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Advanced persistent attacks, incorporated by sophisticated malware, are on the rise against hosts, user applications and utility software. Modern malware hide their malicious payload by applying packing mechanism. Packing tools instigate code encryption to protect the original malicious payload. Packing is employed in tandem with code obfuscation/encryption/compression to create malware variants. Despite being just a variant of known malware, the packed malware invalidates the traditional signature based malware detection as packing tools create an envelope of packer code around the original base malware. Therefore, unpacking becomes a mandatory phase prior to anti-virus scanning for identifying the known malware hidden behind packing layers. Existing techniques of unpacking solutions increase execution overhead of AV scanners in terms of time. This paper illustrates an easy to use approach which works in two phases to reduce this overhead. The first phase (ESCAPE) discriminates the packed code from the native code (non-packed) by using random block entropy. The second phase (PEAL) validates inferences of ESCAPE by employing bi-classification (packed vs native) model using relevant hex byte features extracted blockwise. The proposed approach is able to shrink the overall execution time of AV scanners by filtering out native samples and avoiding excessive unpacking overhead. Our method has been evaluated against a set consisting of real packed instances of malware and benign programs. [ABSTRACT FROM AUTHOR]

Mobile ad hoc networks (MANETs) are vulnerable to various types of attacks due to inherently in-secure wireless communication medium and multihop routing communication process. In this paper, we analyze the behavior and impact of JellyFish attack over TCP-based MANETs. We have implemented and evaluated all three variants of JellyFish attack namely JF-reorder, JF-delay and JF-drop through simulation processes. These attacks exploit the behavior of closed loop protocols such as TCP and disturb the communication process without disobeying any protocol rules, thus the detection process becomes difficult. Consequently, traffic is disrupted leading to degradation in network throughput. Through extensive simulation results that are obtained using an industry standard scalable network simulator called EXata-Cyber, impact of these attacks in terms of network throughput, overhead incurred and end-to-end delay is analyzed and used for devising detection and countermeasure. We have proposed a light-weight direct trust-based detection (DTD) algorithm which detect and remove a JellyFish node from an active communication route. In our proposed DTD algorithm, each node uses locally calculated trust values which are collected over a time period to identify whether its neighbor node is a JF-attacker or not. [ABSTRACT FROM AUTHOR]

Android Smartphone popularity has increased malware threats forcing security researchers and AntiVirus (AV) industry to carve out smart methods to defend Smartphone against malicious apps. Robust signature based solutions to mitigate threats become necessary to protect the Smartphone and confidential user data. Here we present AndroSimilar, an approach which generates signatures by extracting statistically robust features, to detect malicious Android apps. Proposed method is effective against code obfuscation and repackaging, widely used techniques to propagate unseen variants of known malware by evading AV signatures. AndroSimilar is a syntactic foot-printing mechanism that finds regions of statistical similarity with known malware to detect those unknown, zero day samples. We also show that syntactic similarity considering whole app, rather than just embedded DEX file is more effective, contrary to known fuzzy hashing approach. We also apply clustering algorithm to identify small set of family signatures to reduce overall signature database size. Proposed approach can be refined to deploy as Smartphone AV. [ABSTRACT FROM AUTHOR]

In this paper, we develop and evaluate an adaptive self-configurable routing framework that can deal with dynamic nature of mobile ad hoc networks and provides quality-of-service (QoS) guarantees for efficient video streaming. Proposed framework mainly consists of two major components. Firstly, it is a reactive bandwidth-aware node-disjoint multipath routing protocol which determines routes based on the specified bandwidth requirements of the requesting application. The second component of the framework is a session admission control (SAC) process that permits or denies a session to enter into the network based on the current availability of network bandwidth. We also propose methods to handle QoS violations caused by network mobility and congestion by keeping backup routes, performing local route recovery, avoiding routing through short-lived low quality links and periodic monitoring of the active transmission routes. To verify our proposed algorithms, the network with H.264/SVC encoded video traces which are generated from real-time video traffic is used for modeling the behaviour of the source nodes. It has been observed that reactively discovered and maintained routes on the basis of the most recent information about network topology and available resources can significantly improve the admission decision accuracy of SAC process, in turn improving the quality of received video traffic significantly. [ABSTRACT FROM AUTHOR]

