Introduction to Api Calls

With these methods, data is created by reading the information in the file without running the malicious software, or by examining the places it affects such as changes on the network at runtime, api calls.

However, it is troublesome to insert API calls into the original sequence to cover the malicious purpose with implementation on GAN.

For solve this problem, this research proposed antivirus signature based on DLL Files and API Calls of ransomware files.

In this paper, we propose a malware classification model with RNN, especially the long short-term memory (LSTM) and the gated recurrent unit (GRU), to classify variants of malware by using long-sequences of API calls.

The results reveal a multitude of issues, ranging from an over-claim of sensitive permissions and the use of possibly privacy-invasive API calls, to numerous potentially exploitable CWE and CVE-identified weaknesses and vulnerabilities, the, in some cases, excessive employment of third-party trackers, and a number of other flaws related to the use of third-party software libraries, unsanitised input, and weak user password policies, to mention just a few.

By instrumenting Codeplay’s ComputeAorta[2] OpenCL implementation, it is possible to record OpenCL API calls and to reconstruct the execution graph as seen by the OpenCL device driver.

Through the creation of source-specific textual configuration files, RAMOSE enables the querying of SPARQL endpoints via simple Web RESTful API calls that return either JSON or CSV-formatted data, thus hiding all the intrinsic complexities of SPARQL and RDF from common Web users.

The other major contribution in this paper is identifying the Windows API calls for each of the adversary techniques based on the MITRE ATT&CK.

A total of 77,702 API calls processed an estimated 167,179 text records, which took a total of 1,979 processing-minutes (33.

With ChemProps, other polymer databases can remove duplicate entries and enable a more accurate “search by SMILES” function by using ChemProps as a common name-to-SMILES translator through API calls.

We serialize the key function in light of the sequence of API calls and pick up a similar module that captures the global semantics of malware.

Manually detecting and replacing deprecated APIs is a tedious and time-consuming task due to the large number of API calls used in the projects.

This paper focuses on an important optimization opportunity in Python-hosted domain-specific languages (DSLs): the use of laziness for optimization, whereby multiple API calls are deferred and then optimized prior to execution (rather than executing eagerly, which would require executing each call in isolation).

There are remarkable efforts in static and dynamic malware analysis using static features and API calls respectively.

sg) was matched to postal code and geographical coordinates via OneMAP API calls.

The main challenge is to synthesize well-typed Rust programs to account for proper chaining of API calls and Rust’s ownership type system and polymorphic types.

Methods For images, pseudonymization of PIDs is done using API calls that receive PIDs present in Digital Imaging and Communications in Medicine (DICOM) headers and returns the pseudonymized identifiers.

Furthermore, the user can extend µSE by customizing the API calls targeted by the mutation analysis.

</p><p>The openEO H2020 project (2017-2020) has developed the API as well as an ecosystem of software around it, including clients (JavaScript, Python, R, QGIS, browser-based), back-ends that translate API calls into existing image analysis or GIS software or services (for Sentinel Hub, WCPS, Open Data Cube, GRASS GIS, GeoTrellis/GeoPySpark, and GEE) as well as a hub that allows querying and searching openEO providers for their capabilities and datasets.

For the purpose of detect malware injection The hypervisor injection attack proposed in this paper by using a method of X-cross application programming interface calls (API-HI-attack) raises awareness that malware is injecting into the simulation tool with X-cross-language API calls.

With package structures and API calls being used as features, the classifying of those candidates is accomplished through coarse and fine-grained filtering.

sg) was matched to postal code and geographical coordinates via OneMAP API calls.

However, they fail to exploit the high-order connectivity of the interaction of API calls and the structural information of software projects.

Additionally, by analyzing all external package API calls in these JavaScript files, we found that a high percentage of these API calls are attributed to trivial packages.

The first encompasses permissions, API calls, and possible connections to external URLs, while the second concentrates on potential security weaknesses and vulnerabilities, including the use of trackers, in-depth manifest analysis, shared software analysis, and taint analysis.

