Adaptive Adversary Research Articles

On the power of randomization in distributed algorithms in dynamic networks with adaptive adversaries

This paper investigates the power of randomization in general distributed algorithms in dynamic networks where the network's topology may evolve over time, as determined by some adaptive adversary. In such a context, randomization may help algorithms to better deal with i) “bad” inputs to the algorithm, and ii) evolving topologies generated by “bad” adaptive adversaries. We prove that randomness offers limited power to better deal with “bad” adaptive adversary. We define a simple notion of prophetic adversary for determining the evolving topologies. Such an adversary accurately predicts all randomness in the algorithm beforehand, and hence the randomness will be useless against “bad” prophetic adversaries. Given a randomized algorithm P whose time complexity satisfies some mild conditions, we prove that P can always be converted to a new algorithm Q with comparable time complexity, even when Q runs against prophetic adversaries. This implies that the benefit of P using randomness for dealing with the adaptive adversaries is limited.

Forward-Secure Edge Authentication for Graphs

AbstractThe edge authentication of graphs has been studied in the literature because graphs are one of the most widely used data organization structures. The majority of such schemes cannot be used to authenticate general directed graphs (GDGs); other schemes cannot be used for addressing either the issue of dynamic update or the issue of information leakage (such as the existence of nodes/edges and structural relationship of the graph). Also, all the existing schemes do not consider the forward security: if the signer’s secret key has been compromised, all previously generated signatures remain valid. This property provides high-level security protection for authentication schemes. To address these issues, in this work, we propose a forward-secure edge authentication scheme for GDGs. Observe that existing such schemes can only give a proof such that ‘there is an edge between nodes $u$ and $v$’. Our scheme, however, can directly give a proof such that ‘there is no edge between nodes $u$ and $v$’, which makes the function of edge authentication schemes more diverse. Moreover, our proposed scheme is proven to be secure against an adaptive chosen-message adversary in the random oracle model. To show its desirable performance, we analyze the computational costs of our scheme and compare it with other related schemes in terms of features.

Randomized renaming in shared memory systems

Renaming is a task in distributed computing where n processes are assigned new names from a name space of size m. The problem is called tight if m=n, and loose if m>n. In recent years renaming came to the fore again and new algorithms were developed. For tight renaming in asynchronous shared memory systems, Alistarh et al. describe a construction based on the AKS network that assigns all names within O(logn) steps per process. They also show that, depending on the size of the name space, loose renaming can be done considerably faster. For m=(1+ϵ)⋅n and constant ϵ, they achieve a step complexity of O(loglogn).In this paper we consider tight as well as loose renaming and introduce randomized algorithms that achieve their tasks with high probability. The model assumed is the asynchronous shared-memory model against an adaptive adversary. Our algorithm for loose renaming maps n processes to a name space of size m=(1+2∕(logn)ℓ)⋅n=(1+o(1))⋅n performing O(ℓ⋅(loglogn)2) test-and-set operations. In the case of tight renaming, we present a protocol that assigns n processes to n names with step complexity O(logn), but without the overhead and impracticality of the AKS network. This algorithm utilizes modern hardware features in form of a counting device which is also described in the paper. This device may have the potential to speed up other distributed algorithms as well.

