Ming Yang Kao

Hamsa: fast signature generation for zero-day polymorphic worms with provable attack resilience

Zero-day polymorphic worms pose a serious threat to the security of Internet infrastructures. Given their rapid propagation, it is crucial to detect them at edge networks and automatically generate signatures in the early stages of infection. Most existing approaches for automatic signature generation need host information and are thus not applicable for deployment on high-speed network links. In this paper, we propose Hamsa, a network-based automated signature generation system for polymorphic worms which is fast, noise-tolerant and attack-resilient. Essentially, we propose a realistic model to analyze the invariant content of polymorphic worms which allows us to make analytical attack-resilience guarantees for the signature generation algorithm. Evaluation based on a range of polymorphic worms and polymorphic engines demonstrates that Hamsa significantly outperforms Polygraph (J. Newsome et al., 2005) in terms of efficiency, accuracy, and attack resilience

A dynamic programming approach to de novo peptide sequencing via tandem mass spectrometry

Tandem mass spectrometry fragments a large number of molecules of the same peptide sequence into charged molecules of prefix and suffix peptide subsequences and then measures mass/charge ratios of these ions. The de novo peptide sequencing problem is to reconstruct the peptide sequence from a given tandem mass spectral data of k ions. By implicitly transforming the spectral data into an NC-spectrum graph G (V, E) where /V/ = 2k + 2, we can solve this problem in O(/V//E/) time and O(/V/2) space using dynamic programming. For an ideal noise-free spectrum with only b- and y-ions, we improve the algorithm to O(/V/ + /E/) time and O(/V/) space. Our approach can be further used to discover a modified amino acid in O(/V//E/) time. The algorithms have been implemented and tested on experimental data.

Complexities for Generalized Models of Self-Assembly

In this paper, we extend Rothemund and Winfrees examination of the tile complexity of tile self-assembly [6]. They provided a lower bound of Ω(log <i>N</i>/log log <i>N</i>) on the tile complexity of assembling an <i>N</i> × <i>N</i> square for almost all <i>N</i>. Adleman et al. [1] gave a construction which achieves this bound. We consider whether the tile complexity for self-assembly can be reduced through several natural generalizations of the model. One of our results is a tile set of size <i>O</i>(√log <i>N</i>) which assembles an <i>N</i> × <i>N</i> square in a model which allows flexible glue strength between non-equal glues (This was independently discovered in [3]). This result is matched by a lower bound dictated by Kolmogorov complexity. For three other generalizations, we show that the Ω(log <i>N</i>/log log <i>N</i>) lower bound applies to <i>N</i> × <i>N</i> squares. At the same time, we demonstrate that there are some other shapes for which these generalizations allow reduced tile sets. Specifically, for thin rectangles with length <i>N</i> and width <i>k</i>, we provide a tighter lower bound of Ω(<i>N</i>(1/<i>k</i>)/<i>k</i>) for the standard model, yet we also give a construction which achieves <i>O</i>(log <i>N</i>/log log <i>N</i>) complexity in a model in which the temperature of the tile system is adjusted during assembly. We also investigate the problem of verifying whether a given tile system uniquely assembles into a given shape, and show that this problem is NP-hard.

Compact Encodings of Planar Graphs via Canonical Orderings and Multiple Parentheses

We consider the problem of coding planar graphs by binary strings. Depending on whether O(1)-time queries for adjacency and degree are supported, we present three sets of coding schemes which all take linear time for encoding and decoding. The encoding lengths are significantly shorter than the previously known results in each case.

Reducing tile complexity for self-assembly through temperature programming

We consider the tile self-assembly model and how tile complexity can be eliminated by permitting the temperature of the self-assembly system to be adjusted throughout the assembly process. To do this, we propose novel techniques for designing tile sets that permit an arbitrary length m binary number to be encoded into a sequence of O(m) temperature changes such that the tile set uniquely assembles a supertile that precisely encodes the corresponding binary number. As an application, we show how this provides a general tile set of size O(1) that is capable of uniquely assembling essentially any n X n square, where the assembled square is determined by a temperature sequence of length O(log n) that encodes a binary description of n. This yields an important decrease in tile complexity from the required Ω(log n/log log n) for almost all n when the temperature of the system is fixed. We further show that for almost all n, no tile system can simultaneously achieve both o(log n) temperature complexity and O(log n/log log n) tile complexity, showing that both versions of an optimal square building scheme have been discovered. This work suggests that temperature change can constitute a natural, dynamic method for providing input to self-assembly systems that is potentially superior to the current technique of designing large tile sets with specific inputs hardwired into the tileset.

