arXiv subjects

Majid Khabbazian

Publications and source records attributed to Majid Khabbazian.

16 recordsLinked to original sources

arXiv2026

2G2T: Constant-Size, Statistically Sound MSM Outsourcing

Multi-scalar multiplication (MSM), MSM(vec{P},vec{x}) = sum_{i=1}^n x_i P_i, is a dominant computational kernel in discrete-logarithm-based cryptography and often becomes a bottleneck for verifiers and other resource-constrained clients. We present 2G2T, a simple protocol for verifiably outsourcing MSM to an untrusted server. 2G2T is efficient for both parties: the server performs only two MSM computations and returns only two group elements to the client, namely the claimed result A = MSM(vec{P},vec{x}) and an auxiliary group element B. Client-side verification consists of a single length-n field inner product and only three group operations (two scalar multiplications and one group addition). In our Ristretto255 implementation, verification is up to about 300x faster than computing the MSM locally using a highly optimized MSM routine (for n up to 2^18). Moreover, 2G2T enables latency-hiding verification: nearly all verifier work can be performed while waiting for the server's response, so once (A,B) arrives the verifier completes the check with only one scalar multiplication and one group addition (both independent of n). Finally, despite its simplicity and efficiency, we prove that 2G2T achieves statistical soundness: for any (even unbounded) adversarial server, the probability of accepting an incorrect result is at most 1/q per query, and at most e/q over e adaptive executions, in a prime-order group of size q.

cs.CR↗

arXiv2025

Plaintext-Scale Fair Data Exchange

The Fair Data Exchange (FDE) protocol (CCS'24) achieves atomic, pay-per-file exchange with a constant on-chain footprint, but existing implementations do not scale: proof verification can take hours even for files of only tens of megabytes. In this work, we present two FDE implementations: VECKplus and VECKstar. VECKplus reduces client-side verification to O(lambda) -- independent of file size -- where lambda is the security parameter. VECKplus brings verification time to approximately 1 s on a commodity desktop for any file size. VECKplus also significantly reduces proof generation time by limiting expensive range proofs to a Theta(lambda)-sized subset of the file. This improvement is especially beneficial for large files, even though proof generation and encryption are already precomputable and highly parallelizable on the server: for a 32 MiB file, for instance, proof generation time drops from approximately 6,295 s to approximately 4.8 s (approximately 1,300x speed-up). As in the existing ElGamal implementation, however, VECKplus retains exponential ElGamal over the full file. Consequently, the client must perform ElGamal decryption and download ciphertexts that are at least 10x the plaintext size. We address both drawbacks in the second implementation, VECKstar: we replace bulk ElGamal encryption with a fast, hash-derived mask and confine public-key work to a Theta(lambda) sample tied together with a file-size-independent zk-SNARK, adding less than 0.1 s to verification in our prototype. Importantly, this also reduces the communication overhead from at least 10x to less than 50%. Together, these changes yield plaintext-scale performance. Finally, we bridge Bitcoin's secp256k1 and BLS12-381 with a file-size-independent zk-SNARK to run FDE fully off-chain over the Lightning Network, reducing fees from approximately USD 10 to less than USD 0.01 and payment latency to a few seconds.

cs.CR↗

arXiv2023

Condorcet Attack Against Fair Transaction Ordering

We introduce the Condorcet attack, a new threat to fair transaction ordering. Specifically, the attack undermines batch-order-fairness, the strongest notion of transaction fair ordering proposed to date. The batch-order-fairness guarantees that a transaction tx is ordered before tx' if a majority of nodes in the system receive tx before tx'; the only exception (due to an impossibility result) is when tx and tx' fall into a so-called "Condorcet cycle". When this happens, tx and tx' along with other transactions within the cycle are placed in a batch, and any unfairness inside a batch is ignored. In the Condorcet attack, an adversary attempts to undermine the system's fairness by imposing Condorcet cycles to the system. In this work, we show that the adversary can indeed impose a Condorcet cycle by submitting as few as two otherwise legitimate transactions to the system. Remarkably, the adversary (e.g., a malicious client) can achieve this even when all the nodes in the system behave honestly. A notable feature of the attack is that it is capable of "trapping" transactions that do not naturally fall inside a cycle, i.e. those that are transmitted at significantly different times (with respect to the network latency). To mitigate the attack, we propose three methods based on three different complementary approaches. We show the effectiveness of the proposed mitigation methods through simulations, and explain their limitations.

