Biblio

It has been a hot research topic to detect and mitigate Distributed Denial-of-Service (DDoS) attacks due to the significant increase of serious threat of such attacks. The rapid growth of Internet of Things (IoT) has intensified this trend, e.g. the Mirai botnet and variants. To address this issue, a light-weight DDoS mitigation mechanism was presented. In the proposed scheme, flooding attacks are detected by stochastic queue allocation which can be executed with widespread and inexpensive commercial products at a network edge. However, the detection process is delayed when the number of incoming flows is large because of the randomness of queue allocation. Thus, in this paper we propose an efficient queue allocation algorithm for rapid DDoS mitigation using limited resources. The idea behind the proposed scheme is to avoid duplicate allocation by decreasing the randomness of the existing scheme. The performance of the proposed scheme was confirmed via theoretical analysis and computer simulation. As a result, it was confirmed that malicious flows are efficiently detected and discarded with the proposed algorithm.

With the emergence of quantum computers, traditional digital signature schemes based on problems such as large integer solutions and discrete logarithms will no longer be secure, and it is urgent to find effective digital signature schemes that can resist quantum attacks. Lattice cryptography has the advantages of computational simplicity and high security. In this paper, we propose an identity-based digital signature scheme based on the rejection sampling algorithm. Unlike most schemes that use a common Gaussian distribution, this paper uses a bimodal Gaussian distribution, which improves efficiency. The identity-based signature scheme is more convenient for practical application than the traditional certificate-based signature scheme.

Quantum computers have the potential to outshine classical alternatives in solving specific problems, under the assumption of mature enough hardware. A specific subset of these problems relate to military applications. In this paper we consider the state-of-the-art of quantum technologies and different applications of this technology. Additionally, four use-cases of quantum computing specific for military applications are presented. These use-cases are directly in line with the 2021 AI strategic agenda of the Netherlands Ministry of Defense.

Purpose: Smart apps and wearables devices are an increasingly used way in healthcare to monitor a range of functions associated with certain health conditions. Even if in the present there are some devices and applications developed, there is no sufficient evidence of the use of such wearables devices in the detection of some disorders such as depression. Thus, through this paper, we want to address this need and present a quantitative research to determine the user requirements for developing a smart device that can detect depression. Material and Methods: To determine the user requirements for developing a system to detect depression we developed a questionnaire which was applied to 205 participants. Results and conclusions: Such a system addressed to detect depression is of interest among the respondents. The most essential parameters to be monitored refer to sleep quality, level of stress, circadian rhythm, and heart rate. Also, the developed system should prioritize reliability, privacy, security, and ease of use.

Quantum entanglement gives rise to a range of non-classical effects, which are extensively exploited in quantum computing and quantum communication. Therefore, detection and quantification of entanglement as well as preparation of highly entangled quantum states remain the fundamental objectives in these fields. Much attention has been devoted to the studies of graph states, which play a role of a central resource in quantum error correction, quantum cryptography and practical quantum metrology in the presence of noise.We examine multi-qubit graph states generated by the action of controlled phase shift operators on a separable quantum state of a system, in which all the qubits are in arbitrary identical states. Analytical expression is obtained for the geometric measure of entanglement of a qubit with other qubits in graph states represented by arbitrary graphs. We conclude that this quantity depends on the degree of the vertex corresponding to the qubit, the absolute values of the parameter of the phase shift gate and the parameter of the initial state the gate is acting on. Moreover, the geometric measure of entanglement of certain types of graph states is quantified on the IBM’s quantum computer ibmq\_athens based on the measurements of the mean spin. Namely, we consider states associated with the native connectivity of ibmq\_athens, the claw and the complete graphs. Appropriate protocols are proposed to prepare these states on the quantum computer. The results of quantum computations verify our theoretical findings [1].

In quantum cryptography research area, quantum digital signature is an important research field. To provide a better privacy for users in constructing quantum digital signature, the stronger anonymity of quantum digital signatures is required. Quantum ring signature scheme focuses on anonymity in certain scenarios. Using quantum ring signature scheme, the quantum message signer hides his identity into a group. At the same time, there is no need for any centralized organization when the user uses the quantum ring signature scheme. The group used to hide the signer identity can be immediately selected by the signer himself, and no collaboration between users.Since the quantum finite automaton signature scheme is very efficient quantum digital signature scheme, based on it, we propose a new quantum ring signature scheme. We also showed that the new scheme we proposed is of feasibility, correctness, anonymity, and unforgeability. And furthermore, the new scheme can be implemented only by logical operations, so it is easy to implement.