A Moving Target Defense for Securing Cyber-Physical Systems

This article considers the design and analysis of multiple moving target defenses for recognizing and isolating attacks on cyber-physical systems. We consider attackers who perform integrity attacks on a set of sensors and actuators in a control system. In such cases, a model aware adversary can carefully design attack vectors to bypass bad data detection and identification filters while causing damage to the control system. To counter such an attacker, we propose the moving target defense which introduces stochastic, time-varying parameters in the control system. The underlying random dynamics of the system limit an attacker's model knowledge and inhibits his/her ability to construct stealthy attack sequences. Moreover, the time-varying nature of the dynamics thwarts adaptive adversaries. We explore three main designs. First, we consider a hybrid system where parameters within the existing plant are switched among multiple modes. We demonstrate how such an approach can enable both the detection and identification of malicious nodes. Next, we investigate the addition of an extended system with dynamics that are coupled to the original plant but do not affect system performance. An attack on the original system will affect the authenticating subsystem and in turn be revealed by a set of sensors measuring the extended plant. Lastly, we propose the use of sensor nonlinearities to enhance the effectiveness of the moving target defense. The nonlinear dynamics act to conceal normal operational behavior from an attacker who has tampered with the system state, further hindering an attacker's ability to glean information about the time-varying dynamics. In all cases mechanisms for analysis and design are proposed. Finally, we analyze attack detectability for each moving target defense by investigating expected lower bounds on the detection statistic. Our contributions are tested via simulation.

Distributed Online Linear Regressions

We study online linear regression problems in a distributed setting, where the data is spread over a network. In each round, each network node proposes a linear predictor, with the objective of fitting the network-wide data. It then updates its predictor for the next round according to the received local feedback and information received from neighboring nodes. The predictions made at a given node are assessed through the notion of regret, defined as the difference between their cumulative network-wide square errors and those of the best off-line network-wide linear predictor. Various scenarios are investigated, depending on the nature of the local feedback (full information or bandit feedback), on the set of available predictors (the decision set), and the way data is generated (by an oblivious or adaptive adversary). We propose simple and natural distributed regression algorithms, involving, at each node and in each round, a local gradient descent step and a communication and averaging step where nodes aim at aligning their predictors to those of their neighbors. We establish regret upper bounds typically in O(T <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3/4</sup> ) when the decision set is unbounded and in O(√T) in case of bounded decision set.

Broadcast Complexity and Adaptive Adversaries in Verifiable Secret Sharing

Verifiable secret sharing (VSS) is one of the basic problems in the theory of distributed cryptography and has an important role in secure multiparty computation. In this case, it is tried to share a confidential data as secret, between multiple nodes in a distributed system, in the presence of an active adversary that can destroy some nodes, such that the secret can be reconstructed with the participation of certain size of honest nodes. A dynamic adversary can change its corrupted nodes among the protocol. So far, there is not a formal definition and there are no protocols of dynamic adversaries in VSS context. Also, another important question is, would there exist a protocol to share a secret with a static adversary with at most 1 broadcast round? In this paper, we provide a formal definition of the dynamic adversary. The simulation results prove the efficiency of the proposed protocol in terms of the runtime, the memory usage, and the number of message exchanges. We show that the change period of the dynamic adversary could not happen in less than 4 rounds in order to have a perfectly secure VSS, and then we establish a protocol to deal with this type of adversary. Also, we prove that the lower bound of broadcast complexity for the static adversary is (2,0)-broadcast rounds.

Adaptively Simulation-Secure Attribute-Hiding Predicate Encryption

This paper demonstrates how to achieve simulation-based strong attribute hiding against adaptive adversaries for predicate encryption (PE) schemes supporting expressive predicate families under standard computational assumptions in bilinear groups. Our main result is a simulation-based adaptively strongly partially-hiding PE (PHPE) scheme for predicates computing arithmetic branching programs (ABP) on public attributes, followed by an inner-product predicate on private attributes. This simultaneously generalizes attribute-based encryption (ABE) for boolean formulas and ABP's as well as strongly attribute-hiding PE schemes for inner products. The proposed scheme is proven secure for any a priori bounded number of ciphertexts and an unbounded (polynomial) number of decryption keys, which is the best possible in the simulation-based adaptive security framework. This directly implies that our construction also achieves indistinguishability-based strongly partially-hiding security against adversaries requesting an unbounded (polynomial) number of ciphertexts and decryption keys. The security of the proposed scheme is derived under (asymmetric version of) the well-studied decisional linear (DLIN) assumption. Our work resolves an open problem posed by Wee in TCC 2017, where his result was limited to the semi-adaptive setting. Moreover, our result advances the current state of the art in both the fields of simulation-based and indistinguishability-based strongly attribute-hiding PE schemes. Our main technical contribution lies in extending the strong attribute hiding methodology of Okamoto and Takashima [EUROCRYPT 2012, ASIACRYPT 2012] to the framework of simulation-based security and beyond inner products.

