Abstract: Botnets, which consist of remotely controlled compromised machines called bots, provide a distributed platform for several threats against cyber world entities and enterprises. Intrusion detection system (IDS) provides an efficient countermeasure against botnets. It continually monitors and analyzes network traffic for potential vulnerabilities and possible existence of active attacks. A payload-inspection-based IDS (PI-IDS) identifies active intrusion attempts by inspecting transmission control protocol and user datagram protocol packet’s payload and comparing it with previously seen attacks signatures. However, the PI-IDS abilities to detect intrusions might be incapacitated by packet encryption. Traffic-based IDS (T-IDS) alleviates the shortcomings of PI-IDS, as it does not inspect packet payload; however, it analyzes packet header to identify intrusions. As the network’s traffic grows rapidly, not only the detection-rate is critical, but also the efficiency and the scalability of IDS become more significant. In this paper, we propose a state-of-the-art T-IDS built on a novel randomized data partitioned learning model (RDPLM), relying on a compact network feature set and feature selection techniques, simplified subspacing and a multiple randomized meta-learning technique. The proposed model has achieved 99.984% accuracy and 21.38 s training time on a well-known benchmark botnet dataset. Experiment results demonstrate that the proposed methodology outperforms other well-known machine-learning models used in the same detection task, namely, sequential minimal optimization, deep neural network, C4.5, reduced error pruning tree, and randomTree.

Abstract: In this paper, a novel anti-swing control method is proposed for 3-dimensional (3-D) underactuated overhead crane systems, which guarantees fast transportation and efficient swing suppression. Specifically, to increase the performance of the payload swing suppression, a swing-suppressing element is introduced, based on which a novel positioning error signal is constructed. Then, a new control method is developed, and the overall system is divided into two subsystems. The stability analysis of the two subsystems and the overall system is given. In addition, the convergence of the system states is proved. Simulation results are provided to demonstrate the superior performance of the proposed controller over the existing controllers. Meanwhile, the practical performance of the proposed controller is experimentally validated on a portable overhead crane test-bed.

Abstract: A system and method configured for providing a cryptographic platform for exchanging information. One or more information transactions including encrypted information may be generated and/or provided to a distributed ledger. The one or more information transactions may include information intended for one or more parties. Information transactions intended for one or more parties may be identified. An information transaction may include one or more of a transaction identifier associated with one or more parties, an information payload, and/or other information. The information payload may include encrypted information. The encrypted information may be encrypted with one or more public keys associated with one or more parties. One or more information transactions may be retrieved from the distributed ledger. The encrypted information may be decrypted with one or more private keys that correspond to the public keys. Presentation of the encrypted information to one or more parties may be facilitated.

Abstract: A system and method of recording data from a number of devices in a distributed network system in a manner adaptable for auditing the device output. The devices may include one or more control, sensor, edge, or peripheral computing devices physically separate in the distributed network system and in communication with a control server. Such distributed networks systems are common in SCADA or IoT applications. The content stream of data records output from the devices are recorded; a payload stripped stream of data records which are stripped of the payload are recorded and preferably retained by an escrow service. The metadata of the data records includes the hash value of one or more predecessor data records. The hash values are calculated based on the payload and a linkage function, preferably a cryptographic function. A comparison of hash values of the payload stripped stream and the content stream provides the audit ability.

Abstract: Two-layered fractional order fuzzy logic controller (TL-FOFLC) is implemented for robotic manipulator.The optimal controller parameters are obtained with cuckoo search algorithm.Robustness analysis of proposed scheme is done with its integer order design, conventional FLC and PID controllers.The proposed scheme outperforms its integer order design, conventional FLC and PID controller. The robotic manipulators are highly coupled and nonlinear systems wherein the time-varying parameters and uncertainties adversely affect the characteristics and response of these systems. Hence, these systems require an effective and robust controller to handle such complexities which is a difficult challenge for control engineers. This paper presents two-layered fractional order fuzzy logic controller (TL-FOFLC) scheme for a two-link planar rigid robotic manipulator with payload for trajectory tracking task. For the optimal design, the controller parameters of the proposed scheme are obtained with potential meta-heuristic technique named as cuckoo search algorithm (CSA). In order to ensure effectiveness, the performance of proposed TL-FOFLC is compared with that of its integer order design approach, i.e., two-layered FLC (TL-FLC), single-layered FLC (SL-FLC), and the conventional proportional-integral-derivative (PID) controllers. Further, the robustness testing is carried out for parameter variations and external disturbance rejection.