cs.CR↗

arXiv2020

Hashcashed Reputation with Application in Designing Watchtowers

We propose a novel reputation system to stimulate well-behaviour, and competition in online markets. Our reputation system is suited for markets where a publicly-verifiable "proof-of-misbehaviour" can be generated when one party misbehaves. Such markets include those that provide blockchain services, such as monitoring services by watchtowers. Watchtowers are entities that watch the blockchain on behalf of their offline clients to protect the clients' interests in applications such as payment networks (e.g., the Lightning network). In practice, there is no trust between clients and watchtowers, and it is challenging to incentivize watchtowers to well-behave (e.g., to refuse bribery). To showcase our reputation system, in this work, we create an open market of watchtowers, where watchtowers are motivated to not only deliver their promised service but also reduce their service fees in competition with each other.

cs.CR↗

arXiv2020

Barometers Can Hear, and Sense Finger Taps

Most modern smartphones are equipped with a barometer to sample air pressure. Accessing these samples is deemed harmless, hence does not require any permission. In this work, we show, however, that these samples can reveal sensitive information in smartphones with ingress protection. For the first time, it is shown that barometer samples, even at a low rate of 25 Hz, can leak information about the smartphone's speaker activity. Specifically, we use these samples to detect with high accuracy (>= 95%) whether the smartphone's speaker is silent or playing a sound such as a ringtone. In addition, we use the samples to detect the activity of an external speaker. Finally, we show that low-rate barometer samples can be used to 1) detect touchscreen finger taps with 100% accuracy, and 2) gain information about the positions of finger taps.

cs.CR↗

arXiv2020

The DAO Induction Attack Against the RPL-based Internet of Things

RPL is the emerging routing standard for low power and lossy networks (LLNs). LLN is a key component of the Internet of Things (IoT), hence its security is imperative for the age of IoT. In this work, we present the DAO induction attack, a novel attack against RPL. In this attack, a malicious insider or a compromised node periodically increments its DTSN number. Each such increment can trigger/induce a large number of control message transmissions in the network. We show that this degrades the network performance in terms of end-to-end latency, packet loss ratio, and power consumption. To mitigate, we propose a lightweight solution to detect the DAO induction attack. Our solution imposes nearly no overhead on IoT devices, which is important as these devices are typically constrained in terms of power, memory and processing.

cs.CR↗

arXiv2019

Packet Loss Recovery in Broadcast for Real-Time Applications in Dense Wireless Networks

Packet loss recovery in wireless broadcast is challenging, particularly for real-time applications which have strict and short delivery deadline. To recover the maximum number of lost packets within a short time, existing packet recovery solutions often rely on instantly decodable network coding (IDNC). Some of these solutions can recover nearly the maximum number of lost packets possible at the cost of collecting feedback from all (or a large percentage of) users. This is impractical in dense networks. In addition, their runtime grows with the number of users, which is not desirable due to the urgent delivery deadline of real-time applications. In this work, we introduce RIDNC, a random encoding approach to IDNC. We propose RACE, a light RIDNC encoder that can recover nearly as many lost packets as the optimal RIDNC encoder. We compare RACE with the CrowdWiFi encoder, a high performing packet loss recovery solution used in CrowdWiFi, a commercial system for broadcasting live video in dense networks. We show that RACE is up to two orders of magnitude faster than the CrowdWiFi encoder, and recovers more lost packets in practice, where there is not enough time to collect feedback from many users.

cs.NI↗

arXiv2019

The Gain of Energy Accumulation in Multi-hop Wireless Network Broadcast

Broadcast is a fundamental network operation, widely used in wireless networks to disseminate messages. The energy-efficiency of broadcast is important particularly when devices in the network are energy constrained. To improve the efficiency of broadcast, different approaches have been taken in the literature. One of these approaches is broadcast with energy accumulation. Through simulations, it has been shown in the literature that broadcast with energy accumulation can result in energy saving. The amount of this saving, however, has only been analyzed for linear multi-hop wireless networks. In this work, we extend this analysis to two-dimensional (2D) multi-hop networks. The analysis of saving in 2D networks is much more challenging than that in linear networks. It is because, unlike in linear networks, in 2D networks, finding minimum-energy broadcasts with or without energy accumulation are both NP-hard problems. Nevertheless, using a novel approach, we prove that this saving is constant when the path loss exponent alpha is strictly greater than two. Also, we prove that the saving is theta(log n) when alpha=2, where n denotes the number of nodes in the network.