Distributed robust time-efficient broadcasting algorithms for multi-channel wireless multi-hop networks with channel disruption

Broadcasting is a fundamental problem for wireless multi-hop networks such as wireless ad hoc and sensor networks. In this paper, we study distributed robust time-efficient global broadcasting for SINR-based (i.e., Signal-to-Interference-plus-Noise-Ratio-based) multi-channel wireless multihop networks subject to channel disruption. In this study, we make the following assumptions: i) for successful packet reception, the SINR at receivers must exceed a certain threshold; ii) an adversary exists in the network, which uniformly and randomly chooses t > 0 channels to disrupt from total F > 1 available channels in every round. To address the broadcasting issue in such networks, we first propose a degree-aware broadcasting algorithm and then propose a degree-independent broadcasting algorithm. The proposed algorithms elaborately integrate distributed channel selection and transmission scheduling at different nodes while considering the following factors: the impact of SINR constraint, availability of channels, sending probability on selected channel, presence of adversary, with and without node degree information. We present the detailed design of the two algorithms. We deduce their worst-case time performance to accomplish the task of global broadcasting with high probability. We further prove that both algorithms can still preserve the same time performance under more powerful oblivious adversary and weakly adaptive adversary. Simulation results show that the proposed algorithms have satisfactory average-case time performance.

Efficient randomized test-and-set implementations

We study randomized test-and-set (TAS) implementations from registers in the asynchronous shared memory model with n processes. We introduce the problem of group election, a natural variant of leader election, and propose a framework for the implementation of TAS objects from group election objects. We then present two group election algorithms, each yielding an efficient TAS implementation. The first implementation has expected max-step complexity $$O(\log ^*k)$$ in the location-oblivious adversary model, and the second has expected max-step complexity $$O(\log \log k)$$ against any read/write-oblivious adversary, where $$k\le n$$ is the contention. These algorithms improve the previous upper bound by Alistarh and Aspnes (in: Proceedings of the 25th International Symposium on Distributed Computing, 2011) of $$O(\log \log n)$$ expected max-step complexity in the oblivious adversary model. We also propose a modification to a TAS algorithm devised by Alistarh, Attiya, Gilbert, Giurgiu, and Guerraoui (in: Proceedings of the 24th International Symposium on Distributed Computing, DISC 2010) for the strong adaptive adversary, which improves its space complexity from super-linear to linear, while maintaining its $$O(\log n)$$ expected max-step complexity. We then describe how this algorithm can be combined with any randomized TAS algorithm that has expected max-step complexity T(n) in a weaker adversary model, so that the resulting algorithm has $$O(\log n)$$ expected max-step complexity against any strong adaptive adversary and O(T(n)) in the weaker adversary model. Finally, we prove that for any randomized 2-process TAS algorithm, there exists a schedule determined by an oblivious adversary such that with probability at least $$1/4^t$$ one of the processes needs at least t steps to finish its TAS operation. This complements a lower bound by Attiya and Censor-Hillel (SIAM J Comput 39(8):3885–3904, 2010) on a similar problem for $$n\ge 3$$ processes.