A cyber-physical system (CPS) is a term that implements mainly three parts, Physical elements, communication networks, and control systems. Currently, CPS includes the Internet of Things (IoT), Internet of Vehicles (IoV), and many other systems. These systems face many security challenges and different types of attacks, such as Jamming, DDoS.CPS attacks tend to be much smarter and more dynamic; thus, it needs defending strategies that can handle this level of intelligence and dynamicity. Last few years, many researchers use machine learning as a base solution to many CPS security issues. This paper provides a survey of the recent works that utilized the Q-Learning algorithm in terms of security enabling and privacy-preserving. Different adoption of Q-Learning for security and defending strategies are studied. The state-of-the-art of Q-learning and CPS systems are classified and analyzed according to their attacks, domain, supported techniques, and details of the Q-Learning algorithm. Finally, this work highlight The future research trends toward efficient utilization of Q-learning and deep Q-learning on CPS security.

DNN models have suffered from adversarial example attacks, which lead to inconsistent prediction results. As opposed to the gradient-based attack, which assumes white-box access to the model by the attacker, we focus on more realistic input perturbations from the real-world and their actual impact on the model robustness without any presence of the attackers. In this work, we promote a standardized framework to quantify the robustness against real-world threats. It is composed of a set of safety properties associated with common violations, a group of metrics to measure the minimal perturbation that causes the offense, and various criteria that reflect different aspects of the model robustness. By revealing comparison results through this framework among 13 pre-trained ImageNet classifiers, three state-of-the-art object detectors, and three cloud-based content moderators, we deliver the status quo of the real-world model robustness. Beyond that, we provide robustness benchmarking datasets for the community.

In modern high-performance computing (HPC) systems, network congestion is an important factor that contributes to performance degradation. However, how network congestion impacts application performance is not fully understood. As Aries network, a recent HPC network architecture featuring a dragonfly topology, is equipped with network counters measuring packet transmission statistics on each router, these network metrics can potentially be utilized to understand network performance. In this work, by experiments on a large HPC system, we quantify the impact of network congestion on various applications' performance in terms of execution time, and we correlate application performance with network metrics. Our results demonstrate diverse impacts of network congestion: while applications with intensive MPI operations (such as HACC and MILC) suffer from more than 40% extension in their execution times under network congestion, applications with less intensive MPI operations (such as Graph500 and HPCG) are mostly not affected. We also demonstrate that a stall-to-flit ratio metric derived from Aries network counters is positively correlated with performance degradation and, thus, this metric can serve as an indicator of network congestion in HPC systems.

Software development and deployment are generally fast-pacing practices, yet to date there is still a significant amount of legacy software running in various critical industries with years or even decades of lifespans. As the source code of some legacy software became unavailable, it is difficult for maintainers to actively patch the vulnerabilities, leaving the outdated binaries appealing targets of advanced security attacks. One of the most powerful attacks today is code reuse, a technique that can circumvent most existing system-level security facilities. While there have been various countermeasures against code reuse, applying them to sourceless software appears to be exceptionally challenging. Fine-grained code randomization is considered to be an effective strategy to impede modern code-reuse attacks. To apply it to legacy software, a technique called binary rewriting is employed to directly reconstruct binaries without symbol or relocation information. However, we found that current rewriting-based randomization techniques, regardless of their designs and implementations, share a common security defect such that the randomized binaries may remain vulnerable in certain cases. Indeed, our finding does not invalidate fine-grained code randomization as a meaningful defense against code reuse attacks, for it significantly raises the bar for exploits to be successful. Nevertheless, it is critical for the maintainers of legacy software systems to be aware of this problem and obtain a quantitative assessment of the risks in adopting a potentially incomprehensive defense. In this paper, we conducted a systematic investigation into the effectiveness of randomization techniques designed for hardening outdated binaries. We studied various state-of-the-art, fine-grained randomization tools, confirming that all of them can leave a certain part of the retrofitted binary code still reusable. To quantify the risks, we proposed a set of concrete criteria to classify gadgets immune to rewriting-based randomization and investigated their availability and capability.