cs.NI↗

arXiv2018

On Finding the Largest Minimum Distance of Locally Recoverable Codes

The (n, k, r)-Locally recoverable codes (LRC) studied in this work are (n, k) linear codes for which the value of each coordinate can be recovered by a linear combination of at most r other coordinates. In this paper, we are interested to find the largest possible minimum distance of (n,k,r)-LRCs, denoted D(n,k,r). We refer to the problem of finding the value of D(n,k,r) as the largest minimum distance (LMD) problem. LMD can be approximated within an additive term of one; it is known in the literature that D(n,k,r) is either equal to d* or d*-1, where d*=n-k-ceil(k/r) +2. Also, in the literature, LMD has been solved for some ranges of code parameters n, k and r. However, LMD is still unsolved for the general code parameters. In this work, we convert LMD to a simply stated problem in graph theory, and prove that the two problems are equivalent. In fact, we show that solving the derived graph theory problem not only solves LMD, but also directly translates to construction of optimal LRCs. Using these new results, we show how to easily derive the existing results on LMD and extend them. Furthermore, we show a close connection between LMD and a challenging open problem in extremal graph theory; an indication that LMD is perhaps difficult to solve for general code parameters.

cs.IT↗

arXiv2017

On the Average Locality of Locally Repairable Codes

A linear block code with dimension $k$, length $n$, and minimum distance $d$ is called a locally repairable code (LRC) with locality $r$ if it can retrieve any coded symbol by at most $r$ other coded symbols. LRCs have been recently proposed and used in practice in distributed storage systems (DSSs) such as Windows Azure storage and Facebook HDFS-RAID. Theoretical bounds on the maximum locality of LRCs ($r$) have been established. The \textit{average} locality of an LRC ($\overline{r}$) directly affects the costly repair bandwidth, disk I/O, and number of nodes involved in the repair process of a missing data block. There is a gap in the literature studying $\overline{r}$. In this paper, we establish a lower bound on $\overline{r}$ of arbitrary $(n,k,d)$ LRCs. Furthermore, we obtain a tight lower bound on $\overline{r}$ for a practical case where the code rate $(R=\frac{k}{n})$ is greater than $(1-\frac{1}{\sqrt{n}})^2$. Finally, we design three classes of LRCs that achieve the obtained bounds on $\overline{r}$. Comparing with the existing LRCs, our proposed codes improve the average locality without sacrificing such crucial parameters as the code rate or minimum distance.

cs.IT↗

arXiv2016

Optimal Locally Repairable Codes with Improved Update Complexity

For a systematic erasure code, update complexity (UC) is defined as the maximum number of parity blocks needed to be changed when some information blocks are updated. Locally repairable codes (LRCs) have been recently proposed and used in real-world distributed storage systems. In this paper, update complexity for optimal LRC is studied and both lower and upper bounds on UC are established in terms of length (n), dimension (k), minimum distance (d), and locality (r) of the code, when (r+1)|n. Furthermore, a class of optimal LRCs with small UC is proposed. Our proposed LRCs could be of interest as they improve UC without sacrificing optimality of the code.

cs.IT↗

arXiv2015

Multi-Version Coding

We derive a simple lower bound for the multi-version coding problem formulated in [1]. We also propose simple algorithms that almost match the lower bound derived. Another lower bound is proven for an extended version of the multi-version coding problem introduced in [2].

