We present Moving Participants Turtle Consensus (MPTC), an asynchronous consensus protocol for crash and Byzantine-tolerant distributed systems. MPTC uses various moving target defense strategies to tolerate certain Denial-of-Service (DoS) attacks issued by an adversary capable of compromising a bounded portion of the system. MPTC supports on the fly reconfiguration of the consensus strategy as well as of the processes executing this strategy when solving the problem of agreement. It uses existing cryptographic techniques to ensure that reconfiguration takes place in an unpredictable fashion thus eliminating the adversary’s advantage on predicting protocol and execution-specific information that can be used against the protocol. We implement MPTC as well as a State Machine Replication protocol and evaluate our design under different attack scenarios. Our evaluation shows that MPTC approximates best case scenario performance even under a well-coordinated DoS attack.

This paper investigates cache placement on a cooperative cache built from individual client caches in an online social network or web service. We use a service that maintains a mapping between content and the clients that cache it, and propose cache placement schemes that leverage relationships between clients (for example, social links) and workload statistics, proactively placing content on clients that are likely to access it. We evaluate efficacy through simulation, comparing our schemes against commonly used cache placement algorithms as well as optimal placement. We synthesize a workload to match characteristics of online social networks. Simulation results of our proposed caching schemes impose moderate network overhead and show considerable improvement to the client's cache hit ratio, even under churn.

Consensus is a basic building block in middleware configuration services [4, 18]. While such services are designed to tolerate crash failures in asynchronous settings, they may not stand up well to Denial-of-Service (DoS) attacks. Specifically, malicious clients can carefully craft workloads that substantially degrade the performance of many state-of-the-art consensus protocols. By exploiting protocol-specific vulnerabilities, attackers can constantly force the protocol participants to slow execution paths [8]. In this paper, we investigate designing consensus protocols that provide acceptable performance under DoS attacks that aim to saturate the bandwidth of protocol participants.

SUMMARY: BioTextQuest combines automated discovery of significant terms in article clusters with structured knowledge annotation, via Named Entity Recognition services, offering interactive user-friendly visualization. A tag-cloud-based illustration of terms labeling each document cluster are semantically annotated according to the biological entity, and a list of document titles enable users to simultaneously compare terms and documents of each cluster, facilitating concept association and hypothesis generation. BioTextQuest allows customization of analysis parameters, e.g. clustering/stemming algorithms, exclusion of documents/significant terms, to better match the biological question addressed. AVAILABILITY: http://biotextquest.biol.ucy.ac.cy CONTACT: [email protected]; [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

We propose a new theoretical model for passively mobile wireless sensor networks, called P M , standing for passively mobile machines . The main modification w.r.t. the population protocol model (Angluin et al., 2006) [30] is that agents now, instead of being automata, are Turing Machines. We provide general definitions for unbounded memories, but we are mainly interested in computations upper-bounded by plausible space limitations. However, we prove that our results hold for more general cases. We focus on complete interaction graphs and define the complexity classes PMSPACE ( f ( n ) ) parametrically, consisting of all predicates that are stably computable by some PM protocol that uses O ( f ( n ) ) memory in each agent. We provide a protocol that generates unique identifiers from scratch only by using O ( log n ) memory, and use it to provide an exact characterization of the classes PMSPACE ( f ( n ) ) when f ( n ) = Ω ( log n ) : they are precisely the classes of all symmetric predicates in NSPACE ( n f ( n ) ) . As a consequence, we obtain a space hierarchy of the PM model when the memory bounds are Ω ( log n ) . We next explore the computability of the PM model when the protocols use o ( log log n ) space per machine and prove that SEM = PMSPACE ( f ( n ) ) when f ( n ) = o ( log log n ) , where SEM denotes the class of the semilinear predicates. Finally, we establish that the minimal space requirement for the computation of non-semilinear predicates is O ( log log n ) .