The paper is related to system and method for protection of an automated control system (ACS) against un-authorized devices connected to the ACS via wired or wireless channels that substantially obviates the disadvantages of the related art. The protection system monitors the signals spreading in the network analyzing the performance of the network for malicious code or hidden connections of attacker. The system is developed specifically for this purpose and it can protect the industrial control systems more effectively than standard anti-virus programs. Specific anti-virus software installed on a central server of the automated control system protects it from software-based attacks both from internal and external offenders. The system comprises a plurality of bus protection devices of different types, including any of a twisted-pair protection device, a power lines protection device, On-Board Diagnostics signal protocol protection device, and a wireless protection device.

Wireless Sensors Networks are extremely densely populated and have to handle large bursts of data during emergency or high activity periods giving rise to congestion which may disrupt normal operation. Our paper proposes a new congestion control protocol for balanced distribution of traffic among the different paths existing between the Source node and the Sink node in accordance to the different route trust values. This probabilistic method of data transmission through the various alternate routes can be appropriately modeled with the help of Genetic Algorithms. Our protocol is mainly targeted in selecting the reliable or trustworthy routes more frequently than the unreliable ones. In addition, it also prevents concentration of the entire data traffic through a single route eliminating any possible occurrence of bottleneck. The merits of our protocol in comparison to the presently existing routing protocols are justified through the simulation results obtained which show improvements in both the percentage ratio of successful transmission of data packets to the total number of data packets sent and the overall network lifetime.

Recently, stratospheric platform communications system (SPs) has gained great interest due to its superior performance compared to conventional communications systems. This paper addresses one of the major performance keys in SPs which is the cellular design based on adaptive concentric circular arrays (CCA). The proposed design technique aims to provide circular cells at any elevation angle to overcome the cell flattening and broadening which result in ellipsoidal cell shape. The cell footprint is controlled by adjusting the beamwidths which can be established by sectorizing the CCA and tapering the current amplitudes of the effective sectors by Hamming function while the others are muted and the resulted array is called Sectorized Hamming tapered CCA (SHTCCA). In this array, each sector has an angular width of 90o and some and two opposite sectors are fully fed while the others has less number of quarter-circular arrays. The tapering of the active sectors results in lower sidelobe levels which is a paramount improvement for the cellular systems. In addition, the SHTCCA is analyzed and optimized to provide the desired beamwidths at any elevation angle that are needed to design circular cell footprint.

In this paper, we propose Petri net models for processing elements. The processing elements include: a general-purpose processor (GPP), a reconfigurable element (RE), and a hybrid element (combining a GPP with an RE). The models consist of many transitions and places. The model and associated analysis methods provide a promising tool for modeling and performance evaluation of reconfigurable processors. The model is demonstrated by considering a simple example. This paper describes the development of a reconfigurable processor; the developed system is based on the Petri net concept. Petri nets are becoming suitable as a formal model for hardware system design. Designers can use Petri net as a modeling language to perform high level analysis of complex processors designs processing chips. The simulation does with PIPEv4.1 simulator. The simulation results show that Petri net state spaces are bounded and safe and have not deadlock and the average of number tokens in first token is 0.9901 seconds. In these models, there are only 5% errors; also the analysis time in these models is 0.016 seconds.

This work presents a mobile location management technique based on the clustering. This technique can be implemented on next generation mobile networks by exploiting the data available on the users (age, function, address, workplace… etc), existing infrastructure (roads, location of base stations… etc) and the users' displacements history.
The simulations are carried out using a realistic model of movements. The results show that our strategy requires a minimum number of location messages compared to the static and dynamic location management techniques.

A Mobile Ad-hoc Network (MANET) is a collection of multi-hop wireless mobile nodes among which the communication is carried out without any centralized control or fixed infrastructure. MANET is a self-organized, self-configurable network having no infrastructure, and in which the mobile nodes move arbitrarily. The wireless link in the network are highly error prone and can go down frequently due to the mobility of nodes, interference and less infrastructure. Hence, because of the highly dynamic environment routing in MANET is a very difficult task. Over the last decade various routing protocols have been proposed for the mobile ad-hoc network and the most important among all of them are AODV, DSR, DSDV and CBRP. This research paper gives the overview of these routing protocols as well as the characteristics and functionality of these routing protocols along with their pros and cons and then make their comparative analysis in order to measure the performance of the network. The main objective of this paper is to compare the performance of all the four routing protocols and then to make the observations about how the performance of these routing protocols can be improved. Performance of these routing protocols are compared on the basis of various parameters such as throughput, delay and packet delivery ratio.

The RSA cryptosystem, invented by Ron Rivest, Adi Shamir and Len Adleman was first publicized in the August 1977 issue of Scientific American. The security level of this algorithm very much depends on two large prime numbers. To check the primality of large number in personal computer is huge time consuming using the best known trial division algorithm. The time complexity for primality testing has been reduced using the representation of divisors in the form of 6n±1. According to the fundamental theorem of Arithmetic, every number has unique factorization. So to check primality, it is sufficient to check if the number is divisible by any prime below the square root of the number. The set of divisors obtained by 6n±1 form representation contains many composites. These composite numbers have been reduced by 30k approach. In this paper, the number of composites has been further reduced using 210k approach. A performance analysis in time complexity has been given between 210k approach and other prior applied methods. It has been observed that the time complexity for primality testing has been reduced using 210k approach.

In defence and military scenarios, Unmanned Aerial Vehicle (UAV) is used for surveillance missions. UAV's transmit live video to the base station. Temporal attacks may be carried out by the intruder during video transmission. These temporal attacks can be used to add/delete objects, individuals, etc. in the live transmission feed. This can cause the video information to misrepresent facts of the UAV transmission. Hence, it is needed to identify the fake video from the real ones. Compression techniques like MPEG, H.263, etc. are popularly used to compress videos. Attacker can either add/delete frames from videos to introduce/remove objects, individuals etc. from video. In order to perform attack on the video, the attacker has to uncompress the video and perform addition/deletion of frames. Once the attack is done, the attacker needs to recompress the frames to a video. Wang and Farid et. al. [1] proposed a method based on double compression technique to detect temporal fingerprints left in the video caused due to frame addition/deletion. Based on double MPEG compression, here we propose a video forensic technique using machine learning techniques to detect video forgery. In order to generate a unique feature vector to identify forged video, we analysed the effect of attacks on Prediction Error Sequence (PES) in various domains like Discrete Cosine Transform (DCT), Discrete Fourier Transform (DFT), Discrete Wavelet Transform (DWT) domain etc. A new PES feature γ is defined and extracted from DWT domain, which is proven robust training parameter for both Support Vector Machine (SVM) and ensemble based classifier. The trained SVM was tested for unknown videos to find video forgery. Experimental results show that our proposed video forensic is robust and efficient in detecting video forgery without any human intervention. Further the proposed system is simpler in design and implementation and also scalable for testing large number of videos.