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Sang-Yoon Chang

Publications and source records attributed to Sang-Yoon Chang.

12 recordsLinked to original sources

DyPBP: Dynamic Peer Beneficialness Prediction for Cryptocurrency P2P Networking

Distributed peer-to-peer (P2P) networking delivers the new blocks and transactions and is critical for the cryptocurrency blockchain system operations. Having poor P2P connectivity reduces the financial rewards from the mining consensus protocol. Previous research defines beneficalness of each Bitcoin peer connection and estimates the beneficialness based on the observations of the blocks and transactions delivery, which are after they are delivered. However, due to the infrequent block arrivals and the sporadic and unstable peer connections, the peers do not stay connected long enough to have the beneficialness score to converge to its expected beneficialness. We design and build Dynamic Peer Beneficialness Prediction (DyPBP) which predicts a peer's beneficialness by using networking behavior observations beyond just the block and transaction arrivals. DyPBP advances the previous research by estimating the beneficialness of a peer connection before it delivers new blocks and transactions. To achieve such goal, DyPBP introduces a new feature for remembrance to address the dynamic connectivity issue, as Bitcoin's peers using distributed networking often disconnect and re-connect. We implement DyPBP on an active Bitcoin node connected to the Mainnet and use machine learning for the beneficialness prediction. Our experimental results validate and evaluate the effectiveness of DyPBP; for example, the error performance improves by 2 to 13 orders of magnitude depending on the machine-learning model selection. DyPBP's use of the remembrance feature also informs our model selection. DyPBP enables the P2P connection's beneficialness estimation from the connection start before a new block arrives.

cs.NI

$\mathcal{PT}$-symmetric mapping of three states and its implementation on a cloud quantum processor

$\mathcal{PT}$-symmetric systems have garnered significant attention due to their unconventional properties. Despite the growing interest, there remains an ongoing debate about whether these systems outperform their Hermitian counterparts in practical applications, and if so, by what metrics this performance should be measured. We developed $\mathcal{PT}$-symmetric approach for mapping $N = 3$ pure qubit states to address this, implemented it using the dilation method, and demonstrated it on a superconducting quantum processor from the IBM Quantum Experience. For the first time, we derived exact expressions for the population of the post-selected $\mathcal{PT}$-symmetric subspace for both $N = 2$ and $N = 3$ states. When applied to the discrimination of $N = 2$ pure states, our algorithm provides an equivalent result to the conventional unambiguous quantum state discrimination. For $N = 3$ states, our approach introduces novel capabilities not available in traditional Hermitian systems, enabling the transformation of an arbitrary set of three pure quantum states into another, at the cost of introducing an inconclusive outcome. Our algorithm has the same error rate for the attack on the three-state QKD protocol as the conventional minimum error, maximum confidence, and maximum mutual information strategies. For post-selected quantum metrology, our results provide precise conditions where $\mathcal{PT}$-symmetric quantum sensors outperform their Hermitian counterparts in terms of information-cost rate. Combined with punctuated unstructured quantum database search, our method significantly reduces the qubit readout requirements at the cost of adding an ancilla, while maintaining the same average number of oracle calls as the original punctuated Grover's algorithm. Our work opens new pathways for applying $\mathcal{PT}$ symmetry in quantum communications, computing, and cryptography.

quant-ph

Base Station Certificate and Multi-Factor Authentication for Cellular Radio Control Communication Security

Current cellular networking remains vulnerable to malicious fake base stations due to the lack of base station authentication mechanism or even a key to enable authentication. We design and build a base station certificate (certifying the base station's public key and location) and a multi-factor authentication (making use of the certificate and the information transmitted in the online radio control communications) to secure the authenticity and message integrity of the base station control communications. We advance beyond the state-of-the-art research by introducing greater authentication factors (and analyzing their individual security properties and benefits), and by using blockchain to deliver the base station digital certificate offline (enabling greater key length or security strength and computational or networking efficiency). We design the certificate construction, delivery, and the multi-factor authentication use on the user equipment. The user verification involves multiple factors verified through the ledger database, the location sensing (GPS in our implementation), and the cryptographic signature verification of the cellular control communication (SIB1 broadcasting). We analyze our scheme's security, performance, and the fit to the existing standardized networking protocols. Our work involves the implementation of building on X.509 certificate (adapted), smart contract-based blockchain, 5G-standardized RRC control communications, and software-defined radios. Our analyses show that our scheme effectively defends against more security threats and can enable stronger security, i.e., ECDSA with greater key lengths. Furthermore, our scheme enables computing and energy to be more than three times efficient than the previous research on the mobile user equipment.

cs.CR

Blockchain-based Trust Management in Security Credential Management System for Vehicular Network