Cross-layer traffic analysis countermeasures against adaptive attackers of wireless sensor networks

In most Wireless Sensor Network (WSN) applications the sensor nodes forward their measurements to a central base station (BS). The unique role of the BS makes it a natural target for an adversary’s attack. Even if a WSN employs conventional security mechanisms such as encryption and authentication, an adversary may apply traffic analysis techniques to locate the BS. This motivates a significant need for improved BS anonymity to protect the identity, role, and location of the BS. Previous work presented distributed beamforming as a very effective anonymity-boosting technique. However, such work assumed that the adversary is unaware of the countermeasure, and thus the anonymity performance could be unattainable. In this paper we extend our preliminary work from Ward and Younis (Proceedings of the IEEE military communications conference (MILCOM 2016), Baltimore, MD, 2016) to show that the adversary could adapt the attack strategy when knowing of the use of distributed beamforming. We analyze two strategies for such an adaptive attack, one using Evidence Theory and one using Traffic Volume. We then develop a cross-layer countermeasure that incorporates distributed beamforming to successfully misdirect such an adaptive adversary and boost BS anonymity. The effectiveness of our approach is validated through simulation.

Verifiable outsourcing computation for modular exponentiation from shareable functions

Verifiable computation (VC) enables a computationally weak client to outsource the computation of a function f to a more powerful but untrusted server. The server returns an answer that allows the client to recover the correct result, accompanied by a proof of correctness. The basic requirement of a VC scheme is efficiency, i.e., the time consuming in preparing its input and verifying the server’s proof must be less than the time required to compute the function on its own. In this paper, we propose a novel outsourcing scheme for modular exponentiation from shareable functions, which is secure even in the presence of adaptive adversaries. Compared with previous works, our algorithm is superior in both efficiency and checkability. In order to keep the exponent privacy, our algorithm invokes the less subroutine, which accounts for the largest proportion of the time spent. The client can detect the error with overwhelming probability. We then gave a comparation that demonstrates the efficiency of the proposed outsourcing algorithm and scheme. Finally, we propose a generic scheme for shareable function family, and analyze the concrete security.

Public-Key Encryption with Integrated Keyword Search

Since the last decade, the public-key encryption with keyword search (PEKS) has been studied as a popular technique for searching data over encrypted files. The notion finds useful application for fine-grained data search on outsourced encrypted data like iCloud, mobile cloud data, etc. In this paper, we present a concrete public-key encryption (PKE)+PEKS scheme and prove its security in the standard model. We prove that our scheme is both IND-PKE-CCA secure, that is, provides message confidentiality against an adaptive chosen-ciphertext adversary, and IND-PEKS-CCA secure, that is, provides keyword privacy against an adaptive chosen-ciphertext adversary, under the Symmetric eXternal Diffie-Hellman (SXDH) assumption. Our construction uses asymmetric pairings which enable a fast implementation useful for practical applications. Our scheme has much shorter ciphertexts than other known PKE+PEKS schemes. Particularly, we compare our scheme with other proposed PEKS and integrated PKE+PEKS schemes and provide a relative analysis of various parameters including assumption, security, and efficiency.

AuCPace: Efficient verifier-based PAKE protocol tailored for the IIoT

Increasingly connectivity becomes integrated in products and devices that previously operated in a stand-alone setting. This observation holds for many consumer applications in the so-called "Internet of Things" (IoT) as well as for corresponding industry applications (IIoT), such as industrial process sensors. Often the only practicable means for authentication of human users is a password. The security of password-based authentication schemes frequently forms the weakest point of the security infrastructure. In this paper we first explain why a tailored protocol designed for the IIoT use case is considered necessary. The differences between IIoT and the conventional Internet use-cases result in largely modified threats and require special procedures for allowing both, convenient and secure use in the highly constrained industrial setting. Specifically the use of a verifier-based password-authenticated key-exchange (V-PAKE) protocol as a hedge against public-key-infrastructure (PKI) failures is considered important. Availability concerns for the case of failures of (part of) the communication infrastructure makes local storage of access credentials mandatory. The larger threat of physical attacks makes it important to use memory-hard password hashing. This paper presents a corresponding tailored protocol, AuCPace, together with a security proof within the Universal Composability (UC) framework considering fully adaptive adversaries. We also introduce a new security notion of partially augmented PAKE that provides specific performance advantages and makes them suitable for a larger set of IIoT applications. We also present an actual instantiation of our protocol, AuCPace25519, and present performance results on ARM Cortex-M0 and Cortex-M4 microcontrollers. Our implementation realizes new speed-records for PAKE and X25519 Diffie-Hellman for the ARM Cortex M4 architecture.