Abstract: Multi-BAM-FUZ scheme, achieves multiple watermarking systems by embedding the BAM weight matrix.The adaptive nature of α computes using Fuzzy for every frame improves imperceptibility.This gives the NCC value of 1.00 and BCR value of 0.99, which is suitable for the content sensitive applications.In addition to fidelity and robustness, this also achieves a higher payload capacity of 2000 images. An efficient reversible adaptive video watermarking scheme for multiple watermarks based on Bi-directional Associative Memory (BAM) Neural Networks and Fuzzy Inference System namely, Multi-BAM-FUZ scheme is proposed in this paper. The main goal of this paper is to design a robust video watermarking system which facilitates secure video transmission over a communication channel by maintaining a trade-off among imperceptibility, robustness and watermark capacity or payload. The BAM neural network supports creation of weight matrix (formed out of multiple images) and this matrix is embedded into the DWT uncorrelated mid frequency coefficients of all the components (Y, Cb, Cr) of every frames of the video with varying embedding strength 'α'. This adaptive embedding strength is generated using the Fuzzy Inference System which takes HVS characteristics such as luminance, texture and edge of each frame as an input in the DWT transform. The simulations performed on various test videos demonstrate that the proposed Multi-BAM-FUZ not only outperforms other existing methods with respect to various video degradation processes, but also maintains a satisfactory image quality, robustness and payload. It is noted that, the implementation of the novel adaptive process enhances the visual quality of about 60.97dB in terms of PSNR and 0.9998 in terms of SSIM, robustness of about nearly 1.0000 and 0.9999 in terms of Normalized Cross Correlation (NCC) value and Bit Correction Rate (BCR) respectively against various attacks. Moreover, the proposed scheme facilitates high level of payload without affecting the imperceptibility and robustness level.

Abstract: With the prosperity of network applications, traffic classification serves as a crucial role in network management and malicious attack detection. The widely used encryption transmission protocols, such as the Secure Socket Layer/Transport Layer Security (SSL/TLS) protocols, leads to the failure of traditional payload-based classification methods. Existing methods for encrypted traffic classification suffer from low accuracy. In this paper, we propose a certificate-aware encrypted traffic classification method based on the Second-Order Markov Chain. We start by exploring reasons why existing methods not perform well, and make a novel observation that certificate packet length in SSL/TLS sessions contributes to application discrimination. To increase the diversity of application fingerprints, we develop a new model by incorporating the certificate packet length clustering into the Second-Order homogeneous Markov chains. Extensive evaluation results show that the proposed method lead to a 30% improvement on average compared with the state-of-the-art method, in terms of classification accuracy.

Abstract: Methods and apparatus for channel state information sounding and feedback are provided. In an aspects, a first message is transmitted to one or more wireless communication devices requesting channel state information. In accordance with this aspects, the first message comprises a header and a payload, the header comprising a plurality of fields of a first field type which are useable to determine the channel state information, and the payload comprising parameters for estimating the channel state information. In certain aspects, the channel state information parameters are also provided in the header of the first message. In various aspects a second message comprising the channel state information is received from the one or more wireless communication devices. In one aspect, the first message is a physical layer convergence protocol data unit (PPDU), and the first field type is a long training field (LTF).