Countermeasures of the detection methods could consist in fixing the bug exploited in the analysis tool or directly modifying results returned by API calls or handling self-modifying code in a smart way.

Malware developers use complex techniques to produce malware variants, by removing, replacing, and adding useless API calls to the code, which are specifically designed to evade detection mechanisms, as well as do not affect the original functionality of the malicious code involved.

In this work, we configure several feature sets for dynamic malware detection extracted from API calls, including an alternative scheme grouping calls in categories, network activity, signatures from the Cuckoo sandbox report, and some interactions with the file system and registry.

In this paper, it is proposed to use NLP methods, such as word embedding, and LDA in relation to the problems of analyzing malware API calls sequences in order to reveal the presence of semantic dependencies and assess the effectiveness of the application of these methods.

Application executions are represented by sequences of consecutive API calls.

However, these countermeasures rely heavily on identifying specific API calls, which has significant limitations as these calls can be misleading or hidden from the analyst.

Beyond package embedding, we use keywords and API calls as resilient features, which reflect the programmer’s intention and style.

After obtaining the central nodes, the average intimacies between sensitive API calls and central nodes are computed to represent the semantic features of the graphs.

, processing and visualizing 3D data can be achieved by few lines of API calls).

Hence, various API mining techniques have been introduced to mine API usage patterns about the co-occurring of API calls or pre-conditions of API calls.

This paper used Debug application programming interface (API) technology to obtain the features of API calls as viruses, filtered API calls according to information entropy, and finally used the support vector machine (SVM) model for virus detection.

In our unique method, a sequence of system API calls is extracted using tracker filter drivers in a sandbox environment.

But the execution of callbacks can also come from direct calls of the framework (API calls).

In an empirical evaluation on 12 subject applications containing 316 synchronous API calls, Desynchronizer identified 256 of these as candidates for refactoring.

Moreover, involving clarification questions and user feedbacks makes the system unusable by one shot API calls, which is the most intuitive usage among common use cases in industry like automated report generation.

We designed and implemented FOCUS as a novel approach to provide developers with API calls and source code while they are programming.

We used a 1-Dimensional CNN by mapping API calls as categorical and term frequency-inverse document frequency (TF-IDF) vectors and compared the results to other classification techniques.

There are different languages like Python, MATLAB, R and much more which have libraries for statistical mathematics and make simple API calls to do the required experiments within any dataset.

In this study, we consider permission and API calls as features that help in developing a model for malware detection.

Since accessing and sending data is usually done via API calls, tracking the data flow between source and sink API is often the method of choice.

Ubi-Interact lets users build real-time systems with modular components that can separate system behaviour from base API calls, leaving the user free to explore and maintain a combination of software and hardware each running in their native environment.

And also further deploy it in such a way that it'll be easy to integrate and easy to use with API calls.

We also illustrate how to train birdspotter into a fully-fledged bot detector that achieves better than state-of-the-art performances without making Twitter API calls, and we showcase its usage in an exploratory analysis of a topical COVID-19 dataset.

Our approach has been integrated into RESTest, a state-of-the-art tool for API testing, achieving an unprecedented level of automation which allows to generate up to 100% more valid API calls than existing fuzzing techniques, 30% on average.

The evaluation, considering 1000 legitimate and ransomware applications, demonstrates that the hybrid API calls-based detection can be proved to be a promising direction in ransomware prevention and mitigation.

It is also the key component for being able to predict API calls accurately.

The recommender system is generated by applying Cosine similarity and making API Calls.

Our main idea is to granularly manage application permissions and encrypt REST API calls to defend against malicious attacks.

Atop this new inter-procedural analysis, we further adjust the traditional backward slicing and forward constant propagation to provide the complete dataflow tracking of sink API calls.

