NXNSAttack: Recursive DNS Inefficiencies and Vulnerabilities

This paper exposes a new vulnerability and introduces a corresponding attack, the NoneXistent Name Server Attack (NXNSAttack), that disrupts and may paralyze the DNS system, making it difficult or impossible for Internet users to access websites, web e-mail, online video chats, or any other online resource. The NXNSAttack generates a storm of packets between DNS resolvers and DNS authoritative name servers. The storm is produced by the response of resolvers to unrestricted referral response messages of authoritative name servers. The attack is significantly more destructive than NXDomain attacks (e.g., the Mirai attack): i) It reaches an amplification factor of more than 1620x on the number of packets exchanged by the recursive resolver. ii) In addition to the negative cache, the attack also saturates the 'NS' section of the resolver caches. To mitigate the attack impact, we propose an enhancement to the recursive resolver algorithm, MaxFetch(k), that prevents unnecessary proactive fetches. We implemented the MaxFetch(1) mitigation enhancement on a BIND resolver and tested it on real-world DNS query datasets. Our results show that MaxFetch(1) degrades neither the recursive resolver throughput nor its latency. Following the discovery of the attack, a responsible disclosure procedure was carried out, and several DNS vendors and public providers have issued a CVE and patched their systems

Consensus in Equilibrium: Can One Against All Decide Fairly?

Is there an equilibrium for distributed consensus when all agents except one collude to steer the decision value towards their preference? If an equilibrium exists, then an n-1 size coalition cannot do better by deviating from the algorithm, even if it prefers a different decision value. We show that an equilibrium exists under this condition only if the number of agents in the network is odd and the decision is binary (among two possible input values). That is, in this framework we provide a separation between binary and multi-valued consensus. Moreover, the input and output distribution must be uniform, regardless of the communication model (synchronous or asynchronous). Furthermore, we define a new problem - Resilient Input Sharing (RIS), and use it to find an iff condition for the (n-1)-resilient equilibrium for deterministic binary consensus, essentially showing that an equilibrium for deterministic consensus is equivalent to each agent learning all the other inputs in some strong sense. Finally, we note that (n-2)-resilient equilibrium for binary consensus is possible for any n. The case of (n-2)-resilient equilibrium for multi-valued consensus is left open

The Role of A-priori Information in Networks of Rational Agents

Until now, distributed algorithms for rational agents have assumed a-priori knowledge of n, the size of the network. This assumption is challenged here by proving how much a-priori knowledge is necessary for equilibrium in different distributed computing problems. Duplication - pretending to be more than one agent - is the main tool used by agents to deviate and increase their utility when not enough knowledge about n is given. We begin by proving that when no information on n is given, equilibrium is impossible for both Coloring and Knowledge Sharing. We then provide new algorithms for both problems when n is a-priori known to all agents. However, what if agents have partial knowledge about n? We provide tight upper and lower bounds that must be a-priori known on n for equilibrium to be possible in Leader Election, Knowledge Sharing, Coloring, Partition and Orientation

The Synergy of Finite State Machines

What can be computed by a network of n randomized finite state machines communicating under the stone age model (Emek & Wattenhofer, PODC 2013)? The inherent linear upper bound on the total space of the network implies that its global computational power is not larger than that of a randomized linear space Turing machine, but is this tight? We answer this question affirmatively for bounded degree networks by introducing a stone age algorithm (operating under the most restrictive form of the model) that given a designated I/O node, constructs a tour in the network that enables the simulation of the Turing machine\u27s tape. To construct the tour with high probability, we first show how to 2-hop color the network concurrently with building a spanning tree

Selecting a Leader in a Network of Finite State Machines

This paper studies a variant of the leader election problem under the stone age model (Emek and Wattenhofer, PODC 2013) that considers a network of n randomized finite automata with very weak communication capabilities (a multi-frequency asynchronous generalization of the beeping model\u27s communication scheme). Since solving the classic leader election problem is impossible even in more powerful models, we consider a relaxed variant, referred to as k-leader selection, in which a leader should be selected out of at most k initial candidates. Our main contribution is an algorithm that solves k-leader selection for bounded k in the aforementioned stone age model. On (general topology) graphs of diameter D, this algorithm runs in O~(D) time and succeeds with high probability. The assumption that k is bounded turns out to be unavoidable: we prove that if k = omega (1), then no algorithm in this model can solve k-leader selection with a (positive) constant probability

Towards consistency oblivious programming

15th International Conference, OPODIS 2011, Toulouse, France, December 13-16, 2011. ProceedingsIt is well known that guaranteeing program consistency when accessing shared data comes at the price of degraded performance and scalability. This paper initiates the investigation of consistency oblivious programming (COP). In COP, sections of concurrent code that meet certain criteria are executed without checking for consistency. However, checkpoints are added before any shared data modification to verify the algorithm was on the right track, and if not, it is re-executed in a more conservative and expensive consistent way. We show empirically that the COP approach can enhance a software transactional memory (STM) framework to deliver more efficient concurrent data structures from serial source code. In some cases the COP code delivers performance comparable to that of more complex fine-grained structures