Abstract: In wireless communications, an access point may send a trigger frame to multiple stations The trigger frame's payload may include a first content and a second content, where the first content is associated with a legacy signal field of an uplink frame, and the second content is associated with a non-legacy signal field of the uplink frame In response to the trigger frame, one or more stations may generate the uplink frame(s) based on the trigger frame and transmit the uplink frame(s) to the access point The uplink frame(s) may include a legacy signal field and a non-legacy signal field The legacy field may include a length of the uplink frame(s) that is based on the first content The non-legacy signal field may include a remaining transmission opportunity (TXOP) duration that is generated based on the second content Other methods, apparatus, and computer-readable media are also disclosed

Abstract: To suppress the co-channel interference in a multi-cell multi-user multiple-input-multiple-output downlink cellular network, a novel interference alignment transceiver beam-forming design along with a low complexity iterative coordinated beam-forming scheme is introduced. While the latter combats the intra-cell interference, the former is utilized to mitigate the inter-cell interference. The proposed schemes consider the codebook-based feedback, which is adopted in the LTE/LTE-advanced systems. Optimal downlink user-specific and cell-specific beam-forming matrices are characterized to maximize the lower bound of expected signal-to-leakage-plus-noise ratio and to minimize the residual inter-cell interference, respectively. Moreover, closed-form expressions for these beam-forming matrices under limited channel state information feedback and in the presence of the quantization error are identified. Simulations are conducted to investigate the performance of the proposed strategy. The results indicate that our scheme can significantly improve the average spectral-efficiency of the underlying network when compared with existing ones where the quantization error is neglected. Furthermore, for a fixed payload size of the codebook, unlike zero-forcing beam-forming in which the sum throughput is bounded as the signal-to-noise ratio (SNR) increases, in our scheme, the performance gap between rank 2 feedback and perfect feedback remains approximately constant as SNR increases.

Abstract: Aiming to embed large amount of data while minimize the sum of costs of all changed pixels, a novel high capacity data hiding scheme based on (7, 4) Hamming code is realized by a family of algorithms. Firstly, n (n = 1, 2, 3) cover pixels are assigned to one set according to the payload. Then, 128 binary strings of length seven are divided into eight sets according to the syndrome of every binary string. Binary strings that share the same syndrome are classified into one set. Finally, a binary string in a certain set determined by the data to be embedded is chosen to modify some of the least significant bits of the n cover pixels. The experimental results demonstrate that the image quality of the proposed method with high embedding payload is superior to those of the related schemes.

Abstract: Since there is good potential for practical applications such as encrypted image authentication, content owner identification and privacy protection, reversible data hiding in encrypted image (RDHEI) has attracted increasing attention in recent years. In this paper, we propose and evaluate a new separable RDHEI framework. Additional data can be embedded into a cipher image previously encrypted using Josephus traversal and a stream cipher. A block histogram shifting (BHS) approach using self-hidden peak pixels is adopted to perform reversible data embedding. Depending on the keys held, legal receivers can extract only the embedded data with the data hiding key, or, they can decrypt an image very similar to the original with the decryption key. They can extract both the embedded data and recover the original image error-free if both keys are available. The results demonstrate that higher embedding payload, better quality of decrypted-marked image and error-free image recovery are achieved.

Abstract: This memo defines Object Security of CoAP (OSCOAP), a method for application layer protection of message exchanges with the Constrained Application Protocol (CoAP), using the CBOR Object Signing and Encryption (COSE) format. OSCOAP provides end-to-end encryption, integrity and replay protection to CoAP payload, options, and header fields, as well as a secure binding between CoAP request and response messages. The use of OSCOAP is signaled with the CoAP option Object- Security, also defined in this memo.

Abstract: This book introduces fundamentals and trade-offs of data de-duplication techniques. It describes novel emerging de-duplication techniques that remove duplicate data both in storage and network in an efficient and effective manner. It explains places where duplicate data are originated, and provides solutions that remove the duplicate data. It classifies existing de-duplication techniques depending on size of unit data to be compared, the place of de-duplication, and the time of de-duplication. Chapter 3 considers redundancies in email servers and a de-duplication technique to increase reduction performance with low overhead by switching chunk-based de-duplication and file-based de-duplication. Chapter 4 develops a de-duplication technique applied for cloud-storage service where unit data to be compared are not physical-format but logical structured-format, reducing processing time efficiently. Chapter 5 displays a network de-duplication where redundant data packets sent by clients are encoded (shrunk to small-sized payload) and decoded (restored to original size payload) in routers or switches on the way to remote servers through network. Chapter 6 introduces a mobile de-duplication technique with image (JPEG) or video (MPEG) considering performance and overhead of encryption algorithm for security on mobile device.

