This paper proposes a novel greedy algorithm, called Creditability-Estimation based Matching Pursuit (CEMP), for the compressed sensing signal recovery. As proved in the algorithm of Stagewise Orthogonal Matching Pursuit (StOMP), two Gaussian distributions are followed by the matched filter coefficients corresponding to and without corresponding to the actual support set of the original sparse signal, respectively. Therefore, the selection for each support point is interpreted as a process of hypothesis testing, and the preliminarily selected support set is supposed to consist of rejected atoms. A hard threshold, which is controlled by an input parameter, is used to implement the rejection. Because the Type I error may happen during the hypothesis testing, not all the rejected atoms are creditable to be the true support points. The creditability of each preliminarily selected support point is evaluated by a well-designed built-in mechanism, and the several most creditable ones are adaptively selected into the final support set without being controlled by any extra external parameters. Moreover, the proposed CEMP does not necessitate the sparsity level to be a priori control parameter in operation. In order to verify the performance of the proposed algorithm, Gaussian and Pulse Amplitude Modulation sparse signals are measured in the noiseless and noisy cases, and the experiments of the compressed sensing signal recoveries by several greedy algorithms including CEMP are implemented. The simulation results show the proposed CEMP can achieve the best performances of the recovery accuracy and robustness as a whole. Besides, the experiment of the compressed sensing image recovery shows that CEMP can recover the image with the highest Peak Signal to Noise Ratio (PSNR) and the best visual quality.

Traceability links between requirements and source code are helpful in software reuse and maintenance tasks. However, manually recovering links in a large group of products requires significant costs and some links may be overlooked. Here, we propose a semi-automatic method to recover traceability links between requirements and source code in the same series of large software products. In order to support differences in representation between requirements and source code, we recover links by using the configuration management log as an intermediary. We refine the links by classifying requirements and code elements in terms of whether they are common to multiple products or specific to one. As a result of applying our method to real products that have 60KLOC, we have recovered valid traceability links within a reasonable amount of time. Automatic parts have taken 13 minutes 36 seconds, and non-automatic parts have taken about 3 hours, with a recall of 76.2% and a precision of 94.1%. Moreover, we recovered some links that were unknown to engineers. By recovering traceability links, software reusability and maintainability will be improved.

This paper presents a novel architecture for a fault-tolerant and dual modular redundancy (DMR) system using a checkpoint recovery approach. The architecture features exploitation of SRAM with simultaneous copy and instantaneous compare function. It can perform low-latency data copying between dual cores. Therefore, it can carry out fast backup and rollback. Furthermore, it can reduce the power consumption during data comparison process compared to the cyclic redundancy check (CRC). Evaluation results show that, compared with the conventional checkpoint/restart DMR, the proposed architecture reduces the cycle overhead by 97.8% and achieves a 3.28% low-latency execution cycle even if a one-time fault occurs when executing the task. The proposed architecture provides high reliability for systems with a real-time requirement.

This paper proposes a disaster recovery method for transport networks. In a scenario of recovery from a disaster, a network is repaired through multiple restoration stages because repair resources are limited. In a practical case, a network should provide the reachability of important traffic in transient stages, even as service interruption risks and/or operational overheads caused by transport paths switching are suppressed. Then, we define the multi-objective optimization problem: maximizing the traffic recovery ratio and minimizing the number of switched transport paths at each stage. We formulate our problem as linear programming, and show that it yields pareto-optimal solutions of traffic recovery versus the number of switched paths. We also propose a heuristic algorithm for applying to networks consisting of a few hundred nodes, and show that it can produce sub-optimal solutions that differ only slightly from optimal solutions.

This paper presents key recovery attacks on Sandwich-MAC instantiating MD5, where Sandwich-MAC is an improved variant of HMAC and achieves the same provable security level and better performance especially for short messages. The increased interest in lightweight cryptography motivates us to analyze such a MAC scheme. Our attacks are based on a distinguishing-H attack on HMAC-MD5 proposed by Wang et al. We first improve its complexity from 297 to 289.04. With this improvement, we then propose key recovery attacks on Sandwich-MAC-MD5 by combining various techniques such as distinguishing-H for HMAC-MD5, IV Bridge for APOP, dBB-near-collisions for related-key NMAC-MD5, meet-in-the-middle attack etc. In particular, we generalize a previous key-recovery technique as a new tool exploiting a conditional key-dependent distribution. Surprisingly, a key which is even longer than the tag size can be recovered without the knowledge of the key size. Finally, our attack also improves the previous partial-key (K1) recovery on MD5-MAC, and extends it to recover both of K1 and K2.