Modeling a multi-target attacker-defender game with multiple attack types

How to allocate limited defense resources effectively and efficiently to prevent damages is a critical and difficult problem, especially when faced with adaptive attackers and various attack types (methods that the attacker uses). There has been a growing amount of literature on studying the strategic interactions between attackers (terrorists) and defenders (government). This research presents a novel class of multi-target attacker-defender games where the attackers have multiple attacking options including assassination, armed assault, bombing/explosion, facility/infrastructure attack, hijacking, hostage taking, and unarmed assault. Different attack types may lead to different attack success probabilities, consequences, and effectiveness of defensive resource allocation. Faced with multiple attack types and adaptive attackers, the defender distributes a limited amount of resources to multiple targets to minimize the total expected loss in a sequential game as the first mover. We provide numerical illustrations for the model results. The model is illustrated by: (a) using historical terrorism and defensive investment data to estimate the model parameters, and (b) comparing the historical resource allocation with the model outputs. From the sensitivity analyses, we find that the defense cost effectiveness against the “Hijacking,” and “Bombing/Explosion” attack types play a critical role in decreasing the expected loss. The proposed multi-attack model leads to less expected loss than that of both the single-attack model and the historical allocation from the Urban Area Security Initiative (UASI). This paper provides new insights on modeling defensive resource allocation models related to adaptive adversaries.

Ordered and delayed adversaries and how to work against them on a shared channel

An execution of a distributed algorithm is often seen as a game between the algorithm and a conceptual adversary causing specific distractions to the computation. In this work we define a class of ordered adaptive adversaries, which cause distractions—in particular crashes—online according to some partial order of the participating stations, which is fixed by the adversary before the execution. We distinguish: Linearly-Ordered adversary, restricted by some pre-defined linear order of (potentially) crashing stations; Anti-Chain-Ordered adversary, previously known as the Weakly-Adaptive adversary, which is restricted by some pre-defined set of crash-prone stations (it can be seen as an ordered adversary with the order being an anti-chain, i.e., a collection of incomparable elements, consisting of these stations); k-Thick-Ordered adversary restricted by partial orders of stations with a maximum anti-chain of size k. We initiate a study of how they affect performance of algorithms. For this purpose, we focus on the well-known Do-All problem of performing t tasks by p synchronous crash-prone stations communicating on a shared channel. The channel restricts communication by the fact that no message is delivered to the operational stations if more than one station transmits at the same time. The question addressed in this work is how the ordered adversaries controlling crashes of stations influence work performance, defined as the total number of available processor steps during the whole execution and introduced by Kanellakis and Shvartsman (Distrib Comput 5(4):201–217, 1992) in the context of Write-All algorithms. The first presented algorithm solves the Do-All problem with work {mathcal {O}}(t+p sqrt{t}log p) against the Linearly-Ordered adversary. Surprisingly, the upper bound on performance of this algorithm does not depend on the number of crashes f and is close to the absolute lower bound varOmega (t+psqrt{t}) proved in Chlebus et al. (Distrib Comput 18(6):435–451, 2006). Another algorithm is developed against the Weakly-Adaptive adversary. Work done by this algorithm is mathcal {O}(t + psqrt{t} + pmin left{ p/(p-f),tright} log p ), which is close to the lower bound varOmega (t + psqrt{t} + pmin left{ p/(p-f),tright} ) proved in [11] and answers the open questions posed there. We generalize this result to the class of k-Thick-Ordered adversaries, in which case the work of the algorithm is bounded by mathcal {O}(t + psqrt{t} + pmin left{ p/(p-f),k,tright} log p ). We complement this result by proving the almost matching lower bound Ω(t+pt+pminp/(p-f),k,t).\\documentclass[12pt]{minimal}\t\t\t\t\\usepackage{amsmath}\t\t\t\t\\usepackage{wasysym}\t\t\t\t\\usepackage{amsfonts}\t\t\t\t\\usepackage{amssymb}\t\t\t\t\\usepackage{amsbsy}\t\t\t\t\\usepackage{mathrsfs}\t\t\t\t\\usepackage{upgreek}\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\t\t\t\t\\begin{document}$$\\begin{aligned} \\varOmega (t + p\\sqrt{t} + p\\min \\left\\{ p/(p-f),k,t\\right\\} ). \\end{aligned}$$\\end{document}Independently from the results for the ordered adversaries, we consider a class of delayed adaptive adversaries, which could see random choices with some delay. We present an algorithm that works efficiently against the 1-RD adversary, which could see random choices of stations with one round delay, achieving close to optimal {mathcal {O}}(t+p sqrt{t}log ^{2} p) work complexity. This shows that restricting the adversary by not allowing it to react on random decisions immediately makes it significantly weaker, in the sense that there is an algorithm achieving (almost) optimal work performance.