The long-distance transmission of quantum secret key is a challenge for quantum communication. As far as the current relay technology is concerned, the trusted relay technology is a more practical scheme. However, the trusted relay technology requires every relay node to be trusted, but in practical applications, the security of some relay nodes cannot be guaranteed. How to overcome the security problem of trusted relay technology and realize the security key distribution of remote quantum network has become a new problem. Therefore, in this paper, a method of quantum key distribution in ring network is proposed under the condition of the coexistence of trusted and untrusted repeaters, and proposes a partially-trusted based routing algorithm (PT-RA). This scheme effectively solves the security problem of key distribution in ring backbone network. And simulation results show that PT-RA can significantly improve key distribution success rate compared with the original trusted relay technology.

Domain name system (DNS) resolves the IP addresses of domain names and is critical for IP networking. Recent denial-of-service (DoS) attacks on Internet targeted the DNS system (e.g., Dyn), which has the cascading effect of denying the availability of the services and applications relying on the targeted DNS. In view of these attacks, we investigate the DoS on DNS system and introduce the query-crafting threats where the attacker controls the DNS query payload (the domain name) to maximize the threat impact per query (increasing the communications between the DNS servers and the threat time duration), which is orthogonal to other DoS approaches to increase the attack impact such as flooding and DNS amplification. We model the DNS system using a state diagram and comprehensively analyze the threat space, identifying the threat vectors which include not only the random/invalid domains but also those using the domain name structure to combine valid strings and random strings. Query-crafting DoS threats generate new domain-name payloads for each query and force increased complexity in the DNS query resolution. We test the query-crafting DoS threats by taking empirical measurements on the Internet and show that they amplify the DoS impact on the DNS system (recursive resolver) by involving more communications and taking greater time duration. To defend against such DoS or DDoS threats, we identify the relevant detection features specific to query-crafting threats and evaluate the defense using our prototype in CloudLab.

Advanced Persistent Threats (APTs) are stealthy, sophisticated, long-term, multi-stage attacks that threaten the security of sensitive information. Dynamic Information Flow Tracking (DIFT) has been proposed as a promising mechanism to detect and prevent various cyber attacks in computer systems. DIFT tracks suspicious information flows in the system and generates security analysis when anomalous behavior is detected. The number of information flows in a system is typically large and the amount of resources (such as memory, processing power and storage) required for analyzing different flows at different system locations varies. Hence, efficient use of resources is essential to maintain an acceptable level of system performance when using DIFT. On the other hand, the quickest detection of APTs is crucial as APTs are persistent and the damage caused to the system is more when the attacker spends more time in the system. We address the problem of detecting APTs and model the trade-off between resource efficiency and quickest detection of APTs. We propose a game model that captures the interaction of APT and a DIFT-based defender as a two-player, multi-stage, zero-sum, Stackelberg semi-Markov game. Our game considers the performance parameters such as false-negatives generated by DIFT and the time required for executing various operations in the system. We propose a two-time scale Q-learning algorithm that converges to a Stackelberg equilibrium under infinite horizon, limiting average payoff criteria. We validate our model and algorithm on a real-word attack dataset obtained using Refinable Attack INvestigation (RAIN) framework.

When using digital signatures, we need to deal with the problem of fairness of information exchange. To solve this problem, Chen, etc. introduced a new conception which is named concurrent signatures in Eurocrypt'04. Using concurrent signatures scheme, two entities in the scheme can generate two ambiguous signatures until one of the entities releases additional information which is called keystone. After the keystone is released, the two ambiguous signatures will be bound to their real signers at the same time. In order to provide a method to solve the fairness problem of quantum digital signatures, we propose a new quantum concurrent signature scheme. The scheme we proposed does not use a trusted third party in a quantum computing environment, and has such advantages as no need to conduct complex quantum operations and easy to implement by a quantum circuit. Quantum concurrent signature improves the theory of quantum cryptography, and it also provides broad prospects for the specific applications of quantum cryptography.