RC4 is a widely-used stream cipher, adopted in many standard protocols, such as WEP, WPA and SSL/TLS, as a standard encryption algorithm. Isobe et al. proposed a plaintext recovery attack on RC4 in the broadcast setting, where the same plaintext is encrypted with different secret keys. Their attack is able to recover the first 257bytes by exploiting the biases of the initial bytes of a keystream. In this paper, we propose two types of full plaintext recovery attacks that are able to recover all the bytes, even after the 258th byte, of a plaintext, unlike Isobe et al.'s attack. To achieve this, we combine the use of multiple keystream biases appropriately. The first attack utilizes the initial byte biases and Mantin's long-term bias. This attack can recover the first 1000 terabytes of a plaintext from 234 ciphertexts with a probability of almost one. The second attack is based on two long-term biases. Since this attack does not rely on the biases of the initial bytes of the RC4 keystream, it can recover any byte of a plaintext, even if the initial bytes are disregarded. Given 235 ciphertexts encrypted by different keys, any byte of a target plaintext can be recovered with a probability close to one.

In this paper, we deal with upper bounds for the security of some Feistel networks. Such a topic has been discussed since the introduction of Luby-Rackoff construction. The Luby-Rackoff construction is unrealistic because its round functions must be chosen at random from the set of all functions. Knudsen dealt with a more practical construction whose round functions are chosen at random from a family of 2k randomly chosen functions, and showed an upper bound for the security by demonstrating generic key recovery attacks. However it is still difficult for designers to choose functions randomly. Then, this paper considers the security of some Feistel networks which have more efficient and practical round functions, and such Feistel networks are indeed used by some Feistel ciphers in practice. We show new properties using the relationship between plaintexts and ciphertexts. We propose new generic key recovery attacks by using our properties, and confirm the feasibility by implementing the attack on Feistel ciphers with small block sizes. As a result, we conclude that efficient and practical 6-round Feistel networks are not secure.

Razor Flip-Flop (FF) is a good combination for the dynamic voltage scaling (DVS) technique to achieve high energy efficiency. We previously proposed a RazorProtector scheme, which uses, under a very high IR-drop zone, a redundant data-path to provide a very fast recovery for a Razor-FF based processor. In this paper, we propose a dynamic method to adjust the redundancy level to fine-grained fit both the program behaviors and processor manufacturing variations so as to achieve an optimal power saving. We design an online turning method to adjust the redundancy level according to the most related parameters, ILP (Instruction Level Parallelism) and DCF (Delay Criticality Factor). Our simulation results show that under a workload suite with different behaviors, the adaptive redundancy can achieve better Energy Delay Product (EDP) reduction than any static controls. Compared to the traditional application of Razor-FF and DVS, our proposed dynamic control achieves an EDP reduction of 56% in average for the workloads we studied.

In this paper, an image prior based on soft-morphological filters and its application to image recovery are presented. In morphological image processing, a gray-scale image is represented as a subset in a three-dimensional space, which is spanned by spatial and intensity axes. Morphological opening and closing, which are basic operations in morphological image processing, respectively approximate the image subset and its complementary images as the unions of structuring elements that are translated in the three-dimensional space. In this study, the opening and closing filters are applied to an image prior to resolve the regularization problem of image recovery. When the proposed image prior is applied, the image is recovered as an image that has no noise component, which is eliminated by the opening and closing. However, the closing and opening filters are less able to eliminate Gaussian noise. In order to improve the robustness against Gaussian noise, the closing and opening filters are respectively approximated as soft-closing and soft-opening with relaxed max and min functions. In image recovery experiments, image denoising and deblurring using the proposed prior are demonstrated. Comparisons of the proposed prior with the existing priors that impose a penalty on the gradient of the intensity are also shown.

