This paper considers two dimensional valence-arousal model. Pictorial stimuli of International Affective Picture Systems were chosen for emotion elicitation. Physiological signals like, Galvanic Skin Response, Heart Rate, Respiration Rate and Temperature measured accessing emotional responses. The experimental procedure uses non-invasive sensors signal collection. A group healthy volunteers was shown four types categorized as High Valence Arousal, Low Arousal around thirty minutes Linear...

Emotions and affect are universal means of expressing the physiological state an individual. Most our daily interactions with other individuals involve emotions as integral part. It has become highly prominent in technological research, new technologies related to human-machine interaction or medical applications developed. Detecting analyzing have quite important area research. In this paper, we took effort find effect different on signals. We used International Affective Picture System...

Searchable Symmetric Encryption (SSE) supports efficient yet secure query processing over outsourced symmetrically encrypted databases without the need for decryption. A longstanding open question has been following: can we design a fast, scalable, linear storage and low-leakage SSE scheme that efficiently arbitrary Boolean queries databases? In this paper, present design, analysis prototype implementation of first conjunctive, disjunctive more general (in both conjunctive normal forms)...

Emotion Recognition always has been one of the key areas in human machine interaction, learning or affective computing. Two dimensional valence arousal model used here. In this paper, we present how simple emotion recognition can be done by measuring nine basic non-invasive Biological markers physiological signals including BR [BReathing], ECG [ElectroCardioGram], EMG [ElectroMyoGram], GSR [Galvanic Skin Response], HR [Heart Rate], PR [Pulse RR [Respiration and ST [Skin Temperature] on...

Neural Networks (NN) have recently emerged as backbone of several sensitive applications like automobile, medical image, security, etc. NNs inherently offer Partial Fault Tolerance (PFT) in their architecture; however, the biased PFT can lead to severe consequences cryptography and security critical scenarios. In this paper, we propose a revised implementation which enhances property NN significantly with detailed mathematical analysis. We evaluated performance considering both software FPGA...

Fault injection-based cryptanalysis is one of the most powerful practical threats to modern cryptographic primitives. Popular countermeasures such fault-based attacks generally use some form redundant computation detect and react/correct injected faults. However, are shown be vulnerable selective fault injections. In this article, we aim develop a primitive that tolerant by its construction does not require compute same value multiple times. We utilize effectiveness Neural Networks (NNs),...

Pairing cryptosystems are extremely powerful mathematical tools for developing cryptographic protocols that can provide end-to-end security applications like Internet-of-Things (IoT), cloud services and cyber-physical systems (CPS). However, these require the implementations to be light-weight but still real-time, with additional feature of being flexible. The flexibility come from different choices underlying algorithms along suitable parameter choices. A software implementation offers...

Searchable symmetric encryption (SSE) allows a client to outsource the storage of her data an (untrusted) server in private manner, while maintaining ability selectively search over it. A key feature all existing SSE schemes is tradeoff between security (in terms information leakage server) and efficiency operational overhead on sides). The premise this work that typically offer scope for massively parallel implementations with improved without compromising security. Based idea, we propose...

In this paper, we present the first Hardware (HW) / Software (SW) co-design based generic discrete Gaussian sampler architecture on Xilinx Zynq platform. The area optimized and secure can produce a distribution an arbitrary standard deviation center given as input. We use multi-level logic optimization Knuth-Yao algorithm's Discrete Distribution Generating (DDG) tree travel-based Boolean mapping of random bits samples instead previous two-level to reduce resource utilization. This method...

FPGAs (Field Programmable Gate arrays) have gained massive popularity today as accelerators for a variety of workloads, including big data analytics, and parallel distributed computing. This has fueled the study mechanisms to provision among multiple tenants general purpose computing resources on cloud. Such offer new challenges, such ensuring IP protection bitstream confidentiality mutually distrusting clients sharing same FPGA. A direct adoption existing techniques from single tenancy...

Searchable symmetric encryption (SSE) is a special class of schemes for computing directly over encrypted data. SSE aims to be significantly more efficient as compared other solutions, such fully homomorphic (FHE), while leaking only minimal information the adversary. particularly and scalable Boolean queries large relational databases outsourced third-party cloud service providers. However, practical implementations often suffer from performance bottlenecks due randomised memory accesses...

Searchable symmetric encryption (SSE) aims to support efficient query-execution directly over encrypted databases. Practical implementations of SSE suffer from performance bottlenecks due randomised memory accesses and computation-intensive cryptographic operations. We propose CAMISE – a fully associative memory-integrated framework for designing systems with fast query processing large show novel usage custom-designed Content Addressable Memory (CAM) minimise storage-access latencies during...