it promptly via known symbols and filter out the noise. Our proposed scheme leve…
Background and Objectives: Substitution-box (s-box) is one of the essential components to create confusion and nonlinear properties in cryptography. To strengthening a cipher against various attacks, including side channel attacks, these boxes need to have numerous security properties. In this paper, a novel method to generate s-boxes is introduced aimed at improving the resistance of s-boxes against side channel attacks. Methods: In the preprocessing phase of this approach, a suitable initial s-box which has some basic security properties is generated by adopting a fast algorithm. Then, in th…
Algorithms that rely on a pseudorandom number generator often lose their performance guarantees when adversaries can predict the behavior of the generator. To protect non-cryptographic applications against such attacks, we propose 'strong' pseudorandom generators characterized by two properties: computationally indistinguishable from random and backtracking-resistant. Some existing cryptographically secure generators also meet these criteria, but they are too slow to be accepted for general-purpose use. We introduce a new open-sourced generator called 'Randen' and show that it is 'strong' in a…
The tremendous growth in the number of Internet of Things (IoT) devices has increased focus on the energy efficiency and security of an IoT device. In this paper, we will present a design level, non-volatile adiabatic architecture for low-energy and Correlation Power Analysis (CPA) resistant IoT devices. IoT devices constructed with CMOS integrated circuits suffer from high dynamic energy and leakage power. To solve this, we look at both adiabatic logic and STT-MTJs (Spin Transfer Torque Magnetic Tunnel Junctions) to reduce both dynamic energy and leakage power. Furthermore, CMOS integrated ci…
Adversarial examples tremendously threaten the availability and integrity of machine learning-based systems. While the feasibility of such attacks has been observed first in the domain of image processing, recent research shows that speech recognition is also susceptible to adversarial attacks. However, reliably bridging the air gap (i.e., making the adversarial examples work when recorded via a microphone) has so far eluded researchers. We find that due to flaws in the generation process, state-of-the-art adversarial example generation methods cause overfitting because of the binning operatio…
Malicious domains are increasingly common and pose a severe cybersecurity threat. Specifically, many types of current cyber attacks use URLs for attack communications (e.g., C\&C, phishing, and spear-phishing). Despite the continuous progress in detecting these attacks, many alarming problems remain open, such as the weak spots of the defense mechanisms. Since machine learning has become one of the most prominent methods of malware detection, A robust feature selection mechanism is proposed that results in malicious domain detection models that are resistant to evasion attacks. This mechanism …
Power side-channel attacks are a very effective cryptanalysis technique that can infer secret keys of security ICs by monitoring the power consumption. Since the emergence of practical attacks in the late 90s, they have been a major threat to many cryptographic-equipped devices including smart cards, encrypted FPGA designs, and mobile phones. Designers and manufacturers of cryptographic devices have in response developed various countermeasures for protection. Attacking methods have also evolved to counteract resistant implementations. This paper reviews foundational power analysis attack tech…
Osaka University（大阪大学）；NTT Social Informatics Laboratories（NTT社会信息学实验室）
Diffusion models have attracted attention in recent years as innovative generative models. In this paper, we investigate whether a diffusion model is resistant to a membership inference attack, which evaluates the privacy leakage of a machine learning model. We primarily discuss the diffusion model from the standpoints of comparison with a generative adversarial network (GAN) as conventional models and hyperparameters unique to the diffusion model, i.e., time steps, sampling steps, and sampling variances. We conduct extensive experiments with DDIM as a diffusion model and DCGAN as a GAN on the…
Spectre attacks enable an attacker to access restricted data in an application's memory. Both the academic community and industry veterans have developed several mitigations to block Spectre attacks, but to date, very few have been formally vetted; most are "best effort" strategies. Formal guarantees are particularly crucial for protecting isolated environments like sandboxing against Spectre attacks. In such environments, a subtle flaw in the mitigation would allow untrusted code to break out of the sandbox and access trusted memory regions. In our work, we develop principled foundations to b…
Smartphones store a significant amount of personal and private information, and are playing an increasingly important role in people's lives. It is important for authentication techniques to be more resistant against two known attacks called shoulder surfing and smudge attacks. In this work, we propose a new technique called 3D Pattern. Our 3D Pattern technique takes advantage of a new input paradigm called pre-touch, which could soon allow smartphones to sense a user's finger position at some distance from the screen. We implement the technique and evaluate it in a pilot study (n=6) by compar…
P2P systems are highly susceptible to Sybil attacks, in which an attacker creates a large number of identities and uses them to control a substantial fraction of the system. Persea is the most recent approach towards designing a social network based Sybil-resistant DHT. Unlike prior Sybil-resistant P2P systems based on social networks, Persea does not rely on two key assumptions: (i) that the social network is fast mixing, and (ii) that there is a small ratio of attack edges to honest peers. Both assumptions have been shown to be unreliable in real social networks. The hierarchical distributio…
Data poisoning attacks aim to manipulate the model produced by a learning algorithm by adversarially modifying the training set. We consider differential privacy as a defensive measure against this type of attack. We show that such learners are resistant to data poisoning attacks when the adversary is only able to poison a small number of items. However, this protection degrades as the adversary poisons more data. To illustrate, we design attack algorithms targeting objective and output perturbation learners, two standard approaches to differentially-private machine learning. Experiments show …
Line Speed Publish/Subscribe Inter-networking (LIPSIN) is one of the proposed forwarding mechanisms in Information Centric Networking (ICN). It is a stateless source-routing approach based on Bloom filters. However, it has been shown that LIPSIN is vulnerable to brute-force attacks which may lead to distributed denial-of-service (DDoS) attacks and unsolicited messages. In this work, we propose a new forwarding approach that maintains the advantages of Bloom filter based forwarding while allowing forwarding nodes to statelessly verify if packets have been previously authorized, thus preventing …
FIT-Print: Towards False-claim-resistant Model Ownership Verification via Targeted Fingerprint
State Key Laboratory of Blockchain and Data Security, Zhejiang University（区块链与数据安全国家重点实验室，浙江大学）；Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security, Hangzhou（杭州高新技术区（滨江）区块链与数据安全研究院，杭州）；College of Computing and Data Science, Nanyang Technological University（南洋理工大学计算机与数据科学学院）；Department of Computer Science, City University of Hong Kong（香港城市大学计算机科学系）