Abstract: Data hiding schemes in the compressed domain have attracted more attention since the compressed image format is one of the most frequently transmitted formats over the Internet. Specifically, among various compression algorithms, Absolute Moment Block Truncation Coding (AMBTC) is a good choice due to its extremely low complexity and acceptable distortion. In this study, we propose a novel steganography using matrix embedding with Hamming code to insert secret message into AMBTC compressed bit-stream. Experimental results demonstrate that our scheme outperforms the other four existing BTC-based data hiding approaches in terms of embedding capacity, bit rate, and hiding efficiency.

Abstract: Telemedicine is a rapidly developing application of clinical medicine where medical information is transferred through the internet and other networks for the purpose of consulting, and remote medical procedures or examinations. This paper presents a novel neural network inspired watermarking technique, to enhance the authentication of the transmitted sensitive medical images over telemedicine network. In order to examine the medical images, the multiple scan images of same type or different types can be considered as watermarks and the same are trained using Bidirectional Associative Memory (BAM) neural network. The resultant weight matrix is embedded in the less correlated Principal Component Analysis (PCA) components of the wavelet coefficients of the cover video frames using additive embedding type of watermark. At the receiver end, the same BAM neural network is used with the randomly generated target matrix and the extracted weight matrix as input. As a result of this, the input matrix will be obtained. From the input matrix, the physician can extract their own information or scan images using their private or secret key. The proposed watermarking technique is validated with the existing systems in terms of imperceptibility, robustness and watermark capacity using the metrics such as Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), Normalized Cross Correlation (NCC), Bit Correction Rate (BCR), Detection rate, Receiver Operating Characteristics (ROC) and payload. The performance of the proposed system is evaluated by introducing various notable image processing attacks, geometrical attacks and video processing attacks on watermarked video. The experimental results demonstrate that the proposed technique has good perceptual quality of 50.6292 dB in terms of PSNR value, robustness of about nearly 1.0000 in terms of NCC value and payload of 1000 watermarks.

Abstract: Precise location services are seen as key enablers to future Intelligent Transport Systems (ITSs). Relying on Vehicle-to-Vehicle (V2V) communication links, one promising solution consists in performing distributed Cooperative Positioning (CP). More specifically, Cooperative Awareness Message (CAM) broadcasts from neighboring vehicles (seen as “virtual anchors”) are used to exchange positional information and to measure V2V radiolocation metrics such as the Received Signal Strength Indicator (RSSI). For the sake of fusing these nonlinear hybrid data, Particle Filters (PFs) represent the required positional information by a set of particles with associated weights. However, in a jointly cooperative and distributed context, the transmission of explicit particle clouds (required by receiving neighbors to update their own location estimates) is hardly affordable under limited V2V channel capacity with typical numbers of particles. In this paper we thus combine and compare several solutions in terms of message representation and adaptive transmission policy so as to reduce simultaneously CAM overhead, channel congestion and computational complexity. Proposals are made at both signal processing level (parametric density approximation) and protocol level (jointly adaptive transmission payload, power and rate), showing no impact on channel load in congested scenarios and negligible CP accuracy degradation in comparison with standard CAM transmission at critical rates.

Abstract: Intrusion detection system, IDS, traditionally inspects the payload information of packets. This approach is not valid in encrypted traffic as the payload information is not available. There are two approaches, with different detection capabilities, to overcome the challenges of encryption: traffic decryption or traffic analysis. This paper presents a comprehensive survey of the research related to the IDSs in encrypted traffic. The focus is on traffic analysis, which does not need traffic decryption. One of the major limitations of the surveyed researches is that most of them are concentrating in detecting the same limited type of attacks, such as brute force or scanning attacks. Both the security enhancements to be derived from using the IDS and the security challenges introduced by the encrypted traffic are discussed. By categorizing the existing work, a set of conclusions and proposals for future research directions are presented.

