College of Engineering, Pune

About: College of Engineering, Pune is a based out in . It is known for research contribution in the topics: Sliding mode control & Control theory. The organization has 4264 authors who have published 3492 publications receiving 19371 citations. The organization is also known as: COEP.

Intrusion Detection System using Self Organizing Maps

Abstract: With the rapid expansion of computer usage and computer network the security of the computer system has became very important. Every day new kind of attacks are being faced by industries. Many methods have been proposed for the development of intrusion detection system using artificial intelligence technique. In this paper we will have a look at an algorithm based on neural networks that are suitable for Intrusion Detection Systems (IDS) [1] [2]. The name of this algorithm is “Self Organizing Maps” (SOM). Neural networks method is a promising technique which has been used in many classification problems. The neural network component will implement the neural approach, which is based on the assumption that each user is unique and leaves a unique footprint on a computer system when using it. If a user's footprint does not match his/her reference footprint based on normal system activities, the system administrator or security officer can be alerted to a possible security breach. At the end of the paper we will figure out the advantages and disadvantages of Self Organizing Maps and explain how it is useful for building an Intrusion Detection System.

Secure file storage in cloud computing using hybrid cryptography algorithm

Abstract: Now a day's cloud computing is used in many areas like industry, military colleges etc to storing huge amount of data. We can retrieve data from cloud on request of user. To store data on cloud we have to face many issues. To provide the solution to these issues there are n number of ways. Cryptography and steganography techniques are more popular now a day's for data security. Use of a single algorithm is not effective for high level security to data in cloud computing. In this paper we have introduced new security mechanism using symmetric key cryptography algorithm and steganography. In this proposed system AES, blowfish, RC6 and BRA algorithms are used to provide block wise security to data. All algorithm key size is 128 bit. LSB steganography technique is introduced for key information security. Key information contains which part of file is encrypted using by which algorithm and key. File is splited into eight parts. Each and every part of file is encrypted using different algorithm. All parts of file are encrypted simultaneously with the help of multithreading technique. Data encryption Keys are inserted into cover image using LSB technique. Stego image is send to valid receiver using email. For file decryption purpose reverse process of encryption is applied.

Influence of Cryoprocessing on Mechanism of Carbide Development in Cobalt-Bearing High-Speed Steel (M35)

Abstract: Cryogenic treatment has been used commonly to high-speed tool steels to enhance the wear resistance of the materials In the current research study, specimens of complex alloyed high-speed tool steel (M35) were hardened at 1473 K (1200 °C), triple tempered at 673 K (400 °C) and then cryogenically treated at 88 K (−185 °C) for varying lengths of period starting from 16 to 48 hours of cryosoaking followed by soft tempering at 373 K (100 °C) These treated specimens were studied as a function of cryosoaking period for their electrical resistivity, residual compressive stress, and its correlation with carbide density was established TEM analysis indicated carbide size 0156 to 1 μm, which confirms that the cryogenic treatment enhances the precipitation of finer carbides Lower residual stresses in the higher carbide density regimes identified in 2D contour map were explained by the stress relaxation in the matrix through precipitation of incoherent carbides

Texture Based Palmprint Identification Using DCT Features

Abstract: In the palmprint recognition application utilizing more information other than principle lines or minutiae is much helpful. In this paper we proposed Discrete Cosine Transform (DCT) based feature vector for palmprint representation and matching and compared with DFT and Wavelet transform. Here the central part of the palmprint image of size 128x128 is resized to the size of 64x64 and divided into four non overlapping sub-images. The transform is applied on each sub-image directly without any preprocessing. By dividing the transformed sub-image into nine blocks, standard deviation is calculated for each block and such in total 36 (9x4=36) standard deviations will form the feature vector. This feature vector is used in matching stage. Total 10 images per person are taken from standard database available. Training set is prepared with the help of k images where k varies from 1 to 8. Results are checked against remaining images image in identification mode. Results are represented in terms of Genuine acceptance rate(%). In identification mode 97.5% recognition rate is obtained. The work is preliminary but recognition rate is promising and without any pre-processing.