cyber security UDP Flood Attack UDP Flood Attack is a type of Denial of Service attack in which a hacker floods the random ports on the victim host with UDP packets. In this attack, the hacker spoofs the IP Address of the packets, to make sure that the returning ICMP packets don’t reach back to the hacker.
Machine Learning (ML) Convolutional Neural Networks (CNN) Convolutional Neural Network (CNN) is an neural network which extracts or identifies a feature in a particular image and is the basis of GoogleNet and VGG19 and used for object detection and classification. CNN has five basic components Convolution, ReLU, Pooling, Flattening and Full connection.
Machine Learning (ML) Understand basic TensorFlow programming concepts We understand basic TensorFlow programming concepts using a code to add two numbers in TensorFlow. We created placeholders like tf.placeholder, operations like tf.constant and tf.add, sessions using tf.session and configuration using tf.configProto
Machine Learning (ML) Training vs Inference Training and Inference are two major processes of Machine Learning and is deeply connected. Training is the process by which we generate various parameters such as weights and biases which are used in a particular model. Inference is the process of using the trained model to do a particular task
cyber security DNS Amplification Attack DNS (Domain Name System) Amplification is a form of reflection based DDoS attack, in which a hacker spoofs the look-up requests to spoof the DNS servers to hide the source of an exploit and also to direct the response to the target. The attack exploits the disparity in the bandwidth consumption
cyber security IP Spoofing Attack IP (Internet Protocol) Spoofing is a form of cyber attack in which hacker crafts the IP packets which are used to carry out the DDoS attacks as well as MitM attack. In this attack, the fake crafted IP packets are used to impersonate another system or is used to hide the identity of the hacker.
cyber security MAC Flooding Attack MAC (Media Access Control) Flooding is a type of cyber attack done in a network to compromise the security of the network switches. In this attack the network is flooded with the fake MAC addresses. The hacker uses this attack to steal sensitive data that is being transferred in the network.
cyber security Ping Of Death Attack Ping of Death (PoD) Attack is a form of DDoS attack, which is used for disrupting the victim network by sending the packets larger then the max size allowed using some arbitrary commands. The attack degrades the targeted system or even freeze the system.
Machine Learning (ML) Hidden Markov Model Hidden Markov Model is a stochastic model describing a sequence of possible events in which the probability of each event depends on the state attained in the previous event. Markov model can be used in real life forecasting problems. Simple Markov model cannot be used for customer level predictions
Machine Learning (ML) Markov Chain Markov chain is a stochastic model describing a sequence of possible events in which the probability of each event depends only on the state attained in the previous event. It refers to the sequence of random variables such a process moves through, with the Markov property of serial dependence
cyber security Smurf Attack Smurf Attack is a type of DDoS Attack, which floods the system with the spoofed ping messages. The attack has an amplification vector that increases the damage by exploiting the characteristics of the broadcast network. The attack swamps the internet with the replies to ICMP echo requests.
cyber security BlueBugging Attack Bluebugging is a type of cyber attack done on the Bluetooth enabled devices. The attack allows the hacker to access the cell commands and infiltrate the phone calls, read and send SMS. This allows any hacker to modify the contact list, connect to the internet and eavesdrop on any phone conversation
Machine Learning (ML) Deep Learning on 2-Dimensional Images Applying deep learning concepts on images has proved to be one of the important work which has resulted in early detection of diseases resulting in saving millions of life to monitoring activities on the entire Earth We take a look at medical images, Satellite Images and the various Python libraries
Machine Learning (ML) Deep Learning for Medical Imaging and Diagnosis One of the major medical challenges that we face today is the early detection of diseases so that the proper threatment can be applied. This can be solved by applying machine learning to analyse MRI scan, CT Scan, Xray Scans, InfraRed Images, Arthoscopy, UV radiation, Scintigraphy and Ultrasound
Data Structures Trie data structure A trie (digital tree, radix tree, prefix tree) is a kind of an ordered search tree data structure that is used to store a dynamic set or associative array where the keys are usually strings. Worst case search time complexity is Θ(key_length) and trie is widely used in real life applications
Machine Learning (ML) Recurrent Neural Networks (RNN) Recurrent Neural Network is one of the widely used algorithms of Deep Learning mainly due to is unique Design. It is the only algorithm that remembers the most recent Input and makes use of memory element. It is used by Apple Siri and Google Voice Search. RNN is used for sequential data.
Algorithms Aho Corasick Algorithm Aho Corasick algorithm is a string algorithm to find or search occurrences of k number of Patterns: P1 ,P2 .... Pk in a string text T. It is a modification over the KMP algorithm
Data Structures B+ Tree : Search, Insert and Delete operations A B+ tree is an N-ary tree with a variable often large number of children per node. A B+ tree consists of a root, internal nodes and leaves. The root may be either a leaf or a node with two or more children. It can be viewed as a B-tree in which each node contains only keys with an additional level
Machine Learning (ML) Residual Network (ResNet) ResNet makes it possible to train up to hundreds or even thousands of layers and still achieves compelling performance. Thanks to this technique they were able to train a network with 152 layers while still having lower complexity than VGGNet. It achieves a top-5 error rate of 3.57%
Machine Learning (ML) GoogleNet / InceptionNet The winner of the ILSVRC 2014 competition was GoogleNet from Google. It achieved a top-5 error rate of 6.67%. GoogleNet has 22 layer, and almost 12x less parameters (So faster and less then Alexnet and much more accurate). Their idea was to make a model that also could be used on a smart-phone
Machine Learning (ML) Architecture of AlexNet and its current use Alexnet is a Deep Convolutional Neural Network (CNN) for image classification that won the ILSVRC-2012 competition and achieved a winning top-5 test error rate of 15.3%, compared to 26.2% achieved by the second-best entry. We see the architecture and compare it with GoogleNet and ResNet
cyber security Distributed Denial Of Service Attack (DDoS) Distributed Denial Of Service (DDoS) is a form of cyber attack which is done to make target online services unavailable to the users. The attack disrupts the normal traffic of a targeted server, network or service by overwhelming the target or its surrounding infrastructure
cyber security Man In The Middle Attack (MitM) Man In The Middle (MitM) is a type of cyber attack in which a hacker intercepts the communication between two people either to eavesdrop or to impersonate one of the person. The aim of the attack is to steal financial details such as account details, credit card numbers or sensitive details
cyber security Denial Of Service Attack Denial Of Service Attack is a form of cyber attack basically used by hackers to prevent the victims from accessing any legitimate service. This hacker floods the web servers with excessive traffic in order to succeed in this attack. The attack does not result in theft or loss of data
cyber security SQL Injection Attack SQL(Structured Query Language) Attack is a cyber attack used for the manipulation of the backend database through the malicious SQL Query. The attack allows a hacker to cause repudiation issues and spoof the identity. The attack allows the complete exposure of the database