Abstract: Steganography is the art of hiding user information in various file types including image, audio and video. Security of steganography lies in imperceptibility of secret information in the cover image. Human Visual System (HVS) is not able to detect the changes in low color values of an image. To the best of our knowledge, none of the available steganographic techniques have exploited this weakness of HVS. In this paper, a new LSB technique is presented which hides information in the cover image taking into account the pixel value of color or grey level of every pixel. Our experiments show that the proposed technique has a high payload and low perceptibility of secret information hidden in the cover image as compared to the existing Least Significant Bit (LSB) based algorithms. We have used MATLAB for the implementation of proposed

Abstract: In this research paper, an adaptive difference expansion-based reversible data hiding technique with the capability of embedding either three bits or two bits or one bit for each pixel and which can deal with color image is presented. To embed and extract data, the proposed technique has some salient features such as its capability to control the embedding capacity by using three global embedding parameters. These parameters are computed using the statistics of the embedded pixel surrounding pixels. Also, the data embedding steps in the proposed scheme can be reversed to completely retrieve the cover image free from any deformation. Furthermore, in the proposed technique, no reference images or memorization of the embedded pixel positions are needed in the data extraction process. A course of experiments is conducted, and the results demonstrated that the proposed technique outperforms other similar techniques in terms of payload capacity and PSNR.

Abstract: In this paper, a compressed domain video watermarking scheme is proposed which embeds the watermark in the homogeneous moving object within a shot of video sequence to resist geometric attacks such as rotation, scaling etc. Intuitively, object based watermarking results low payload and has the least impact on visual quality since the object area is generally small and highly textured. The proposed work has two main contributions, firstly, an existing compressed domain motion coherent block detection algorithm [7] is extended to detect the moving objects within a video shot and secondly, a watermarking scheme has been proposed by embedding within the moving objects to resist RST attacks. A comprehensive set of experiments has been carried out to justify the applicability of the proposed scheme over the existing literature.

Abstract: A system, apparatuses and methods are provided to download and process data and other content streamed over a wide area network using one or more dynamically fetched, material specific, data handlers (e.g., download assistants). A download assistant fetches a data stream from a remote location and processes the streamed data iteratively using buffers and multi-threaded processes through the decoder (e.g., codec), allowing source material-specific processing of the data as it is streamed from one or more download sources as well as content-indifferent and platform-indifferent decoding. To minimize versioning issues, payload construction for secure delivery is simplified to packing and encrypting a directory tree containing any number of files or other digital media into an archive and, when needed, dividing a payload into multiple files or archives with a descriptor that lists the archives.

Abstract: In this paper, we present a joint delay-efficient channel assignment and packet scheduling scheme for a heterogeneous M2M uplink system. The uplink sensor traffic is aggregated at multiple M2M aggregators (MAs) and then processed at a M2M application server (AS). The system bandwidth is divided into multiple orthogonal subcarriers to be assigned to different MA-AS wireless links. We categorize the uplink traffic into multiple classes based on the maximum packet delay, arrival rate and payload size. The delay-requirements of each class are mapped onto sigmoidal utility functions. We then determine the joint subcarrier assignment and packet scheduling scheme such that it maximizes a proportionally-fair system utility metric. The centralized optimization is a mixed integer non-linear programming (MINLP) problem with high computational complexity. Therefore, we propose a two-stage distributed optimization problem that is solved independently across MAs and AS. We first determine the delay-efficient subcarrier assignment and then determine the corresponding delay-efficient packet scheduler. Using Monte-Carlo simulations, we numerically show that distributed optimization does not result in any loss in delay-performance and also outperforms other state-of-the-art schemes.

Abstract: In this paper, the constrained problem is investigated for both flexible string model and Euler–Bernoulli beam model with the tip payload, based on an infinite dimensional generalisation of a distributed control method. The control objectives are to develop the control law so that the motion of flexible mechanical systems can track a desired reference signal, and ensure that the string or beam remain in a constrained space. We prove that, with the proposed control, the tracking error is exponentially stable without violation of the constraint. The proof of convergence is based on an Integral-Barrier Lyapunov Function (IBLF), and extensive simulations are provided to illustrate the performance of the control system.