Image Dehazing is a fast growing research area with several practical applications. Dehazing improves the image quality that has been affected due to the scattering phenomenon caused by air or water. Extensive work has been carried out in this field. But a significant research gap exists when it comes to large-scale performance evaluation covering a variety of dehazing approaches, datasets, and Image Quality Assessment (IQA) metrics. In this work, we try to fill this gap by reviewing more than 100 methods from different categories. We present a complete taxonomy for image dehazing methods. Haze and IQA datasets were discussed and compared. In addition, we also contribute a real-world dense-to-low high and low-resolution hazy image dataset. Our real hazy images dataset (D2L-Haze) contains 107 natural outdoor dense and moderate haze images. Qualitative and Quantitative evaluation of dehazing approaches allows us to identify their strength and limitations. Several shortcomings of the existing techniques and some open challenges are discussed. To the best of our knowledge, this is the first extensive review that covers all the aspects of Daytime image enhancement and dehazing. [ABSTRACT FROM AUTHOR]

As there is large amount of data generated from various web applications which are difficult to manage in cloud databases. Solution to this problem is to partition the data. In this paper three techniques named Horizontal, vertical and workload driven partitioning are reviewed. The main focus of the paper is to compare these techniques on the bases of complexity, scalability, consistency and number of distributed transactions. It provides result, based on that we can choose the most relevant partitioning technique to store cloud data. [ABSTRACT FROM AUTHOR]

Background: The procedures of anterior segmental osteotomy are stable, versatile and can be undertaken for multiple deformities affecting the anterior portion of jaws. Objectives: To describe indications in which anterior segmental osteotomy alone can correct maxillomandibular deformities and if adjunct surgery is needed or not. Orthosurgical planning with cephalometric predictions of those deformities of anterior portions of jaws which can be corrected by anterior segmental osteotomy. Achieve occlusion and periodical follow-up of the operated patients to analyze changes produced by surgery and stability of results clinico-radiographically. Material and methods: The study consisted of 16 selected patients of which 9 were female and 7 were male. The ages ranged from 17 to 25 years. Patients with skeletal deformity along with malocclusion which was too severe to be corrected orthodontically were selected. History and examinations were carried out as per standardized protocol. The parameters were laid down only after reviewing the literature and discussion with an orthodontist as presurgical and postsurgical orthodontics are considered mandatory for these cases. Results: Presurgical orthodontics is required for decompensating the intradental and interdental relationship. Cephalometric studies should be mandatory. Model surgery and construction of an occlusal wafer was of great help in achieving the desired position of osteotomized segments intraoperatively. [ABSTRACT FROM AUTHOR]

ABSTRACT Collusion attack is an attack against Optimised Link State Routing (OLSR) protocol in mobile ad hoc network. Two malicious nodes work together so that routes to the target (victim) node(s) are not established in the network. Multipoint relay (MPR) selection process in OLSR is exploited to achieve this route denial. Packet delivery ratio for the target drops to 0% for nodes at distance of 3 hops or more. In this paper, we propose use of convergence characteristics of OLSR in designing effective, resource efficient countermeasures for packet dropping attacks such as collusion attack. We propose a detection method and countermeasure Scruple where discovery packets called ScruplePackets are injected to probe routes from target node to its three-hop neighbours. Acquired information is analysed to conclude if the node is a target of collusion attack. We also propose a novel attack-resistant method named Forced MPR Switching OLSR in which a node temporarily blacklists potential attackers on observing symptoms of the attack, thereby, forcing recomputation of its MPR set. Proposed approaches incur minimal penalty on network performance. Simulations conducted on Network Simulator 3 confirm effectiveness of the proposed method. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]