The classical key distribution systems used for data transmission in networked microgrids (NMGs) rely on mathematical assumptions, which however can be broken by attacks from quantum computers. This paper addresses this quantum-era challenge by using quantum key distribution (QKD). Specifically, the novelty of this paper includes 1) a QKD-enabled communication architecture it devises for NMGs, 2) a real-time QKD- enabled NMGs testbed it builds in an RTDS environment, and 3) a novel two-level key pool sharing (TLKPS) strategy it designs to improve the system resilience against cyberattacks. Test results validate the effectiveness of the presented strategy, and provide insightful resources for building quantum-secure NMGs.

Physical Unclonable Function is an innovative hardware security primitives that exploit the physical characteristics of a physical object to generate a unique identifier, which play the role of the object's fingerprint. Silicon PUF, a popular type of PUFs, exploits the variation in the manufacturing process of integrated circuits (ICs). It needs an input called challenge to generate the response as an output. In addition, of classical attacks, PUFs are vulnerable to physical and modeling attacks. The performance of the PUFs is measured by several metrics like reliability, uniqueness and uniformity. So as an evidence, the main goal is to provide a complete tool that checks the strength and quantifies the performance of a given physical unconscionable function. This paper provides a tool and develops a set of metrics that can achieve safely the proposed goal.

Almost everyone recognizes the emergence of a new challenge in the cyber domain, namely increased threats to the security of the Internet and its various uses. Seldom does a day go by without dire reports and hair raising narratives about unauthorized intrusions, access to content, or damage to systems, or operations. And, of course, a close correlate is the loss of value. An entire industry is around threats to cyber security, prompting technological innovations and operational strategies that promise to prevent damage and destruction. This paper is a collection chapters entitled 1) "Cybersecurity – Problems, Premises, Perspectives," 2) "An Abbreviated Technical Perspective on Cybersecurity," 3) "The Conceptual Underpinning of Cyber Security Studies" 4) "Cyberspace as the Domain of Content," 5) "The Conceptual Underpinning of Cyber Security Studies," 6) "China’s Perspective on Cyber Security," 7) "Pursuing Deterrence Internationally in Cyberspace," 8) "Is Deterrence Possible in Cyber Warfare?" and 9) "A Theoretical Framework for Analyzing Interactions between Contemporary Transnational Activism and Digital Communication."

Wireless sensor networks (WSNs) have been widely used in various applications for continuous event monitoring and detection. Dual to lack of a protected physical boundary, WSNs are vulnerable to trace-back attacks. The existing secure routing protocols are designed to protect source location privacy by increasing uncertainty of routing direction against statistic analysis on traffic flow. Nevertheless, the security has not been quantitatively measured and shown the direction of secure routing design. In this paper, we propose a theoretical security measurement scheme to define and analyze the quantitative amount of the information leakage from each eavesdropped message. Through the theoretical analysis, we identify vulnerabilities of existing routing algorithms and quantitatively compute the direction information leakage based on various routing strategy. The theoretical analysis results also indicate the direction for maximization of source location privacy.

This paper examines the influence of quantization on the compressive sensing theory applied to the nonuniformly sampled nonsparse signals with reduced set of randomly positioned measurements. The error of the reconstruction will be generalized to exact expected squared error expression. The aim is to connect the generalized random sampling strategy with the quantization effect, finding the resulting error of the reconstruction. Small sampling deviations correspond to the imprecisions of the sampling strategy, while completely random sampling schemes causes large sampling deviations. Numerical examples provide an agreement between the statistical results and theoretical values.

Homomorphic encryption enables computation on encrypted data while maintaining secrecy. This leads to an important open question whether quantum computation can be delegated and verified in a non-interactive manner or not. In this paper, we affirmatively answer this question by constructing the quantum homomorphic encryption scheme with quantum obfuscation. It takes advantage of the interchangeability of the unitary operator, and exchanges the evaluation operator and the encryption operator by means of equivalent multiplication to complete homomorphic encryption. The correctness of the proposed scheme is proved theoretically. The evaluator does not know the decryption key and does not require a regular interaction with a user. Because of key transmission after quantum obfuscation, the encrypting party and the decrypting party can be different users. The output state has the property of complete mixture, which guarantees the scheme security. Moreover, the security level of the quantum homomorphic encryption scheme depends on quantum obfuscation and encryption operators.