We transform the app by placing a wrapper around the app, called App2SecApp, to ensures safe executional monitoring in terms of: (1) behavioral invariance of the app, and (2) monitoring of sensitive API calls and prompting the user, if there is a possible leakage from the app's sandbox through any of the API calls.

Modern malware classification techniques rely on machine learning models that can be trained on features such as opcode sequences, API calls, and byte n-grams, among many others.

The proposed multi-level memory scheduling method places data in a key-value storage, flushes sensor data when the edge memory is full, and reduces the number of I/O operations, network latency, and the number of REST API calls in the edge cloud.

Our objective is to measure the current practice of declared SDK versions (which we term as DSDK versions afterwards) in real apps, and the (in)consistency between DSDK versions and their host apps’ API calls.

The framework extracts requested permissions and API calls from Android malware samples and uses them as features to train a large set of machine learning classifiers.

Furthermore, all the existing methods use the features obtained only from the app stores such as description and rating, which could be inaccurate, varied in different stores, and affected by language barrier; they totally neglect useful information clearly capturing the app’s functionalities and behaviors that can be mined from the apps themselves such as the API calls and manifest information.

We discussed about dynamic analysis and Windows API Calls.

Then, it builds clones that mimic the application code in terms of the type of operations, the number and size of network calls with external servers and API calls made at different layers of the technology stack.

In this study, the authors extract sequences of API calls using dynamic analysis and then use colour mapping rules to create feature images representing malware behaviour.

It builds a complete call graph for Android applications and identifies call traces from entry methods to sensitive API calls.

M2 introduces a new data-centric approach that leverages higher-level device abstractions and hardware acceleration to efficiently share device data, not API calls.

Based on the preliminary studies, we design LpGL so that it uses the device's gaze/head orientation information and geometry data to infer user perception information, intercepts application-level graphics API calls, and employs frame rate control, mesh simplification, and culling techniques to enhance energy efficiency of AR headsets without detriment of user experience.

Most previous malware detection approaches mainly rely on features such as permissions, API calls, and opcode sequences.

Ideally, our presentation would be based on API calls to the data itself, eliminating the need to transform and re-load after every change.

We then propose a method to convert the multiple sequential data (API calls) to a family behavior graph for further analysis.

The method monitors behavior points based on API calls and then uses the calling sequence of those behavior points at runtime to construct a behavior chain.

However, many security risks have arisen due to improper usage of these libraries mainly due to the wrong sequence of API calls.

You can use REST API calls to automate the configuration as part of the infrastructure automation.

In this paper, we investigate the four predominant domains of registry, DLL, API calls and network connections in memory forensics to implement the system ‘Malfore,’ which helps automate the entire process of memory forensics.

In this paper, we provide the second part of the CICAndMal2017 dataset [16] publicly available which includes permissions and intents as static features, and API calls as dynamic features.

These paths chain together API calls and use the output of executed APIs as inputs to others.

By working with various app features such as binary N-grams of API calls, we will generate feature sets consisting of a selected range of binary N-grams.

In this study, an LSTM based classification method was developed by using API calls of 8 different types of real malware.

There are many researches done in this field, however, most researchers used n-gram to detect the sequence of API calls and although it gave good results, it is time consuming to process through all the output.

Firstly, the API calls are obtained through static analysis to generate API call graphs that contain the relationships among APIs.

API management and classification is a cumbersome task considering the rapid increase in the number of APIs, and API to API calls.

The proposed model uses a new and unique mapping technique between each Facebook Like object to their corresponding Facebook page category/sub-category object extracted from the API calls as Likes metadata, which is then evaluated as features for a set of machine learning algorithms to predict individual psychodemographic profiles from users Likes.

In this paper, we describe how the API developer can use patterns to map sentences to API calls by utilizing the similarities between names and types in the sentences and the API.

Since the release in 2016, Microsoft Concept Graph has received more than 100,000 pageviews, 2 million API calls and 3,000 registered downloads from 50,000 visitors over 64 countries.