Minimizing the Two-Round Even–Mansour Cipher

The r-round (iterated) Even-Mansour cipher (also known as key-alternating cipher) defines a block cipher from r fixed public n-bit permutations P1,…,P r as follows: given a sequence of n-bit round keys k0,…,k r , an n-bit plaintext x is encrypted by xoring round key k0, applying permutation P1, xoring round key k1, etc. The (strong) pseudorandomness of this construction in the random permutation model (i.e., when the permutations P1,…,P r are public random permutation oracles that the adversary can query in a black-box way) was studied in a number of recent papers, culminating with the work of Chen and Steinberger (EUROCRYPT 2014), who proved that the r-round Even-Mansour cipher is indistinguishable from a truly random permutation up to \( \mathcal{O} (2^{\frac{rn}{r+1}})\) queries of any adaptive adversary (which is an optimal security bound since it matches a simple distinguishing attack). All results in this entire line of work share the common restriction that they only hold under the assumption that the round keys k0,…,k r and the permutations P1,…,P r are independent. In particular, for two rounds, the current state of knowledge is that the block cipher E(x) = k2 ⊕ P2(k1 ⊕ P1(k0 ⊕ x)) is provably secure up to \( \mathcal{O} (2^{2n/3})\) queries of the adversary, when k0, k1, and k2 are three independent n-bit keys, and P1 and P2 are two independent random n-bit permutations. In this paper, we ask whether one can obtain a similar bound for the two-round Even-Mansour cipher from just one n-bit key and one n-bit permutation. Our answer is positive: when the three n-bit round keys k0, k1, and k2 are adequately derived from an n-bit master key k, and the same permutation P is used in place of P1 and P2, we prove a qualitatively similar \( \widetilde{ \mathcal{O} } (2^{2n/3})\) security bound (in the random permutation model). To the best of our knowledge, this is the first “beyond the birthday bound” security result for AES-like ciphers that does not assume independent round keys.