An efficient subcarrier allocation scheme of a supporting cell is proposed to recover the communication of faulty cell users in an OFDM-based wireless system. With the proposed subcarrier allocation scheme, the number of subcarriers allocated to faulty cell users is maximized while the average throughput of supporting cell users is maintained at a desired level. To find the maximum number of subcarriers allocated to faulty cell users, the average throughput of the subcarrier with the k-th smallest channel gain in a subcarrier group is derived by an inductive method. It is shown by simulation that the proposed subcarrier allocation scheme can provide more subcarriers to faulty cell users than the random selection subcarrier allocation scheme.

Feedback data loss can severely degrade overall system performance. In addition, it can affect the control and computation of the Cyber-physical Systems (CPS). CPS hold enormous potential for a wide range of emerging applications that include different data traffic patterns. These data traffic patterns have wide varieties of diversities. To recover various traffic patterns we need to know the nature of their underlying property. In this paper, we propose a data recovery framework for different traffic patterns of CPS, which comprises data pre-processing step. In the proposed framework, we designed a Data Pattern Analyzer to classify the different patterns and built a model based on the pattern as a data pre-processing step. Inside the framework, we propose a data recovery scheme, called Efficient Temporal and Spatial Data Recovery (ETSDR) algorithm to recover the incomplete feedback for CPS to maintain real time control. In this algorithm, we utilize the temporal model based on the traffic pattern and consider the spatial correlation of the nearest neighbor sensors. Numerical results reveal that the proposed ETSDR outperforms both the weighted prediction (WP) and the exponentially weighted moving average (EWMA) algorithms regardless of the increment percentage of missing data in terms of the root mean square error, the mean absolute error, and the integral of absolute error.

Most of the previous work on power optimization regarded the capacity of battery power as an ideal constant value. In fact, experiments showed that 30% of the total battery capacity was wasted by improper discharge pattern [1]. In this letter, a battery-aware task scheduling protocol which harnesses one of the typical characteristics of batteries, i.e., battery recovery, is proposed to extend usage time for smart phones. The key idea is to adjust the working schedule of the components in smart phones for more energy recovering. Experiments show that when the proposed protocol is applied in an online music application, as much as 9% lifespan extension for batteries can be obtained.

We discuss how to recover RSA secret keys from noisy key bits with erasures and errors. There are two known algorithms recovering original secret keys from noisy keys. At Crypto 2009, Heninger and Shacham proposed a method for the case where an erroneous version of secret keys contains only erasures. Subsequently, Henecka et al. proposed a method for an erroneous version containing only errors at Crypto 2010. For physical attacks such as side-channel and cold boot attacks, we need to study key recovery from a noisy secret key containing both erasures and errors. In this paper, we propose a method to recover a secret key from such an erroneous version and analyze the condition for error and erasure rates so that our algorithm succeeds in finding the correct secret key in polynomial time. We also evaluate a theoretical bound to recover the secret key and discuss to what extent our algorithm achieves this bound.

This letter proposes a novel intrusion tolerant system consisting of several virtual machines (VMs) that refresh the target system periodically and by live migration, which monitors the many features of the VMs to identify and replace exhausted VMs. The proposed scheme provides adequate performance and dependability against denial of service (DoS) attacks. To show its efficiency and security, we conduct experiments on the CSIM20 simulator, which showed 22% improvement in a normal situation and approximately 77.83% improvement in heavy traffic in terms of the response time compared to that reported in the literature. We measure and compare the response time. The result show that the proposed scheme has shorter response time and maintains than other systems and supports services during the heavy traffic.

Presented is a new measuring and reconstruction framework of Compressed Sensing (CS), aiming at reducing the measurements required to ensure faithful reconstruction. A sparse vector is segmented into sparser vectors. These new ones are then randomly sensed. For recovery, we reconstruct these vectors individually and assemble them to obtain the original signal. We show that the proposed scheme, referred to as SegOMP, yields higher probability of exact recovery in theory. It is finished with much smaller number of measurements to achieve a same reconstruction quality when compared to the canonical greedy algorithms. Extensive experiments verify the validity of the SegOMP and demonstrate its potentials.