cs.DC↗

arXiv2014

Broadcast Throughput in Radio Networks: Routing vs. Network Coding

The broadcast throughput in a network is defined as the average number of messages that can be transmitted per unit time from a given source to all other nodes when time goes to infinity. Classical broadcast algorithms treat messages as atomic tokens and route them from the source to the receivers by making intermediate nodes store and forward messages. The more recent network coding approach, in contrast, prompts intermediate nodes to mix and code together messages. It has been shown that certain wired networks have an asymptotic network coding gap, that is, they have asymptotically higher broadcast throughput when using network coding compared to routing. Whether such a gap exists for wireless networks has been an open question of great interest. We approach this question by studying the broadcast throughput of the radio network model which has been a standard mathematical model to study wireless communication. We show that there is a family of radio networks with a tight $Θ(\log \log n)$ network coding gap, that is, networks in which the asymptotic throughput achievable via routing messages is a $Θ(\log \log n)$ factor smaller than that of the optimal network coding algorithm. We also provide new tight upper and lower bounds that show that the asymptotic worst-case broadcast throughput over all networks with $n$ nodes is $Θ(1 / \log n)$ messages-per-round for both routing and network coding.

cs.DS↗

arXiv2014

Randomized Broadcast in Radio Networks with Collision Detection

We present a randomized distributed algorithm that in radio networks with collision detection broadcasts a single message in $O(D + \log^6 n)$ rounds, with high probability. This time complexity is most interesting because of its optimal additive dependence on the network diameter $D$. It improves over the currently best known $O(D\log\frac{n}{D}\,+\,\log^2 n)$ algorithms, due to Czumaj and Rytter [FOCS 2003], and Kowalski and Pelc [PODC 2003]. These algorithms where designed for the model without collision detection and are optimal in that model. However, as explicitly stated by Peleg in his 2007 survey on broadcast in radio networks, it had remained an open question whether the bound can be improved with collision detection. We also study distributed algorithms for broadcasting $k$ messages from a single source to all nodes. This problem is a natural and important generalization of the single-message broadcast problem, but is in fact considerably more challenging and less understood. We show the following results: If the network topology is known to all nodes, then a $k$-message broadcast can be performed in $O(D + k\log n + \log^2 n)$ rounds, with high probability. If the topology is not known, but collision detection is available, then a $k$-message broadcast can be performed in $O(D + k\log n + \log^6 n)$ rounds, with high probability. The first bound is optimal and the second is optimal modulo the additive $O(\log^6 n)$ term.

cs.DS↗

arXiv2013

A Bound on the Throughput of Radio Networks

We consider the well-studied radio network model: a synchronous model with a graph G=(V,E) with |V|=n where in each round, each node either transmits a packet, with length B=Omega(log n) bits, or listens. Each node receives a packet iff it is listening and exactly one of its neighbors is transmitting. We consider the problem of k-message broadcast, where k messages, each with Theta(B) bits, are placed in an arbitrary nodes of the graph and the goal is to deliver all messages to all the nodes. We present a simple proof showing that there exist a radio network with radius 2 where for any k, broadcasting k messages requires at least Omega(k log n) rounds. That is, in this network, regardless of the algorithm, the maximum achievable broadcast throughput is O(1/log n).

cs.DS↗

arXiv2011

Bounding Interference in Wireless Ad Hoc Networks with Nodes in Random Position

The interference at a wireless node s can be modelled by the number of wireless nodes whose transmission ranges cover s. Given a set of positions for wireless nodes, the interference minimization problem is to assign a transmission radius (equivalently, a power level) to each node such that the resulting communication graph is connected, while minimizing the maximum interference. We consider the model introduced by von Rickenback et al. (2005), in which each transmission range is represented by a ball and edges in the communication graph are symmetric. The problem is NP-complete in two dimensions (Buchin 2008) and no polynomial-time approximation algorithm is known. Furthermore, even in one dimension (the highway model), the problem's complexity is unknown and the maximum interference of a set of n wireless nodes can be as high as Theta(sqrt(n)) (von Rickenback et al. 2005). In this paper we show how to solve the problem efficiently in settings typical for wireless ad hoc networks. In particular, we show that if node positions are represented by a set P of n points selected uniformly and independently at random over a d-dimensional rectangular region, for any fixed d, then the topology given by the closure of the Euclidean minimum spanning tree of P has maximum interference O(log n) with high probability. We extend this bound to a general class of communication graphs over a broad set of probability distributions. Next we present a local algorithm that constructs a graph from this class; this is the first local algorithm to provide an upper bound on the expected maximum interference. Finally, we discuss an empirical evaluation of our algorithm with a suite of simulation results.

cs.CG↗