In recent years, persistent cyber adversaries have developed increasingly sophisticated techniques to evade detection. Once adversaries have established a foothold within the target network, using seemingly-limited passive reconnaissance techniques, they can develop significant network reconnaissance capabilities. Cyber deception has been recognized as a critical capability to defend against such adversaries, but, without an accurate model of the adversary's reconnaissance behavior, current approaches are ineffective against advanced adversaries. To address this gap, we propose a novel model to capture how advanced, stealthy adversaries acquire knowledge about the target network and establish and expand their foothold within the system. This model quantifies the cost and reward, from the adversary's perspective, of compromising and maintaining control over target nodes. We evaluate our model through simulations in the CyberVAN testbed, and indicate how it can guide the development and deployment of future defensive capabilities, including high-interaction honeypots, so as to influence the behavior of adversaries and steer them away from critical resources.

A quantum high secure direct communication with authentication protocol is proposed by using single photons. The high security of the protocol is achieved on levels. The first level involves the verification of the quantum channel security by using fake photons. The authentication process is also ensured by the fake photons. The second level of security is given by the use of multiple polarization bases. The secret message is encoded in groups of photons; each single character of the message is associated with m (m≥7) photons. Thus, at least 27 (128) characters will be encoded. In order to defeat the quantum teleportation attack, the string of bits associated to the secret message is encrypted with a secret string of bits by using XOR operator. Encryption of the sender's identity string and the receiver's identity string by the XOR operator with a random string of fake photons defends quantum man-in-the-middle attack efficiently. Quantum memory is required to implement our protocol. Storage of quantum information is a key element in quantum information processing and provides a more flexible, effective and efficient communication. Our protocol is feasible with current technologies.

Quantized deep neural networks (QDNNs) are necessary for low-power, high throughput, and embedded applications. Previous studies mostly focused on developing optimization methods for the quantization of given models. However, quantization sensitivity depends on the model architecture. Also, the characteristics of weight and activation quantization are quite different. This study proposes a holistic approach for the optimization of QDNNs, which contains QDNN training methods as well as quantization-friendly architecture design. Synthesized data is used to visualize the effects of weight and activation quantization. The results indicate that deeper models are more prone to activation quantization, while wider models improve the resiliency to both weight and activation quantization.

A QPSK-assisted MIMO equalization is investigated to compensate bandwidth limitation for 800-Gb/s/λ DP-256QAM systems with only 25G-class optics. Compared with conventional MIMO equalization, the proposed equalization scheme exhibits 1.8-dB OSNR improvement at 15% FEC limit.

Payment channel networks have been introduced to mitigate the scalability issues inherent to permissionless decentralized cryptocurrencies such as Bitcoin. Launched in 2018, the Lightning Network (LN) has been gaining popularity and consists today of more than 5000 nodes and 35000 payment channels that jointly hold 965 bitcoins (9.2M USD as of June 2020). This adoption has motivated research from both academia and industryPayment channels suffer from security vulnerabilities, such as the wormhole attack [39], anonymity issues [38], and scalability limitations related to the upper bound on the number of concurrent payments per channel [28], which have been pointed out by the scientific community but never quantitatively analyzedIn this work, we first analyze the proneness of the LN to the wormhole attack and attacks against anonymity. We observe that an adversary needs to control only 2% of nodes to learn sensitive payment information (e.g., sender, receiver, and amount) or to carry out the wormhole attack. Second, we study the management of concurrent payments in the LN and quantify its negative effect on scalability. We observe that for micropayments, the forwarding capability of up to 50% of channels is restricted to a value smaller than the channel capacity. This phenomenon hinders scalability and opens the door for denial-of-service attacks: we estimate that a network-wide DoS attack costs within 1.6M USD, while isolating the biggest community costs only 238k USDOur findings should prompt the LN community to consider the issues studied in this work when educating users about path selection algorithms, as well as to adopt multi-hop payment protocols that provide stronger security, privacy and scalability guarantees.