After the disclosure of the RC4 algorithm in 1994, a number of keystream biases of RC4 were reported, e.g., Mantin and Shamir showed that the second byte of the keystream is biased to 0, Sepehrdad et al. found that the l-th byte of the keystream is biased to -l, and Maitra et al. showed that 3rd to 255th bytes of the keystream are also biased to 0, where l is the keylength in byte. However, it is unknown that which bias is strongest in each byte of initial bytes. This paper comprehensively analyzes initial keystream biases of RC4. In particular, we introduce several new biases in the initial (1st to 257th) bytes of the RC4 keystream, which are substantially stronger than known biases. Combining the new biases with the known ones, a complete list of strongest single-byte biases in the first 257bytes of the RC4 keystream is constructed for the first time. Then, we show that our set of these biases are applicable to plaintext recovery attacks, key recovery attacks and distinguishing attacks.

Wide-area VM migration is a technology with potential to aid IT services recovery since it can be used to evacuate virtualized servers to safe locations upon a critical disaster. However, the amount of data involved in a wide-area VM migration is substantially larger compared to VM migrations within LAN due to the need to transfer virtualized storage in addition to memory and CPU states. This increase of data makes it challenging to relocate VMs under a limited time window with electrical power. In this paper, we propose a mechanism to improve live storage migration across WAN. The key idea is to reduce the amount of data to be transferred by proactively caching virtual disk blocks to a backup site during regular VM operation. As a result of pre-cached disk blocks, the proposed mechanism can dramatically reduce the amount of data and consequently the time required to live migrate the entire VM state. The mechanism was evaluated using a prototype implementation under different workloads and network conditions, and we confirmed that it dramatically reduces the time to complete a VM live migration. By using the proposed mechanism, it is possible to relocate a VM from Japan to the United States in just under 40 seconds. This relocation would otherwise take over 1500 seconds, demonstrating that the proposed mechanism was able to reduce the migration time by 97.5%.

This paper studies the performance of code-aided (CA) soft-information based carrier phase recovery, which iteratively exploits the extrinsic information from channel decoder to improve the accuracy of phase synchronization. To tackle the problem of strong coupling between phase recovery and decoding, a semi-analytical model is proposed to express the distribution of extrinsic information as a function of phase offset. Piecewise approximation of the hyperbolic tangent function is employed to linearize the expression of soft symbol decision. Building on this model, open-loop characteristic and closed-loop performance of CA iterative soft decision-directed (ISDD) carrier phase synchronizer are derived in closed-form. Monte Carlo simulation results corroborate that the proposed expressions are able to characterize the performance of CA ISDD carrier phase recovery for systems with different channel codes.

Smart TVs are expected to play a leading role in the future networked intelligent screen market. Currently, many operators are planning to deploy it in large scale in a few years. Therefore, it is necessary for smart TVs to provide high quality services for users. Packet loss is one critical reason that decreases the QoS in smart TVs. Even a very small amount of packet loss (1-2%) can decrease the QoS and affect users' experience seriously. This paper applies stochastic differential equations to analyzing the queue in the buffer of access points in smart TV multicast systems, demonstrates the reason for packet loss, and then proposes an end-to-end error recovery scheme (short as OPRSFEC) whose core algorithm is based on Reed-Solomon theory, and optimizes four aspects in finite fields: 1) Using Cauchy matrix instead of Vandermonde matrix to code and decode; 2) generating inverse matrix by table look-up; 3) changing the matrix multiplication into the table look-up; 4) originally dividing the matrix multiplication. This paper implements the scheme on the application layer, which screens the heterogeneity of terminals and servers, corrects 100% packet loss (loss rate is 1%-2%) in multicast systems, and brings very little effect on real-time users experience. Simulations demonstrate that the proposed scheme has good performances, successfully runs on Sigma and Mstar Moca TV terminals, and increases the QoS of smart TVs. Recently, OPRSFEC middleware has become a part of IPTV2.0 standard in Shanghai Telecom and has been running on the Mstar boards of Haier Moca TVs properly.

This paper presents a new scalable method to considerably reduce the rollback propagation effect of the conventional optimistic message logging by utilizing positive features of reliable FIFO group communication links. To satisfy this goal, the proposed method forces group members to replicate different receive sequence numbers (RSNs), which they assigned for each identical message to their group respectively, into their volatile memories. As the degree of redundancy of RSNs increases, the possibility of local recovery for each crashed process may significantly be higher. Experimental results show that our method can outperform the previous one in terms of the rollback distance of non-faulty processes with a little normal time overhead.