212 skills found · Page 8 of 8
SivarajeshA / Cache Side Channel Attack On GnuPGIn this task, I have performed the FLUSH+RELOAD attack on GnuPG cryptography Library to observe accesses to critical functions like Square (S), Module (r), and Multiply (M) function during the encryption or decryption process of the RSA algorithm. In this project, Gogo will mount a side-channel attack with a goal to leak the critical accesses of Gollu.
PriyanujBora / Black Hole Attack In MANETs With Streamlit ImplementationInteractive simulation of black hole attack detection in Mobile Ad-hoc Networks (MANETs) using novel Dolphin-Bee optimization algorithm with Streamlit visualization interface
arhcoder / Eight Queens Game♟ Eight queens game online app with backtracking algorithm to solve it. Chess board on which eight queens must be placed so that they cannot attack each other.
awais7012 / FastAPI RateLimiter⚡ FastAPI Advanced Rate Limiter is a battle-tested library providing 6 different rate limiting algorithms with support for both in-memory and Redis backends. Perfect for APIs, microservices, and any FastAPI application that needs protection from abuse, overload, or DDoS attacks.
xaslln / Brute WalletloginWalllets is a specialized tool designed for brute force attacks on cryptocurrency wallets. It utilizes advanced algorithms to attempt to crack wallet passwords, enabling access to locked assets. Ideal for security researchers and ethical hackers, BruteCryptoWallet helps identify vulnerabilities in wallet security.
manjunath5496 / Active Learning Papers"So if an algorithm is an idealized recipe, a program is the detailed set of instructions for a cooking robot preparing a month of meals for an army while under enemy attack."― Kernighan Brian W
rishabh-mondal / Evaluating Shallow And Deep Neural Networks For Network Intrusion Detection Systems Intrusion detection system (IDS) has become an essential layer in all the latest ICT system due to an urge towards cyber safety in the day-to-day world. Reasons including uncertainty in finding the types of attacks and increased the complexity of advanced cyber attacks, IDS calls for the need of integration of Deep Neural Networks (DNNs). In this paper, DNNs have been utilized to predict the attacks on Network Intrusion Detection System (N-IDS). A DNN with 0.1 rate of learning is applied and is run for 1000 number of epochs and KDDCup-’99’ dataset has been used for training and benchmarking the network. For comparison purposes, the training is done on the same dataset with several other classical machine learning algorithms and DNN of layers ranging from 1 to 5. The results were compared and concluded that a DNN of 3 layers has superior performance over all the other classical machine learning algorithms.
madison-freeman / Consensus From TrustDesigned and implemented a distributed consensus algorithm given a graph of “trust” relationships between nodes as an alternative method of resisting sybil attacks and achieving consensus. In this project, we developed a robust CompliantNode class that will work in all combinations of the graph parameters.
guptatrisha97 / Phishing URL DetectorWith the integration of Machine Learning in detecting phishing attempts, the avenue of its applications is extremely widespread. Malicious emails are a form of phishing attack, which redirects the user to visit unexpected sites or cause computer viruses to be downloaded on the user’s system. The project’s aim is to mitigate the vulnerability of such emails by using an ML algorithm to detect these URLs and notify the user of the possible danger.
Newanimalfarm1984 / DCT DIGITAL Watermark The digital watermarking of DCT algorithm based on Arnold scrambling, which utilize Matlab as a programming tool, it is programmed to achieve and developed a related research. The watermarking image is reconstructed by Arnold, and then the DCT is carried out the watermark image and the host image. The embedding of the watermark is carried out, and the host image is embedded in the watermark to obtain the carrier image. The watermark is extracted by the carrier image and the original host image, then the DCT coefficients of the carrier image are obtained and the DCT coefficients of the host image are obtained. Then, we compare the watermark image to be extracted on the carrier image and the host image. After the DCT inverse transform and Arnold anti-scrambling are carried out, the extracted watermark image. Utilizing the telescopic, rotate, add the Gaussian noise and other attacks to verify the watermark of the anti-attack. The simulation results demonstrate that the algorithm can achieve the requirement of robustness and invisibility. the algorithm is safe that the anti-attack performance of the watermark is superior to the general DCT algorithm.
Roiabr / Final Project Phishing Detection On BEC AttackA machine learning algorithms to detect a BEC Attack
Phat3 / Ddsa Side Channel AttackActive side channel attack against Deterministic DSA algorithm
jogonba2 / Cipher Type DetectionMachine learning system for identifying unknown cipher/hash algorithms based on bit variations among plaintext-keyword-ciphertext (chosen-plaintext attack).
khovratovich / TradeoffAlgorithms for tradeoff attacks
alevkov / Ddos DetectAn algorithm for identifying ddos attacks in a window of network traffic.
drmick / Rust Hashcash DdosThe application shows how to resist DDOS attacks using proof of work algorithm
SherinBK / Invisible Digital WatermarkingThe "Image Watermarking for copyright authentication" project aims to develop a robust system using digital watermarking techniques to protect digital images from unauthorized use and distribution, with efficient algorithms that can withstand common image alteration attacks.
rccreager / HidefaceA set of tools for implementing popular face detection algorithms and adversarial attacks, then validating (non) detection after attack
huangyebiaoke / Adversarial Attack Method Based On IGANeural Network Adversarial Attack Method Based on Improved Genetic Algorithm
ivinjohn98 / Algorithm For Detecting DDoS AttackAn Adaptive Algorithm for Detection of Distributed Denial of Service attacks using entropy in dataset