An augmented approach for pseudo-free groups in smart cyber-physical system

The contemporary advancement in smart technology has led to a greater business prospective. Smart system like cyber-physical system (CPS) has become prevalent in many area of applications. Challenges in integration of CPS with group of network has physical components to sense the state of changes in the real world is paving way towards the introduction of enhanced security mechanism. In this paper, we propose a security framework for group of network is a pseudo-free to communicate with the cyber physical system to assure high security. Pseudo-freeness is a very strong assumption of security used in cryptography. Group is said to be pseudo-free group, if an adversary who is allowed to see group description, is unable to solve non-trivial equations. Non-trivial equations are the equations that have no solution in a free group. The notion of pseudo-freeness was introduced with few open problems whether such groups exists in cryptosystem or not. The conjecture that the RSA group is pseudo-free has been settled for case of static adversary who is given only the group description and its goal is to come up with an equation and solution. Later on the notion of pseudo-freeness has been extended to adaptive adversary for case of univariate equations. In case of adaptive pseudo-free groups, the adversary learns solutions of some non-trivial equations before producing a new equation. Here we make extension to the notion of pseudo-free groups from univariate to multivariate equations and system of equations in face of adaptive adversary. We define and prove the security of adaptive pseudo-free groups for case of multivariate equations and system of equations. According to the results, this framework can be used as a system design for a group to have strong security with cyber physical system.

Integrating the API SRA methodology and game theory for improving chemical plant protection

Game theory has been employed in academia to study the improvement of security in chemical plants. Being able to model intelligent interactions between adaptive adversaries and defenders is the main advantage of game theory, while the main criticisms of the usage of game theory is that it is mathematically complicated and that it over-simplifies reality. The ANSI/API standard 780 on Security Risk Assessment for the petroleum and petrochemical industries (abbreviated as the “API SRA methodology”), conversely, provides a systematic approach for obtaining qualitative or semi-quantitative data, and is criticized on its failure at modelling strategic (and intelligent) adversaries. Integration of game theory and the API SRA methodology for improving chemical plant protection is therefore an interesting domain of study. In this paper, the API SRA methodology bridges the gap between “chemical security reality” and “chemical security theory (that is, game theoretic models)”, by providing quantitative inputs for game theoretic models and by reflecting on game theoretic results with respect to industrial practice.

Near-Optimal and Practical Jamming-Resistant Energy-Efficient Cognitive Radio Communications

This paper studies the problem of jamming-resistant spectrum aggregation and access (SAA) for energy-efficiency (EE) cognitive radio communications. We consider various jamming behaviors, where jammers may attack all available channels with arbitrarily changing strategies over time, attack a subset of the channels at certain time slots, or have different intelligence, i.e., oblivious or adaptive adversary, and so on. Without any priori knowledge about the channels and jammers, it is very challenging to design an efficient and practical jamming-resistant SAA algorithm to reach the optimal EE goal. In this paper, we utilize the advanced martingale concentration inequalities in an multi-armed bandits-based online learning framework to facilitate the optimal detection of various jamming behaviors. We first define a novel EE model for discontiguous orthogonal frequency division multiplexing to facilitate scalable SAA over distributed spectrum pools in practice. Then, the jamming-resistant dynamic channel access problem is formulated as a regret minimization problem. Meanwhile, an online stochastic gradient descent with bandit feedback procedure is adopted to allocate the transmit power. The proposed algorithm can autonomously detect the environmental features and find a near-optimal solution in each attacking scenario. Our algorithm is implemented with low complexity and with multiple users under some practical jamming scenarios. Extensive numerical studies show that under some practical jamming scenarios, our algorithm has an EE improvement of 45.3% over a fixed learning period, and an improvement of 82.5% in terms of learning duration compared with existing approaches.

Sade: competitive MAC under adversarial SINR

This paper considers the problem of how to efficiently share a wireless medium which is subject to harsh external interference or even jamming. So far, this problem is understood only in simplistic single-hop or unit disk graph models. We in this paper initiate the study of MAC protocols for the SINR interference model (a.k.a. physical model). This paper makes two contributions. First, we introduce a new adversarial SINR model which captures a wide range of interference phenomena. Concretely, we consider a powerful, adaptive adversary which can jam nodes at arbitrary times and which is only limited by some energy budget. Our second contribution is a distributed MAC protocol called Sade which provably achieves a constant competitive throughput in this environment: we show that, with high probability, the protocol ensures that a constant fraction of the non-blocked time periods is used for successful transmissions.