Reversible sketches: enabling monitoring and analysis over high-speed data streams

A key function for network traffic monitoring and analysis is the ability to perform aggregate queries over multiple data streams. Change detection is an important primitive which can be extended to construct many aggregate queries. The recently proposed sketches are among the very few that can detect heavy changes online for high speed links, and thus support various aggregate queries in both temporal and spatial domains. However, it does not preserve the keys (e. g., source IP address) of flows, making it difficult to reconstruct the desired set of anomalous keys. To address this challenge, we propose the reversible sketch data structure along with reverse hashing algorithms to infer the keys of culprit flows. There are two phases. The first operates online, recording the packet stream in a compact representation with negligible extra memory and few extra memory accesses. Our prototype single FPGA board implementation can achieve a throughput of over 16 Gb/s for 40-byte packet streams (the worst case). The second phase identifies heavy changes and their keys from the representation in nearly real time. We evaluate our scheme using traces from large edge routers with OC-12 or higher links. Both the analytical and experimental results show that we are able to achieve online traffic monitoring and accurate change/intrusion detection over massive data streams on high speed links, all in a manner that scales to large key space size. To the best of our knowledge, our system is the first to achieve these properties simultaneously.

Optimal broadcast in all-port wormhole-routed hypercubes

We give an optimal algorithm that broadcasts on an n-dimensional hypercube in O(n/ log/sub 2/ (n+1)) routing steps with wormhole, e-cube routing and all-port communication. Previously, the best algorithm of P.K. McKinley and C. Trefftz (1993) requires [n/2] routing steps. We also give routing algorithms that achieve tight time bounds for n /spl les/7. >

Randomized Self-assembly for Approximate Shapes

In this paper we design tile self-assembly systems which assemble arbitrarily close approximations to target squares with arbitrarily high probability. This is in contrast to previous work which has only considered deterministic assemblies of a single shape. Our technique takes advantage of the ability to assign tile concentrations to each tile type of a self-assembly system. Such an assignment yields a probability distribution over the set of possible assembled shapes. We show that by considering the assembly of close approximations to target shapes with high probability, as opposed to exact deterministic assembly, we are able to achieve significant reductions in tile complexity. In fact, we restrict ourselves to constant sized tile systems, encoding all information about the target shape into the tile concentration assignment. In practice, this offers a potentially useful tradeoff, as large libraries of particles may be infeasible or require substantial effort to create, while the replication of existing particles to adjust relative concentration may be much easier. To illustrate our technique we focus on the assembly of n×nsquares, a special case class of shapes whose study has proven fruitful in the development of new self-assembly systems.

Optimal Constructions of Hybrid Algorithms

We study on-line strategies for solving problems with hybrid algorithms. There is a problemQandw basicalgorithms for solvingQ. For some ??w, we have a computer with ? disjoint memory areas, each of which can be used to run a basic algorithm and store its intermediate results. In the worst case, only one basic algorithm can solveQin finite time, and all of the other basic algorithms run forever without solvingQ. To solveQwith ahybridalgorithm constructed from the basic algorithms, we run a basic algorithm for some time, then switch to another, and continue this process untilQis solved. The goal is to solveQin the least amount of time. Usingcompetitive ratiosto measure the efficiency of a hybrid algorithm, we construct an optimal deterministic hybrid algorithm and an efficient randomized hybrid algorithm. This resolves an open question on searching with multiple robots posed by Baeza-Yates, Culberson, and Rawlins. We also prove that our randomized algorithm is optimal for ?=1, settling a conjecture of Kao, Reif, and Tate.

Searching in an Unknown Environment

Searching for a goal is a central and extensively studied problem in computer science. In classical searching problems, the cost of a search function is simply the number of queries made to an oracle that knows the position of the goal. In many robotics problems, as well as in problems from other areas, we want to charge a cost proportional to the distance between queries (e.g., the time required to travel between two query points). With this cost function in mind, the abstract problem known as thew-lane cow-path problem was designed. There are known optimal deterministic algorithms for the cow-path problem; we give the first randomized algorithm in this paper. We show that our algorithm is optimal for two paths (w=2) and give evidence that it is optimal for larger values ofw. Subsequent to the preliminary version of this paper, Kaoet al.(in“Proceedings, 5th ACM?SIAM Symposium on Discrete Algorithm,” pp. 372?381, 1994) have shown that our algorithm is indeed optimal for allw?2. Our randomized algorithm gives expected performance that is almost twice as good as is possible with a deterministic algorithm. For the performance of our algorithm, we also derive the asymptotic growth with respect tow?despite similar complexity results for related problems, it appears that this growth has never been analyzed.