Biblio

Intelligent software applications are becoming ubiquitous and pervasive affecting various aspects of our lives and livelihoods. At the same time, the risks to which these systems expose the organizations and end users are growing dramatically. Trustworthiness of software applications is becoming a paramount necessity. Trust is to be regarded as a first-class citizen in the total product life cycle and should be addressed across all stages of software development. Trust can be looked at from two facets: one at an algorithmic level (e.g., bias-free, discrimination-aware, explainable and interpretable techniques) and the other at a process level by making development processes more transparent, auditable, and adhering to regulations and best practices. In this paper, we address the latter and propose a blockchain enabled governance framework for building trustworthy software. Our framework supports the recording, monitoring, and analysis of various activities throughout the application development life cycle thereby bringing in transparency and auditability. It facilitates the specification of regulations and best practices and verifies for its adherence raising alerts of non-compliance and prescribes remedial measures.

In the current generation, road accidents and security problems increase dramatically worldwide in our day to day life. In order to overcome this, Vehicular Ad-hoc Network (VANETs) is considered as a key element of future Intelligent Transportation Systems (ITS). With the advancement in vehicular communications, the attacks have also increased, and such architecture is still exposed to many weaknesses which led to numerous security threats that must be addressed before VANET technology is practically and safely adopted. Distributed Denial of Service (DDoS) attack, replay attacks and Sybil attacks are the significant security threats that affect the communication and privacy in VANET. An algorithm to detect and prevent various kinds of security attacks in VANET communication has been designed and proposed in this work. An analysis has also been done by applying four protocols on an existing scenario of real traffic simulator using OpenStreetMap and the best suitable protocol has been selected for further application. The evaluation has been done using SUMO, NS3 and Java simulation environment. Simulation results and extensive performance analysis shows that our proposed Algorithm performs well in detecting and preventing the attacks in VANET communication.

Image hash regimes have been widely used for authenticating content, recovery of images and digital forensics. In this article we propose a new algorithm for image haunting (SSL) with the most stable key points and regional features, strong against various manipulation of content conservation, including multiple combinatorial manipulations. In order to extract most stable keypoint, the proposed algorithm combines the Speed Up Robust Features (SURF) with Saliency detection. The keyboards and characteristics of the local area are then combined in a hash vector. There is also a sperate secret key that is randomly given for the hash vector to prevent an attacker from shaping the image and the new hash value. The proposed hacking algorithm shows that similar or initial images, which have been individually manipulated, combined and even multiple manipulated contents, can be visently identified by experimental result. The probability of collision between hacks of various images is almost nil. Furthermore, the key-dependent security assessment shows the proposed regime safe to allow an attacker without knowing the secret key not to forge or estimate the right havoc value.

The main technology of traditional information security is firewall, intrusion detection and anti-virus software, which is used in the first anti-outer defence, the first anti-service terminal defence terminal passive defence ideas, the complexity and complexity of these security technologies not only increase the complexity of the autonomous system, reduce the efficiency of the system, but also cannot solve the security problem of the information system, and cannot satisfy the security demand of the information system. After a significant stretch of innovative work, individuals utilize the secret word innovation, network security innovation, set forward the idea “confided in figuring” in view of the equipment security module support, Trusted processing from changing the customary protection thoughts, center around the safety efforts taken from the terminal to forestall framework assaults, from the foundation of the stage, the acknowledgment of the security of data frameworks. Believed figuring is chiefly worried about the security of the framework terminal, utilizing a progression of safety efforts to ensure the protection of clients to work on the security of independent frameworks. Its principle plan thought is implanted in a typical machine to oppose altering the equipment gadget - confided in stage module as the base of the trust, the utilization of equipment and programming innovation to join the trust of the base of trust through the trust bind level to the entire independent framework, joined with the security of information stockpiling insurance, client validation and stage respectability of the three significant safety efforts guarantee that the terminal framework security and unwavering quality, to guarantee that the terminal framework is consistently in a condition of conduct anticipated.

Human facial emotion recognition pays a variety of applications in society. The basic idea of Facial Emotion Recognition is to map the different facial emotions to a variety of emotional states. Conventional Facial Emotion Recognition consists of two processes: extracting the features and feature selection. Nowadays, in deep learning algorithms, Convolutional Neural Networks are primarily used in Facial Emotion Recognition because of their hidden feature extraction from the images. Usually, the standard Convolutional Neural Network has simple learning algorithms with finite feature extraction layers for extracting information. The drawback of the earlier approach was that they validated only the frontal view of the photos even though the image was obtained from different angles. This research work uses a deep Convolutional Neural Network along with a DenseNet-169 as a backbone network for recognizing facial emotions. The emotion Recognition dataset was used to recognize the emotions with an accuracy of 96%.

Compressive Sampling and Sparse reconstruction theory is applied to a linearly frequency modulated continuous wave hybrid lidar/radar system. The goal is to show that high resolution time of flight measurements to underwater targets can be obtained utilizing far fewer samples than dictated by Nyquist sampling theorems. Traditional mixing/down-conversion and matched filter signal processing methods are reviewed and compared to the Compressive Sampling and Sparse Reconstruction methods. Simulated evidence is provided to show the possible sampling rate reductions, and experiments are used to observe the effects that turbid underwater environments have on recovery. Results show that by using compressive sensing theory and sparse reconstruction, it is possible to achieve significant sample rate reduction while maintaining centimeter range resolution.

The Polish Power System is becoming increasingly more dependent on Information and Communication Technologies which results in its exposure to cyberattacks, including the evolved and highly sophisticated threats such as Advanced Persistent Threats or Distributed Denial of Service attacks. The most exposed components are SCADA systems in substations and Distributed Control Systems in power plants. When addressing this situation the usual cyber security technologies are prerequisite, but not sufficient. With the rapidly evolving cyber threat landscape the use of partnerships and information sharing has become critical. However due to several anonymity concerns the relevant stakeholders may become reluctant to exchange sensitive information about security incidents. In the paper a multi-agent architecture is presented for the Polish Power System which addresses the anonymity concerns.

Security of secret data has been a major issue of concern from ancient time. Steganography and cryptography are the two techniques which are used to reduce the security threat. Cryptography is an art of converting secret message in other than human readable form. Steganography is an art of hiding the existence of secret message. These techniques are required to protect the data theft over rapidly growing network. To achieve this there is a need of such a system which is very less susceptible to human visual system. In this paper a new technique is going to be introducing for data transmission over an unsecure channel. In this paper secret data is compressed first using LZW algorithm before embedding it behind any cover media. Data is compressed to reduce its size. After compression data encryption is performed to increase the security. Encryption is performed with the help of a key which make it difficult to get the secret message even if the existence of the secret message is reveled. Now the edge of secret message is detected by using canny edge detector and then embedded secret data is stored there with the help of a hash function. Proposed technique is implemented in MATLAB and key strength of this project is its huge data hiding capacity and least distortion in Stego image. This technique is applied over various images and the results show least distortion in altered image.