Cellular networking is advancing as a wireless technology to support diverse applications in vehicular communication, enabling vehicles to interact with various applications to enhance the driving experience, even when managed by different authorities. Security Credential Management System (SCMS) is the Public Key Infrastructure (PKI) for vehicular networking and the state-of-the-art distributed PKI to protect the privacy-preserving vehicular networking against an honest-but-curious authority using multiple authorities and to decentralize the trust management. We build a Blockchain-Based Trust Management (BBTM) to provide even greater decentralization and security. Specifically, BBTM uses the blockchain to 1) replace the existing Policy Generator (PG), 2) manage the policy of each authority in SCMS, 3) aggregate the Global Certificate Chain File (GCCF), and 4) provide greater accountability and transparency on the aforementioned functionalities. We implement BBTM on Hyperledger Fabric using a smart contract for experimentation and analyses. Our experiments show that BBTM is lightweight in processing, efficient management in the certificate chain and ledger size, supports a bandwidth of multiple transactions per second, and provides validated end-entities.

cs.CR

5G-NIDD: A Comprehensive Network Intrusion Detection Dataset Generated over 5G Wireless Network

With a plethora of new connections, features, and services introduced, the 5th generation (5G) wireless technology reflects the development of mobile communication networks and is here to stay for the next decade. The multitude of services and technologies that 5G incorporates have made modern communication networks very complex and sophisticated in nature. This complexity along with the incorporation of Machine Learning (ML) and Artificial Intelligence (AI) provides the opportunity for the attackers to launch intelligent attacks against the network and network devices. These attacks often traverse undetected due to the lack of intelligent security mechanisms to counter these threats. Therefore, the implementation of real-time, proactive, and self-adaptive security mechanisms throughout the network would be an integral part of 5G as well as future communication systems. Therefore, large amounts of data collected from real networks will play an important role in the training of AI/ML models to identify and detect malicious content in network traffic. This work presents 5G-NIDD, a fully labeled dataset built on a functional 5G test network that can be used by those who develop and test AI/ML solutions. The work further analyses the collected data using common ML models and shows the achieved accuracy levels.

cs.CR

Capture the Flag for Team Construction in Cybersecurity

Team collaboration among individuals with diverse sets of expertise and skills is essential for solving complex problems. As part of an interdisciplinary effort, we studied the effects of Capture the Flag (CTF) game, a popular and engaging education/training tool in cybersecurity and engineering, in enhancing team construction and collaboration. We developed a framework to incorporate CTF as part of a computer-human process for expertise recognition and role assignment and evaluated and tested its effectiveness through a study with cybersecurity students enrolled in a Virtual Teams course. In our computer-human process framework, the post-CTF algorithm using the CTF outcomes assembles the team (assigning individuals to teams) and provides the initial role assignments, which then gets updated by human-based team discussions. This paper shares our insights, design choices/rationales, and analyses of our CTF-incorporated computer-human process framework. The students' evaluations revealed that the computer-human process framework was helpful in learning about their team members' backgrounds and expertise and assigning roles accordingly made a positive impact on the learning outcomes for the team collaboration skills in the course. This experience report showcases the utility of CTF as a tool for expertise recognition and role assignments in teams and highlights the complementary roles of CTF-based and discussion-based processes for an effective team collaboration among engineering students.

cs.CY

$\mathcal{PT}$-Symmetric Quantum Discrimination of Three States

If the system is known to be in one of two non-orthogonal quantum states, $|ψ_1\rangle$ or $|ψ_2\rangle$, it is not possible to discriminate them by a single measurement due to the unitarity constraint. In a regular Hermitian quantum mechanics, the successful discrimination is possible to perform with the probability $p < 1$, while in $\mathcal{PT}$-symmetric quantum mechanics a \textit{simulated single-measurement} quantum state discrimination with the success rate $p$ can be done. We extend the $\mathcal{PT}$-symmetric quantum state discrimination approach for the case of three pure quantum states, $|ψ_1\rangle$, $|ψ_2\rangle$ and $|ψ_3\rangle$ without any additional restrictions on the geometry and symmetry possession of these states. We discuss the relation of our approach with the recent implementation of $\mathcal{PT}$ symmetry on the IBM quantum processor.

quant-ph

$\mathcal{PT}$-Symmetric Quantum State Discrimination for Attack on BB84 Quantum Key Distribution

Quantum Key Distribution or QKD provides symmetric key distribution using the quantum mechanics/channels with new security properties. The security of QKD relies on the difficulty of the quantum state discrimination problem. We discover that the recent developments in $\mathcal{PT}$ symmetry can be used to expedite the quantum state discrimination problem and therefore to attack the BB84 QKD scheme. We analyze the security of the BB84 scheme and show that the attack significantly increases the eavesdropping success rate over the previous Hermitian quantum state discrimination approach. We design and analyze the approaches to attack BB84 QKD protocol exploiting an extra degree of freedom provided by the $\mathcal{PT}$-symmetric quantum mechanics.

