apk multi tool download capable of baksmaling

#Apk multi tool download capable of baksmaling android#
#Apk multi tool download capable of baksmaling software#
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Artificial intelligence, machine learning, and deep learning tools have been elucidating very efficient abilities in capturing hidden patterns of information and inferring useful knowledge that would be capable of unraveling intricate attacks. These approaches are facing challenges such as the high false positive rates, or a limited capacity to detect complex, persistently-evolved ransomware attacks ideally before the files are encrypted or the system is damaged.

In the literature, the research community developed different solutions to combat ransomware, such as the use of honeypots, or the use of statistical methods. Indeed, it is a requirement to design an effective ransomware detection approach.

#Apk multi tool download capable of baksmaling code#

Even that its source code is available online but safeguarding against it is hard.

#Apk multi tool download capable of baksmaling software#

Ransomware is a kind of malware software that hinders the user with the infected mobile from accessing their data due to either data encryption or device locking, while the attacker waits for a ransom to decrypt the data or unlock the cellular device.

#Apk multi tool download capable of baksmaling android#

In, it had been reported that a single family of mobile ransomware had a negative effect on one million Android users in one month. Malware software comes in different forms such as spyware, ransomware, trojans, worms, viruses, or others. Malware is a malicious software accesses and hijacks computer or mobile systems, which eventually could damage, steal, encrypt, or disable the system files or data. Even that, it constitutes a favorable environment for malicious applications to disseminate. Recently, it has been considerably popular for smartphones and the Internet of things devices. Android is an operating system manufactured using a Linux-based kernel for cellular phones. Hence, the proposed SSA-KELM algorithm represents a promising approach for efficient ransomware detection.ĭay by day the number of mobile users exceptionally increases and approximately surpasses the 2.5 billion users worldwide. In addition, it has a competitive convergence ability. The performance of the proposed (SSA-KELM) exhibits noteworthy advantages based on several evaluation measures, including accuracy, recall, true negative rate, precision, g-mean, and area under the curve of a value of 98%, and a ratio of 2% of false positive rate. Meanwhile, the KELM algorithm is utilized for the identification and classification of the apps into benign or ransomware. Then, a hybrid of the Salp Swarm Algorithm (SSA) and Kernel Extreme Learning Machine (KELM) is modeled, where the SSA is used to search for the best subset of features and optimize the KELM hyperparameters. Raw sequences of the applications API calls and permissions were extracted to capture the ransomware pattern of behaviors and build the detection framework. In this article, a framework based on metaheuristic and machine learning is proposed for the detection of Android ransomware. A serious common threat is the ransomware attack, which locks the system or users’ data and demands a ransom for the purpose of decrypting or unlocking them. In recent years, a substantial increasing rate of malicious efforts to attack smartphone vulnerabilities has been noticed. Even that smartphones bring numerous facilities, but they form a wide gate into personal and financial information. Nowadays, smartphones are an essential part of people’s lives and a sign of a contemporary world.