ETSI

The goal is to have a technical survey for mitigating against threats introduced by adopting AI into systems. The technical survey shed light on available methods of securing AI-based systems by mitigating against known or potential security threats. It also addresses security capabilities, challenges, and limitations when adopting mitigation for AI-based systems in certain potential use cases

Methods for testing whether TETRA Voice plus Data (V+D) Base Station (BS) and Mobile Station (MS) equipment and TETRA Direct Mode Operation (DMO) equipment achieve the performance specified in ETSI EN 300 392-2 [1]. Specific test methods for DMO equipment are recommended in annex F of the present document. The purpose of these specifications is to provide a sufficient quality of radio transmission and reception for equipment operating in a TETRA system and to minimize harmful interference to other equipment. The present document is applicable to TETRA systems operating at radio frequencies in the range of 137 MHz to 1 GHz. Versions V3.3.1 [i.5] and earlier of the present document specified the methods used for type testing. The minimum technical characteristics of TETRA Voice plus Data (V+D) Base Station (BS) and Mobile Station (MS) equipment and TETRA Direct Mode Operation (DMO) equipment and radio test methods to be used for providing presumption of conformity, are now specified in ETSI EN 303 758

The present document is a choice of Test Purposes Description Language (TPDL), with the intention to capture all of the information required by the Test Template and should be parseable using software.

The Testing Framework (document format) specifies a testing framework defining a methodology for the development of the test strategies, test systems and resulting test specifications. The present document identifies the implementation under test (scope of the testing), the format for the test specification, the test architecture, the points of control and observation, the naming conventions (e.g. for test case ID and test case grouping ID), etc. It also provides the Implementation Conformance Statement which is basically a checklist for a client-owner so they know what parts of the specification will be tested and if any is optional. The ICS will be published as a separate GS.

The present document establishes the minimum RF characteristics and minimum performance requirements for E-UTRA User Equipment (UE).

The present document specifies the protocol conformance testing for the 3GPP UE connecting to the 5G System (5GS) via its radio interface(s). The following information can be found in the present document (first part of a multi-part test specification): - the overall test structure; - the test configurations; - the conformance requirement and references to the core specifications; - the test purposes; and - a brief description of the test procedure, the specific test requirements and short message exchange table. The applicability of the individual test cases is specified in the ICS proforma specification (3GPP TS 38.523-2 [2]). The Test Suites are specified in part 3 (3GPP TS 38.523-3 [3]). The present document is valid for UE implemented according to 3GPP Releases starting from Release 15 up to the Release indicated on the cover page of the present document.

The document focuses on the functionalities enabled via the Mp1 reference point between MEC applications and MEC platform, which allows these applications to interact with the MEC system. Service related functionality includes registration/deregistration, discovery and event notifications. Other functionality includes application availability, traffic rules, DNS and time of day. It describes the information flows, required information, and specifies the necessary operations, data models and API definitions.

The present document describes the problem of securing AI-based systems and solutions, with a focus on machine learning, and the challenges relating to confidentiality, integrity and availability at each stage of the machine learning lifecycle. It also describes some of the broader challenges of AI systems including bias, ethics and explainability. A number of different attack vectors are described, as well as several real-world use cases and attacks.