quant-ph

Share Withholding Attack in Blockchain Mining: Technical Report

Cryptocurrency achieves distributed consensus using proof of work (PoW). Prior research in blockchain security identified financially incentivized attacks based on withholding blocks which have the attacker compromise a victim pool and pose as a PoW contributor by submitting the shares (earning credit for mining) but withholding the blocks (no actual contributions to the pool). We advance such threats to generate greater reward advantage to the attackers while undermining the other miners and introduce the share withholding attack (SWH). SWH withholds shares to increase the attacker's reward payout within the pool, in contrast to the prior threats withholding blocks, and rather builds on the block-withholding threats in order to exploit the information about the impending block submission timing, challenging the popularly established assumption that the block submission time is completely random and unknown to miners. We analyze SWH's incentive compatibility and the vulnerability scope by identifying the critical systems and environmental parameters which determine the attack's impact. Our results show that SWH in conjunction with block withholding yield unfair reward advantage at the expense of the protocol-complying victim miners and that a rational miner will selfishly launch SWH to maximize its reward profit. We inform the blockchain and cryptocurrency research of the novel SWH threat and include the potential countermeasure directions to facilitate such research and development.

cs.CR

Discriminating an Arbitrary Number of Pure Quantum States by the Combined $\mathcal{CPT}$ and Hermitian Measurements

If the system is known to be in one of two non-orthogonal quantum states, $|ψ_1\rangle$ or $|ψ_2\rangle$, $\mathcal{PT}$-symmetric quantum mechanics can discriminate them, \textit{in principle}, by a single measurement. We extend this approach by combining $\mathcal{PT}$-symmetric and Hermitian measurements and show that it's possible to distinguish an arbitrary number of pure quantum states by an appropriate choice of the parameters of $\mathcal{PT}$-symmetric Hamiltonian.

quant-ph

Signal Jamming Attacks Against Communication-Based Train Control: Attack Impact and Countermeasure

We study the impact of signal jamming attacks against the communication based train control (CBTC) systems and develop the countermeasures to limit the attacks' impact. CBTC supports the train operation automation and moving-block signaling, which improves the transport efficiency. We consider an attacker jamming the wireless communication between the trains or the train to wayside access point, which can disable CBTC and the corresponding benefits. In contrast to prior work studying jamming only at the physical or link layer, we study the real impact of such attacks on end users, namely train journey time and passenger congestion. Our analysis employs a detailed model of leaky medium-based communication system (leaky waveguide or leaky feeder/coaxial cable) popularly used in CBTC systems. To counteract the jamming attacks, we develop a mitigation approach based on frequency hopping spread spectrum taking into account domain-specific structure of the leaky-medium CBTC systems. Specifically, compared with existing implementations of FHSS, we apply FHSS not only between the transmitter-receiver pair but also at the track-side repeaters. To demonstrate the feasibility of implementing this technology in CBTC systems, we develop a FHSS repeater prototype using software-defined radios on both leaky-medium and open-air (free-wave) channels. We perform extensive simulations driven by realistic running profiles of trains and real-world passenger data to provide insights into the jamming attack's impact and the effectiveness of the proposed countermeasure.

cs.CR

Insider-Attacks on Physical-Layer Group Secret-Key Generation in Wireless Networks

Physical-layer group secret-key (GSK) generation is an effective way of generating secret keys in wireless networks, wherein the nodes exploit inherent randomness in the wireless channels to generate group keys, which are subsequently applied to secure messages while broadcasting, relaying, and other network-level communications. While existing GSK protocols focus on securing the common source of randomness from external eavesdroppers, they assume that the legitimate nodes of the group are trusted. In this paper, we address insider attacks from the legitimate participants of the wireless network during the key generation process. Instead of addressing conspicuous attacks such as switching-off communication, injecting noise, or denying consensus on group keys, we introduce stealth attacks that can go undetected against state-of-the-art GSK schemes. We propose two forms of attacks, namely: (i) different-key attacks, wherein an insider attempts to generate different keys at different nodes, especially across nodes that are out of range so that they fail to recover group messages despite possessing the group key, and (ii) low-rate key attacks, wherein an insider alters the common source of randomness so as to reduce the key-rate. We also discuss various detection techniques, which are based on detecting anomalies and inconsistencies on the channel measurements at the legitimate nodes. Through simulations we show that GSK generation schemes are vulnerable to insider-threats, especially on topologies that cannot support additional secure links between neighbouring nodes to verify the attacks.

cs.IT